From dca085e50301d4cb3be0236e1220f6b30926dcd6 Mon Sep 17 00:00:00 2001 From: odidev Date: Mon, 25 Aug 2025 09:47:26 +0000 Subject: [PATCH 01/31] Deploy Envoy on Google Axion C4A Arm virtual machine Signed-off-by: odidev --- .../envoy-gcp/_index.md | 57 + .../envoy-gcp/_next-steps.md | 8 + .../envoy-gcp/background.md | 23 + .../envoy-gcp/baseline-testing.md | 141 ++ .../envoy-gcp/benchmarking.md | 1163 +++++++++++++++++ .../envoy-gcp/deploy.md | 57 + .../envoy-gcp/image1.png | Bin 0 -> 58872 bytes .../envoy-gcp/instance.md | 30 + 8 files changed, 1479 insertions(+) create mode 100644 content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md create mode 100644 content/learning-paths/servers-and-cloud-computing/envoy-gcp/_next-steps.md create mode 100644 content/learning-paths/servers-and-cloud-computing/envoy-gcp/background.md create mode 100644 content/learning-paths/servers-and-cloud-computing/envoy-gcp/baseline-testing.md create mode 100644 content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md create mode 100644 content/learning-paths/servers-and-cloud-computing/envoy-gcp/deploy.md create mode 100644 content/learning-paths/servers-and-cloud-computing/envoy-gcp/image1.png create mode 100644 content/learning-paths/servers-and-cloud-computing/envoy-gcp/instance.md diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md new file mode 100644 index 0000000000..81bb86d21e --- /dev/null +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md @@ -0,0 +1,57 @@ +--- +title: Deploy Envoy on Google Axion processors + +minutes_to_complete: 30 + +who_is_this_for: This introductory topic is for software developers interested in migrating their Envoy workloads from x86_64 platforms to Arm-based platforms, specifically on Google Axion–based C4A virtual machines. + +learning_objectives: + - Start an Arm virtual machine on Google Cloud Platform (GCP) using the C4A Google Axion instance family with RHEL 9 as the base image + - Install and configure Envoy on Arm-based GCP C4A instances + - Validate Envoy functionality through baseline testing + - Benchmark Envoy performance on Arm + +prerequisites: + - A [Google Cloud Platform (GCP)](https://cloud.google.com/free?utm_source=google&hl=en) account with billing enabled + - Familiarity with networking concepts and the [Envoy architecture](https://www.envoyproxy.io/docs/envoy/latest/). + +author: Pareena Verma + +##### Tags +skilllevels: Advanced +subjects: Web +cloud_service_providers: Google Cloud + +armips: + - Neoverse + +tools_software_languages: + - Envoy + - Siege + +operatingsystems: + - Linux + +# ================================================================================ +# FIXED, DO NOT MODIFY +# ================================================================================ +further_reading: + - resource: + title: Google Cloud official documentation + link: https://cloud.google.com/docs + type: documentation + + - resource: + title: Envoy documentation + link: https://www.envoyproxy.io/docs/envoy/latest/about_docs + type: documentation + + - resource: + title: The official documentation for Siege + link: https://www.joedog.org/siege-manual/ + type: documentation + +weight: 1 # _index.md always has weight of 1 to order correctly +layout: "learningpathall" # All files under learning paths have this same wrapper +learning_path_main_page: "yes" # Indicates this should be surfaced when looking for related content. Only set for _index.md of learning path content. +--- diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_next-steps.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_next-steps.md new file mode 100644 index 0000000000..c3db0de5a2 --- /dev/null +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_next-steps.md @@ -0,0 +1,8 @@ +--- +# ================================================================================ +# FIXED, DO NOT MODIFY THIS FILE +# ================================================================================ +weight: 21 # Set to always be larger than the content in this path to be at the end of the navigation. +title: "Next Steps" # Always the same, html page title. +layout: "learningpathall" # All files under learning paths have this same wrapper for Hugo processing. +--- diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/background.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/background.md new file mode 100644 index 0000000000..97dafae372 --- /dev/null +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/background.md @@ -0,0 +1,23 @@ +--- +title: Getting started with Envoy on Google Axion C4A (Arm Neoverse-V2) + +weight: 2 + +layout: "learningpathall" +--- + +## Google Axion C4A Arm instances in Google Cloud + +Google Axion C4A is a family of Arm-based virtual machines built on Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high-performance and energy-efficient computing, these virtual machines offer strong performance for modern cloud workloads such as CI/CD pipelines, microservices, media processing, and general-purpose applications. + +The C4A series provides a cost-effective alternative to x86 virtual machines while leveraging the scalability and performance benefits of the Arm architecture in Google Cloud. + +To learn more about Google Axion, refer to the [Introducing Google Axion Processors, our new Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu) blog. + +## Envoy for service proxying and traffic management on Arm + +Envoy is an open-source, high-performance edge and service proxy designed for cloud-native applications. + +It handles service-to-service communication, traffic routing, load balancing, and observability, making microservices more reliable and secure. + +Envoy is widely used in service meshes, API gateways, and modern cloud environments. Learn more from the [Envoy official website](https://www.envoyproxy.io/) and its [official documentation](https://www.envoyproxy.io/docs/envoy/latest/). diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/baseline-testing.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/baseline-testing.md new file mode 100644 index 0000000000..16b53ba8c6 --- /dev/null +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/baseline-testing.md @@ -0,0 +1,141 @@ +--- +title: Envoy baseline testing on Google Axion C4A Arm Virtual machine +weight: 5 + +### FIXED, DO NOT MODIFY +layout: learningpathall +--- + + +Since Envoy is installed successfully on your GCP C4A Arm virtual machine, follow these steps to validate that the Envoy is running. + +## Validate Envoy installation with a baseline test + +In this section, we covered how to create a minimal Envoy config, start Envoy with it, and verify functionality using `curl`. +The test confirmed that Envoy listens on port **10000**, forwards requests to `httpbin.org`, and returns a successful **200 OK** response. + +### Create a Minimal Configuration File + +Using a file editor of your choice, create a file named `envoy_config.yaml`, and add the below content to it. This file configures Envoy to listen on port **10000** and forward all traffic to `http://httpbin.org`. The host_rewrite_literal is essential to prevent 404 Not Found errors from the upstream server. + +```YAML +static_resources: + listeners: + - name: listener_0 + address: + socket_address: + protocol: TCP + address: 0.0.0.0 + port_value: 10000 + filter_chains: + - filters: + - name: envoy.filters.network.http_connection_manager + typed_config: + "@type": type.googleapis.com/envoy.extensions.filters.network.http_connection_manager.v3.HttpConnectionManager + stat_prefix: ingress_http + route_config: + name: local_route + virtual_hosts: + - name: backend + domains: ["*"] + routes: + - match: + prefix: "/" + route: + cluster: service_httpbin + host_rewrite_literal: httpbin.org + http_filters: + - name: envoy.filters.http.router + typed_config: + "@type": type.googleapis.com/envoy.extensions.filters.http.router.v3.Router + clusters: + - name: service_httpbin + connect_timeout: 0.5s + type: LOGICAL_DNS + dns_lookup_family: V4_ONLY + lb_policy: ROUND_ROBIN + load_assignment: + cluster_name: service_httpbin + endpoints: + - lb_endpoints: + - endpoint: + address: + socket_address: + address: httpbin.org + port_value: 80 +``` +- **Listeners:** Envoy is configured to accept incoming HTTP requests on port **10000** of your VM. +- **HTTP Connection Manager:** A filter processes the incoming requests, directing them to the appropriate backend. +- **Routing:** All traffic is routed to the `service_httpbin` cluster, with the `Host` header rewritten to `httpbin.org`. +- **Clusters:** The `service_httpbin` cluster defines the upstream service as `httpbin.org` on port **80**, which is where requests are ultimately forwarded. + +### Run and Test Envoy + +This is the final phase of functional validation, confirming that the proxy is operational. +Start the Envoy proxy using your configuration file. This command will keep the terminal occupied, so you will need a new terminal for the next step. + +```console + envoy -c envoy_config.yaml --base-id 1 +``` +The output should look similar to: + +```output +[2025-08-21 11:53:51.597][67137][info][config] [source/server/configuration_impl.cc:138] loading 1 listener(s) +[2025-08-21 11:53:51.597][67137][info][config] [source/server/configuration_impl.cc:154] loading stats configuration +[2025-08-21 11:53:51.598][67137][warning][main] [source/server/server.cc:928] There is no configured limit to the number of allowed active downstream connections. Configure a limit in `envoy.resource_monitors.downstream_connections` resource monitor. +[2025-08-21 11:53:51.598][67137][info][main] [source/server/server.cc:969] starting main dispatch loop +[2025-08-21 11:53:51.599][67137][info][runtime] [source/common/runtime/runtime_impl.cc:614] RTDS has finished initialization +[2025-08-21 11:53:51.599][67137][info][upstream] [source/common/upstream/cluster_manager_impl.cc:240] cm init: all clusters initialized +[2025-08-21 11:53:51.599][67137][info][main] [source/server/server.cc:950] all clusters initialized. initializing init manager +[2025-08-21 11:53:51.599][67137][info][config] [source/common/listener_manager/listener_manager_impl.cc:930] all dependencies initialized. starting workers +``` + +Now, **Send a test request** from another terminal window to the Envoy listener using `curl`. + +```console +curl -v http://localhost:10000/get +``` +The `-v` flag provides verbose output, showing the full request and response headers. A successful test will show a **HTTP/1.1 200 OK** response with a JSON body from httpbin.org. + +The output should look similar to: + +```output +* Trying 127.0.0.1:10000... +* Connected to 127.0.0.1 (127.0.0.1) port 10000 (#0) +> GET /get HTTP/1.1 +> Host: 127.0.0.1:10000 +> User-Agent: curl/7.76.1 +> Accept: */* +> +* Mark bundle as not supporting multiuse +< HTTP/1.1 200 OK +< date: Fri, 22 Aug 2025 11:20:35 GMT +< content-type: application/json +< content-length: 301 +< server: envoy +< access-control-allow-origin: * +< access-control-allow-credentials: true +< x-envoy-upstream-service-time: 1042 +< +{ + "args": {}, + "headers": { + "Accept": "*/*", + "Host": "httpbin.org", + "User-Agent": "curl/7.76.1", + "X-Amzn-Trace-Id": "Root=1-68a85282-10af9cfe0385774600509ddd", + "X-Envoy-Expected-Rq-Timeout-Ms": "15000" + }, + "origin": "34.63.220.63", + "url": "http://httpbin.org/get" +} +* Connection #0 to host 127.0.0.1 left intact +``` +#### Summary of the curl Output + +- **Successful Connection:** The **curl** command successfully connected to the Envoy proxy on **localhost:10000**. +- **Correct Status Code:** Envoy successfully forwarded the request and received a healthy **200 OK** response from the upstream server. +- **Host Header Rewrite:** The **Host** header was correctly rewritten from **localhost:10000** to **httpbin.org** as defined in the configuration. +- **End-to-End Success:** The proxy is fully operational, proving that requests are correctly received, processed, and forwarded to the intended backend. + +This confirms the end-to-end flow is working correctly. diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md new file mode 100644 index 0000000000..530ee5ce12 --- /dev/null +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md @@ -0,0 +1,1163 @@ +--- +title: Envoy performance benchmarks on Arm64 and x86_64 in Google Cloud +weight: 6 + +### FIXED, DO NOT MODIFY +layout: learningpathall +--- + +## How to run Envoy benchmarks with Siege on Arm64 in GCP + +**Siege** is a lightweight HTTP load testing and benchmarking tool that simulates concurrent users making requests to a target service. It is useful for **Envoy benchmarking** because it measures availability, throughput, response time, and failure rates under load—helping evaluate Envoy’s performance as a proxy under real-world traffic conditions. + +Follow the steps outlined to run Envoy benchmarks using the Siege. +### Install Siege(Build from Source) + +1. Install required build tools + +```console +sudo dnf groupinstall -y "Development Tools" +sudo dnf install -y wget make gcc +``` +2. Download, extract and build Siege source + +```console +wget http://download.joedog.org/siege/siege-4.1.6.tar.gz +tar -xvzf siege-4.1.6.tar.gz +cd siege-4.1.6 +./configure +make +sudo make install +``` +These commands prepare Siege for your system, build (compile) it, and then install it so you can run it from anywhere. + +3. Verify installation + +```console +siege --version +``` +This checks if Siege is installed properly and shows the version number. +```output +SIEGE 4.1.6 + +Copyright (C) 2023 by Jeffrey Fulmer, et al. +This is free software; see the source for copying conditions. +There is NO warranty; not even for MERCHANTABILITY or FITNESS +FOR A PARTICULAR PURPOSE. +``` +### Envoy Benchmarking + +1. Ensure Envoy is Running + +To make sure your Envoy proxy is up with your config file (listening on port 10000 for example): + +```console +envoy -c envoy_config.yaml --base-id 1 +``` +This runs the Envoy proxy with your configuration file (envoy_config.yaml) so it can start listening for requests. + +2. Verify with curl from the another terminal: + +``` +curl -v http://127.0.0.1:10000/get +``` +Running from another terminal returns a **200 OK** status, confirming that Envoy is running and successfully proxying requests. + +3. Run a Time-based Load Test + +Benchmark for a fixed time instead of request count: + +```console +siege -c30 -t10S http://127.0.0.1:10000/get +``` +This runs a load test where 30 users hit Envoy continuously for 10 seconds. After this, Siege will show performance results. + +The output should look similar to: + +```output +** SIEGE 4.1.6 +** Preparing 30 concurrent users for battle. +The server is now under siege... +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes 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200 0.68 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.34 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.95 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.91 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.17 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.19 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.38 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.87 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.26 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.09 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.09 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.48 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.61 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.40 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.42 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.52 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.52 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.37 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.20 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.61 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.96 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.57 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.48 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.07 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.47 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.39 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.83 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.28 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.65 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.88 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.59 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.20 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.66 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.23 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.62 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.41 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.10 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 2.21 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.48 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.55 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.25 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.14 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.90 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.70 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.98 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.64 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.07 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.30 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.07 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.22 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.62 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.43 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.70 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.42 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.79 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.15 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.67 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.54 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.81 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.59 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.34 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.69 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.86 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.55 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.53 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.43 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.28 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.15 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.28 secs: 383 bytes ==> GET /get +HTTP/1.1 200 2.55 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.58 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.63 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.27 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.25 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.36 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.45 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.67 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.43 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 2.27 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.15 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.28 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.16 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.12 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.63 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.58 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.07 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.65 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.98 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.23 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.10 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.10 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.63 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.34 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.21 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.54 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.00 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.11 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.23 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.49 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.31 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.25 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.11 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.38 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.41 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.60 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.81 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.14 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.10 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.31 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.36 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.62 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.46 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.18 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.46 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.09 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.09 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.82 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.89 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.38 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.51 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.80 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.44 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.16 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.07 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.63 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.62 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.10 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.23 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.02 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.37 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.61 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.57 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.83 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.49 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.66 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.10 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.34 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.22 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.19 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.52 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.63 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.19 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.19 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.81 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.80 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.48 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.66 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.68 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.33 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.16 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.80 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.83 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.57 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.29 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.49 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.23 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.07 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.58 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.18 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.34 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.19 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.28 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.31 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.43 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.45 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.48 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.16 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.14 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.15 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.29 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.58 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.75 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.60 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.18 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.68 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.11 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.07 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.78 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.96 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.41 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.29 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.47 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.42 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.75 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.84 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.14 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.60 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.02 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.95 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.16 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.23 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.59 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.23 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.12 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.20 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.54 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.81 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.25 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.36 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.76 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.39 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.15 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.84 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.50 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.14 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.11 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.76 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.56 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.69 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.09 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.18 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.68 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.56 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.58 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.64 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 502 0.36 secs: 122 bytes ==> GET /get +HTTP/1.1 200 0.54 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.57 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.66 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.31 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.12 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.39 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.69 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.49 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.79 secs: 383 bytes ==> GET /get +HTTP/1.1 200 2.81 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.25 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.62 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.39 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.78 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.14 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.69 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.10 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.72 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.40 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.66 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.62 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.93 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.59 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.17 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.18 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.43 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.51 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.39 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.54 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.11 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.23 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.16 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.29 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.75 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.32 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.64 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.15 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.84 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.28 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.58 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.54 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.59 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.93 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.09 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.07 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.93 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.51 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.96 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.44 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.14 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.57 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.33 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.46 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.89 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.60 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.31 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.44 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.36 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.46 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.31 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.16 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.36 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.35 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.33 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.74 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.24 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.42 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.09 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.33 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.14 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.12 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.23 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.33 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.53 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.21 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.56 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.92 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.14 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.68 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.18 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.16 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.34 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.27 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.65 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.18 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.66 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.20 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.36 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.25 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.02 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.66 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.36 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.10 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.47 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.59 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.39 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.40 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.22 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.57 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.17 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.48 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.74 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.32 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.39 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.06 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.24 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.14 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.69 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 2.35 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.83 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.67 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.55 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.60 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.73 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.07 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.28 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.28 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.56 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.73 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.07 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.39 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.53 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.33 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.12 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.78 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.57 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.61 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.49 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.90 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.13 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.02 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.26 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.45 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.20 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.98 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.53 secs: 383 bytes ==> GET /get +HTTP/1.1 200 2.10 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.27 secs: 383 bytes ==> GET /get +HTTP/1.1 200 2.45 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.74 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.46 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.31 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.39 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.48 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.99 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.26 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.53 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.12 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.02 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.80 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.67 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.37 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.07 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.26 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.21 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.38 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.53 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.20 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.64 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 2.89 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.20 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.04 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.08 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.64 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.46 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.81 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.51 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.61 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.35 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.91 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.35 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.91 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.05 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.53 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.51 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.37 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.02 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.42 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.03 secs: 383 bytes ==> GET /get +HTTP/1.1 200 1.17 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.81 secs: 383 bytes ==> GET /get +HTTP/1.1 200 0.14 secs: 383 bytes ==> GET /get + +Lifting the server siege... +Transactions: 1019 hits +Availability: 99.80 % +Elapsed time: 10.38 secs +Data transferred: 0.37 MB +Response time: 0.29 secs +Transaction rate: 98.17 trans/sec +Throughput: 0.04 MB/sec +Concurrency: 28.07 +Successful transactions: 1019 +Failed transactions: 2 +Longest transaction: 2.89 +Shortest transaction: 0.02 +``` + +### Understanding Envoy benchmark metrics and results with Siege + +- **Transactions**: Total number of completed requests during the benchmark. +- **Availability**: Percentage of requests that returned a successful response. +- **Elapsed Time**: Total time taken to run the benchmark test. +- **Data Transferred**: Total amount of data exchanged during the test. +- **Response Time**: Average time taken for the server to respond to each request. +- **Transaction Rate**: Number of requests processed per second. +- **Throughput**: Volume of data transferred per second. +- **Concurrency**: Average number of simultaneous connections maintained. +- **Successful Transactions**: Total number of requests completed successfully. +- **Failed Transactions**: Total number of requests that failed. +- **Longest Transaction**: Maximum response time observed for a single request. +- **Shortest Transaction**: Minimum response time observed for a single request. + +### Benchmark summary on x86_64: +The following benchmark results were collected by running the same benchmark on a c3-standard-4 (4 vCPU, 2 core, 16 GB Memory) x86_64 virtual machine in GCP, running RHEL 9. + +| Metric | Value | Metric | Value | +|-------------------------|--------------|---------------------------|-----------------| +| Transactions | 720 hits | Availability | 98.90 % | +| Elapsed time | 10.98 secs | Data transferred | 0.26 MB | +| Response time | 0.44 secs | Transaction rate | 65.57 trans/sec | +| Throughput | 0.02 MB/sec | Concurrency | 28.66 | +| Successful transactions | 720 | Failed transactions | 8 | +| Longest transaction | 4.63 secs | Shortest transaction | 0.02 secs | + +### Benchmark summary on Arm64: +Results from the earlier run on the c4a-standard-4 (4 vCPU, 16 GB memory) Arm64 VM in GCP (RHEL 9): + +| Metric | Value | Metric | Value | +|-------------------------|---------------|---------------------------|-----------------| +| Transactions | 1019 hits | Availability | 99.80 % | +| Elapsed time | 10.38 secs | Data transferred | 0.37 MB | +| Response time | 0.29 secs | Transaction rate | 98.17 trans/sec | +| Throughput | 0.04 MB/sec | Concurrency | 28.07 | +| Successful transactions | 1019 | Failed transactions | 2 | +| Longest transaction | 2.89 secs | Shortest transaction | 0.02 secs | + +### Envoy performance benchmarking comparison on Arm64 and x86_64 +When you compare the benchmarking results you will notice that on the Google Axion C4A Arm-based instances: + +- Achieved **1019 successful transactions** with only **2 failures**, ensuring **99.80%** availability. +- Delivered a strong **transaction rate of 98.17 trans/sec** and throughput of **0.04 MB/sec**. +- Maintained low **response times (0.29 secs average)**, with a shortest transaction of **0.02 secs**. +- Demonstrated **stable concurrency handling (28.07)** and controlled latency, with the longest transaction completing in **2.89 secs.** diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/deploy.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/deploy.md new file mode 100644 index 0000000000..72adb14d9f --- /dev/null +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/deploy.md @@ -0,0 +1,57 @@ +--- +title: How to deploy Envoy on Google Axion C4A Arm virtual machines +weight: 4 + +### FIXED, DO NOT MODIFY +layout: learningpathall +--- + + +## How to deploy Envoy on a Google Axion C4A Arm virtual machine +This guide shows you how to install Envoy Proxy v1.30.0 on a Google Cloud Axion C4A virtual machine running RHEL 9. You’ll install the basic tools, download the official static Arm64 Envoy binary, give it executable permissions, and check the version. By the end, Envoy will be installed and ready to use on your GCP virtual machine — without needing Docker or building from source. + +1. Install Dependencies + +```console +sudo dnf install -y \ + autoconf \ + curl \ + libtool \ + patch \ + python3 \ + python3-pip \ + unzip \ + git +pip3 install virtualenv +``` + +2. Install Envoy (Static Arm64 Binary) + +This step downloads and installs the Envoy binary. +Download the binary directly to **/usr/local/bin/envoy**. The `-L` flag is crucial as it follows any redirects from the download URL. + +```console +sudo curl -L \ + -o /usr/local/bin/envoy \ + https://github.com/envoyproxy/envoy/releases/download/v1.30.0/envoy-1.30.0-linux-aarch_64 +``` +Make it executable so the system can run the binary as a command. + +```console +sudo chmod +x /usr/local/bin/envoy +``` +Verify the installation by checking its version. + +```console +envoy --version +``` +This confirms the binary is correctly placed and executable. + +You should see an output similar to: + +```output +envoy version: 50ea83e602d5da162df89fd5798301e22f5540cf/1.30.0/Clean/RELEASE/BoringSSL +``` +This confirms the binary is correctly placed and executable. + +Envoy installation is complete. 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a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/instance.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/instance.md new file mode 100644 index 0000000000..aa39cf2bf1 --- /dev/null +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/instance.md @@ -0,0 +1,30 @@ +--- +title: How to create a Google Axion C4A Arm virtual machine on GCP +weight: 3 + +### FIXED, DO NOT MODIFY +layout: learningpathall +--- + +## How to create a Google Axion C4A Arm VM on Google Cloud + +In this section, you learn how to provision a **Google Axion C4A Arm virtual machine** on Google Cloud Platform (GCP) using the **c4a-standard-4 (4 vCPUs, 16 GB memory)** machine type in the **Google Cloud Console**. + +For background on GCP setup, see the Learning Path [Getting started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/). + +### Create a Google Axion C4A Arm VM in Google Cloud Console + +To create a virtual machine based on the C4A Arm architecture: +1. Navigate to the [Google Cloud Console](https://console.cloud.google.com/). +2. Go to **Compute Engine > VM Instances** and select **Create Instance**. +3. Under **Machine configuration**: + - Enter details such as **Instance name**, **Region**, and **Zone**. + - Set **Series** to `C4A`. + - Select a machine type such as `c4a-standard-4`. + + ![Create a Google Axion C4A Arm virtual machine in the Google Cloud Console with c4a-standard-4 selected alt-text#center](./image1.png "Google Cloud Console – creating a Google Axion C4A Arm virtual machine") + +4. Under **OS and Storage**, select **Change**, then choose an Arm64-based OS image. + For this Learning Path, use **Red Hat Enterprise Linux 9**. Ensure you select the **Arm image** variant. Click **Select**. +5. Under **Networking**, enable **Allow HTTP traffic**. +6. Click **Create** to launch the instance. From 7a22274d349c27a5ae8b176c15f2943214221cbb Mon Sep 17 00:00:00 2001 From: Amal Augustine Jose Date: Mon, 1 Sep 2025 11:23:40 +0100 Subject: [PATCH 02/31] Update to ALP: Build an Android chat app with Llama, KleidiAI, ExecuTorch, and XNNPACK 1. Update model name typo in adb command to push model to target. 2. Added missing flag to cross-compile Executorch 3. Added newer text generation sample with better perfroamnce. Tested on Vivo X200 Pro. 3. Updated screenshots to reflect latest LlamaDemo Android Application --- .../5-run-benchmark-on-android.md | 83 ++++++++++-------- .../example-prompt-1.png | Bin 79713 -> 370958 bytes .../example-prompt-2.png | Bin 107757 -> 306420 bytes 3 files changed, 46 insertions(+), 37 deletions(-) diff --git a/content/learning-paths/mobile-graphics-and-gaming/build-llama3-chat-android-app-using-executorch-and-xnnpack/5-run-benchmark-on-android.md b/content/learning-paths/mobile-graphics-and-gaming/build-llama3-chat-android-app-using-executorch-and-xnnpack/5-run-benchmark-on-android.md index 4f07675eac..158c47cbc8 100644 --- a/content/learning-paths/mobile-graphics-and-gaming/build-llama3-chat-android-app-using-executorch-and-xnnpack/5-run-benchmark-on-android.md +++ b/content/learning-paths/mobile-graphics-and-gaming/build-llama3-chat-android-app-using-executorch-and-xnnpack/5-run-benchmark-on-android.md @@ -45,6 +45,7 @@ cmake -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \ -DEXECUTORCH_BUILD_KERNELS_CUSTOM=ON \ -DEXECUTORCH_BUILD_KERNELS_LLM=ON \ -DEXECUTORCH_BUILD_EXTENSION_LLM_RUNNER=ON \ + -DEXECUTORCH_BUILD_EXTENSION_LLM=ON \ -DEXECUTORCH_BUILD_EXTENSION_RUNNER_UTIL=ON \ -DEXECUTORCH_XNNPACK_ENABLE_KLEIDI=ON \ -DXNNPACK_ENABLE_ARM_BF16=OFF \ @@ -82,6 +83,10 @@ cmake --build cmake-out-android/examples/models/llama -j16 --config Release You should now have `llama_main` available for Android. +{{% notice Note %}} +If you notice that Gradle cannot find the Android SDK, add the sdk.dir path to executorch/extension/android/local.properties. +{{% /notice %}} + ## Run on Android via adb shell You will need an Arm-powered smartphone with the i8mm feature running Android, with 16GB of RAM. The following steps were tested on a Google Pixel 8 Pro phone. @@ -103,7 +108,7 @@ You should see your device listed to confirm it is connected. ``` bash adb shell mkdir -p /data/local/tmp/llama -adb push llama3_1B_kv_sdpa_xnn_qe_4_128_1024_embedding_4bit.pte /data/local/tmp/llama/ +adb push llama3_1B_kv_sdpa_xnn_qe_4_64_1024_embedding_4bit.pte /data/local/tmp/llama/ adb push $HOME/.llama/checkpoints/Llama3.2-1B-Instruct/tokenizer.model /data/local/tmp/llama/ adb push cmake-out-android/examples/models/llama/llama_main /data/local/tmp/llama/ ``` @@ -114,49 +119,53 @@ adb push cmake-out-android/examples/models/llama/llama_main /data/local/tmp/llam Use the Llama runner to execute the model on the phone with the `adb` command: ``` bash -adb shell "cd /data/local/tmp/llama && ./llama_main --model_path llama3_1B_kv_sdpa_xnn_qe_4_64_1024_embedding_4bit.pte --tokenizer_path tokenizer.model --prompt "<|start_header_id|>system<|end_header_id|>\nYour name is Cookie. you are helpful, polite, precise, concise, honest, good at writing. You always give precise and brief answers up to 32 words<|eot_id|><|start_header_id|>user<|end_header_id|>\nHey Cookie! how are you today?<|eot_id|><|start_header_id|>assistant<|end_header_id|>" --warmup=1 --cpu_threads=5 +adb shell "cd /data/local/tmp/llama && ./llama_main --model_path llama3_1B_kv_sdpa_xnn_qe_4_64_1024_embedding_4bit.pte --tokenizer_path tokenizer.model --prompt "<|start_header_id|>system<|end_header_id|>\nYour name is Cookie. you are helpful, polite, precise, concise, honest, good at writing. You always give precise and brief answers up to 32 words<|eot_id|><|start_header_id|>user<|end_header_id|>\nHey Cookie! how are you today?<|eot_id|><|start_header_id|>assistant<|end_header_id|>" --warmup=1 --cpu_threads=5" ``` The output should look something like this. ``` -I 00:00:00.003316 executorch:main.cpp:69] Resetting threadpool with num threads = 5 -I 00:00:00.009329 executorch:runner.cpp:59] Creating LLaMa runner: model_path=llama3_1B_kv_sdpa_xnn_qe_4_64_1024_embedding_4bit.pte, tokenizer_path=tokenizer.model -I 00:00:03.569399 executorch:runner.cpp:88] Reading metadata from model -I 00:00:03.569451 executorch:runner.cpp:113] Metadata: use_sdpa_with_kv_cache = 1 -I 00:00:03.569455 executorch:runner.cpp:113] Metadata: use_kv_cache = 1 -I 00:00:03.569459 executorch:runner.cpp:113] Metadata: get_vocab_size = 128256 -I 00:00:03.569461 executorch:runner.cpp:113] Metadata: get_bos_id = 128000 -I 00:00:03.569464 executorch:runner.cpp:113] Metadata: get_max_seq_len = 1024 -I 00:00:03.569466 executorch:runner.cpp:113] Metadata: enable_dynamic_shape = 1 -I 00:00:03.569469 executorch:runner.cpp:120] eos_id = 128009 -I 00:00:03.569470 executorch:runner.cpp:120] eos_id = 128001 -I 00:00:03.569471 executorch:runner.cpp:120] eos_id = 128006 -I 00:00:03.569473 executorch:runner.cpp:120] eos_id = 128007 -I 00:00:03.569475 executorch:runner.cpp:168] Doing a warmup run... -I 00:00:03.838634 executorch:text_prefiller.cpp:53] Prefill token result numel(): 128256 - -I 00:00:03.892268 executorch:text_token_generator.h:118] +I tokenizers:regex.cpp:27] Registering override fallback regex +I 00:00:00.003288 executorch:main.cpp:87] Resetting threadpool with num threads = 5 +I 00:00:00.006393 executorch:runner.cpp:44] Creating LLaMa runner: model_path=llama3_1B_kv_sdpa_xnn_qe_4_64_1024_embedding_4bit.pte, tokenizer_path=tokenizer.model +E tokenizers:hf_tokenizer.cpp:60] Error parsing json file: [json.exception.parse_error.101] parse error at line 1, column 1: syntax error while parsing value - invalid literal; last read: 'I' +I 00:00:00.131486 executorch:llm_runner_helper.cpp:57] Loaded TikToken tokenizer +I 00:00:00.131525 executorch:llm_runner_helper.cpp:167] Reading metadata from model +I 00:00:00.186538 executorch:llm_runner_helper.cpp:110] Metadata: use_sdpa_with_kv_cache = 1 +I 00:00:00.186574 executorch:llm_runner_helper.cpp:110] Metadata: use_kv_cache = 1 +I 00:00:00.186578 executorch:llm_runner_helper.cpp:110] Metadata: get_max_context_len = 1024 +I 00:00:00.186584 executorch:llm_runner_helper.cpp:110] Metadata: get_max_seq_len = 1024 +I 00:00:00.186588 executorch:llm_runner_helper.cpp:110] Metadata: enable_dynamic_shape = 1 +I 00:00:00.186596 executorch:llm_runner_helper.cpp:140] eos_id = 128009 +I 00:00:00.186597 executorch:llm_runner_helper.cpp:140] eos_id = 128001 +I 00:00:00.186599 executorch:llm_runner_helper.cpp:140] eos_id = 128006 +I 00:00:00.186600 executorch:llm_runner_helper.cpp:140] eos_id = 128007 +I 00:00:01.086570 executorch:text_llm_runner.cpp:89] Doing a warmup run... +I 00:00:01.087836 executorch:text_llm_runner.cpp:152] Max new tokens resolved: 128, given start_pos 0, num_prompt_tokens 54, max_context_len 1024 +I 00:00:01.292740 executorch:text_prefiller.cpp:93] Prefill token result numel(): 128256 + +I 00:00:02.264371 executorch:text_token_generator.h:123] Reached to the end of generation -I 00:00:03.892281 executorch:runner.cpp:267] Warmup run finished! -I 00:00:03.892286 executorch:runner.cpp:174] RSS after loading model: 1269.445312 MiB (0 if unsupported) -<|start_header_id|>system<|end_header_id|>\nYour name is Cookie. you are helpful, polite, precise, concise, honest, good at writing. You always give precise and brief answers up to 32 words<|eot_id|><|start_header_id|>user<|end_header_id|>\nHey Cookie! how are you today?<|eot_id|><|start_header_id|>assistant<|end_header_id|>I 00:00:04.076905 executorch:text_prefiller.cpp:53] Prefill token result numel(): 128256 - - -I 00:00:04.078027 executorch:runner.cpp:243] RSS after prompt prefill: 1269.445312 MiB (0 if unsupported) -I'm doing great, thanks! I'm always happy to help, communicate, and provide helpful responses. I'm a bit of a cookie (heh) when it comes to delivering concise and precise answers. What can I help you with today?<|eot_id|> -I 00:00:05.399304 executorch:text_token_generator.h:118] +I 00:00:02.264379 executorch:text_llm_runner.cpp:209] Warmup run finished! +I 00:00:02.264384 executorch:text_llm_runner.cpp:95] RSS after loading model: 1122.187500 MiB (0 if unsupported) +I 00:00:02.264624 executorch:text_llm_runner.cpp:152] Max new tokens resolved: 74, given start_pos 0, num_prompt_tokens 54, max_context_len 1024 +<|start_header_id|>system<|end_header_id|>\nYour name is Cookie. you are helpful, polite, precise, concise, honest, good at writing. You always give precise and brief answers up to 32 words<|eot_id|><|start_header_id|>user<|end_header_id|>\nHey Cookie! how are you today?<|eot_id|><|start_header_id|>assistant<|end_header_id|>I 00:00:02.394162 executorch:text_prefiller.cpp:93] Prefill token result numel(): 128256 + + +I 00:00:02.394373 executorch:text_llm_runner.cpp:179] RSS after prompt prefill: 1122.187500 MiB (0 if unsupported) +I'm doing great, thanks for asking! I'm always ready to help, whether it's answering a question or providing a solution. What can I help you with today?<|eot_id|> +I 00:00:03.072966 executorch:text_token_generator.h:123] Reached to the end of generation - -I 00:00:05.399314 executorch:runner.cpp:257] RSS after finishing text generation: 1269.445312 MiB (0 if unsupported) -PyTorchObserver {"prompt_tokens":54,"generated_tokens":51,"model_load_start_ms":1710296339487,"model_load_end_ms":1710296343047,"inference_start_ms":1710296343370,"inference_end_ms":1710296344877,"prompt_eval_end_ms":1710296343556,"first_token_ms":1710296343556,"aggregate_sampling_time_ms":49,"SCALING_FACTOR_UNITS_PER_SECOND":1000} -I 00:00:04.530945 executorch:stats.h:108] Prompt Tokens: 54 Generated Tokens: 69 -I 00:00:04.530947 executorch:stats.h:114] Model Load Time: 1.196000 (seconds) -I 00:00:04.530949 executorch:stats.h:124] Total inference time: 1.934000 (seconds) Rate: 35.677353 (tokens/second) -I 00:00:04.530952 executorch:stats.h:132] Prompt evaluation: 0.176000 (seconds) Rate: 306.818182 (tokens/second) -I 00:00:04.530954 executorch:stats.h:143] Generated 69 tokens: 1.758000 (seconds) Rate: 39.249147 (tokens/second) -I 00:00:04.530956 executorch:stats.h:151] Time to first generated token: 0.176000 (seconds) -I 00:00:04.530959 executorch:stats.h:158] Sampling time over 123 tokens: 0.067000 (seconds) + +I 00:00:03.072972 executorch:text_llm_runner.cpp:199] RSS after finishing text generation: 1122.187500 MiB (0 if unsupported) +PyTorchObserver {"prompt_tokens":54,"generated_tokens":36,"model_load_start_ms":1756473387815,"model_load_end_ms":1756473388715,"inference_start_ms":1756473389893,"inference_end_ms":1756473390702,"prompt_eval_end_ms":1756473390023,"first_token_ms":1756473390023,"aggregate_sampling_time_ms":22,"SCALING_FACTOR_UNITS_PER_SECOND":1000} +I 00:00:03.072993 executorch:stats.h:108] Prompt Tokens: 54 Generated Tokens: 36 +I 00:00:03.072995 executorch:stats.h:114] Model Load Time: 0.900000 (seconds) +I 00:00:03.072996 executorch:stats.h:124] Total inference time: 0.809000 (seconds) Rate: 44.499382 (tokens/second) +I 00:00:03.072998 executorch:stats.h:132] Prompt evaluation: 0.130000 (seconds) Rate: 415.384615 (tokens/second) +I 00:00:03.073000 executorch:stats.h:143] Generated 36 tokens: 0.679000 (seconds) Rate: 53.019146 (tokens/second) +I 00:00:03.073002 executorch:stats.h:151] Time to first generated token: 0.130000 (seconds) +I 00:00:03.073004 executorch:stats.h:158] Sampling time over 90 tokens: 0.022000 (seconds) ``` You have successfully run the Llama 3.1 1B Instruct model on your Android smartphone with ExecuTorch using KleidiAI kernels. diff --git a/content/learning-paths/mobile-graphics-and-gaming/build-llama3-chat-android-app-using-executorch-and-xnnpack/example-prompt-1.png b/content/learning-paths/mobile-graphics-and-gaming/build-llama3-chat-android-app-using-executorch-and-xnnpack/example-prompt-1.png index f12f3c8a8dd5a18a9de8af22f2e42b12cefa3554..46e00e0606a13ec18a12d8046beff97cf11b9544 100644 GIT binary patch literal 370958 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z3|%dkv2{EAn&}OeKlC^zero+eCfFme_v;c>E5{I}fmgv?g0!1o>r3u8+I~DEd_gqp zbByy%+nVCX&pvw2BRzy*1_zTlyv*s9C}(F5-99atMdFZnT}6 znQD847|T+g6Wm+<^JDej=Z0i8eneaG52I&o^DrreO8wgV6N+xuPDv9IjcN^#(o$Rn zUVIoFjh)R<@(@|cI&@pBc-T#GyT`@knzfexuChK z)qV}q9ACW7VUw~^Ac|R|j7Lu8y6tdsJ-Pc_O2^9y=Sa(wikJRTjx&lbW*o!_avj zwRVHBQnEbER=S_nyqpoLfmiy8T{^8L(#W@VO!sDmZHG$I{GjpGYV?5{*$q{plC$0K qe+&&NJ Date: Mon, 1 Sep 2025 15:13:34 +0200 Subject: [PATCH 03/31] Tech review of MongoDB for GCP --- .../github-on-arm/instance.md | 2 +- .../mongodb-on-gcp/_index.md | 19 +- .../mongodb-on-gcp/background.md | 4 +- .../mongodb-on-gcp/baseline-testing.md | 168 +++++++----------- .../mongodb-on-gcp/benchmarking.md | 83 ++++----- .../mongodb-on-gcp/create-instance.md | 26 +-- .../mongodb-on-gcp/mongodb-deploy.md | 111 +++++------- .../{image1.png => select-instance.png} | Bin 8 files changed, 176 insertions(+), 237 deletions(-) rename content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/{image1.png => select-instance.png} (100%) diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md index b775ebc4f6..632266e2d3 100644 --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md @@ -8,7 +8,7 @@ layout: learningpathall ## Introduction -This guide walks you through provisioning **Google Axion C4A Arm virtual machine** on GCP with the **c4a-standard-4 (4 vCPUs, 16 GB Memory)** machine type, using the **Google Cloud Console**. +This section walks you through creating **Google Axion C4A Arm virtual machine** on GCP with the **c4a-standard-4 (4 vCPUs, 16 GB Memory)** machine type, using the **Google Cloud Console**. If you haven't got a Google Cloud account, you can follow the Learning Path on [Getting Started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/) to get started. diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/_index.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/_index.md index 37e306524b..78c9482bfc 100644 --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/_index.md +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/_index.md @@ -1,25 +1,26 @@ --- title: Deploy MongoDB on Google Axion C4A virtual machine -minutes_to_complete: 60 +minutes_to_complete: 15 -who_is_this_for: This Learning Path is designed for software developers looking to migrate their MongoDB workloads from x86_64 to Arm-based platforms, specifically on Google Axion-based C4A virtual machines. +draft: true +cascade: + draft: true + +who_is_this_for: This is an introductory topic for software developers looking to migrate their MongoDB workloads from x86_64 to Arm-based platforms, specifically on Google Axion-based C4A virtual machines. learning_objectives: - - Provision an Arm virtual machine on the Google Cloud Platform using the C4A Google Axion instance family, and RHEL 9 as the base image. - - Install and run MongoDB on an Arm-based GCP C4A instances. - - Validate the functionality of MongoDB through baseline testing. + - Create an Arm cloud instance on the Google Cloud Platform + - Install and run MongoDB on the Arm-based GCP C4A instance. - Benchmark the MongoDB performance on Arm using Yahoo Cloud Serving Benchmark (YCSB). prerequisites: - A [Google Cloud Platform (GCP)](https://cloud.google.com/free?utm_source=google&hl=en) account with billing enabled. - - Basic understanding of Linux command line. - - Familiarity with the [MongoDB architecture](https://www.mongodb.com/) and deployment practices on Arm64 platforms. -author: Jason Andrews +author: Annie Tallund ##### Tags -skilllevels: Advanced +skilllevels: Introductory subjects: Databases cloud_service_providers: Google Cloud diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md index 99947c23e8..a576e38b4f 100644 --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md @@ -8,9 +8,9 @@ layout: "learningpathall" ## Google Axion C4A series -The Google Axion C4A series is a family of Arm-based virtual machines built on Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high-performance and energy-efficient computing, these virtual machine offer strong performance ideal for modern cloud workloads such as CI/CD pipelines, microservices, media processing, and general-purpose applications. +The C4A series is a family of Arm-based instance types for Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high-performance and energy-efficient computing, these virtual machine offer strong performance suitable for modern cloud workloads such as CI/CD pipelines, microservices, media processing, and general-purpose applications. -The C4A series provides a cost-effective alternative to x86 virtual machine while leveraging the scalability and performance benefits of the Arm architecture in Google Cloud. +The C4A series provides a cost-effective virtual machine while leveraging the scalability and performance benefits of the Arm architecture in Google Cloud. To learn more about Google Axion, refer to the blog [Introducing Google Axion Processors, our new Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu). diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md index 842709484f..02bb7c019b 100644 --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md @@ -6,35 +6,37 @@ weight: 5 layout: learningpathall --- +Now that MongoDB is successfully installed on your GCP C4A Arm virtual machine, follow these steps to verify that the server is running correctly and accepting local connections. -Since MongoDB is installed successfully on your GCP C4A Arm virtual machine, follow these steps to validate that the server is running and accepting local connections. - -## MongoDB Baseline Testing (Using **mongosh**) - -1. Connect to MongoDB +### 1. Connect to MongoDB Open a shell session to the local MongoDB instance: + ```console mongosh mongodb://127.0.0.1:27017 ``` -2. Create a Test Database and Collection: +### 2. Create a Test Database and Collection -```console +Switch to a new database and create a collection: + +```javascript use baselineDB db.createCollection("test") ``` -This creates a new database **baselineDB** and an empty collection named test. -You should see an output similar to: +This creates a new database named `baselineDB` and an empty collection called `test`. + +Expected output: ```output -test> use baselineDB -... db.createCollection("test") -... switched to db baselineDB +{ ok: 1 } ``` -3. Insert 10,000 Test Documents: + +### 3. Insert 10,000 Test Documents + +Populate the collection with 10,000 timestamped documents: ```javascript for (let i = 0; i < 10000; i++) { @@ -45,128 +47,91 @@ for (let i = 0; i < 10000; i++) { }) } ``` -This simulates basic write operations with timestamped records. -10,000 documents will be cretaed and inserted into the test collection of the currently selected database. -The record field would increment from 0 to 9999. The status is always "new". -The timestamp would capture the insertion time for each document using ***new Date()***. -You should see an output similar to: +Each document will contain: +- `record`: a counter from 0 to 9999 +- `status`: always `"new"` +- `timestamp`: the current date/time of insertion + +Sample output: ```output -{ - acknowledged: true, - insertedId: ObjectId('6892dacfbd44e23df4750aa9') -} +{ acknowledged: true, insertedId: ObjectId('...') } ``` -4. Read (Query) a Subset of Documents: +### 4. Read a Subset of Documents + +Verify read functionality by querying the first few documents: -Fetch a few documents to verify read functionality. ```javascript db.test.find({ status: "new" }).limit(5) ``` -This command is a simple read operation to verify that your data is inserted correctly. It queries the test collection in the current database, and only returns documents where the status is "new". ***limit(5)*** returns only the first 5 matching documents. -You should see an output similar to: +This returns the first 5 documents where `status` is `"new"`. + +### 5. Update a Document + +Update a specific document by changing its status: -```output -[ - { - _id: ObjectId('6892dacbbd44e23df474e39a'), - record: 0, - status: 'new', - timestamp: ISODate('2025-08-06T04:32:11.090Z') - }, - { - _id: ObjectId('6892dacbbd44e23df474e39b'), - record: 1, - status: 'new', - timestamp: ISODate('2025-08-06T04:32:11.101Z') - }, - { - _id: ObjectId('6892dacbbd44e23df474e39c'), - record: 2, - status: 'new', - timestamp: ISODate('2025-08-06T04:32:11.103Z') - }, - { - _id: ObjectId('6892dacbbd44e23df474e39d'), - record: 3, - status: 'new', - timestamp: ISODate('2025-08-06T04:32:11.104Z') - }, - { - _id: ObjectId('6892dacbbd44e23df474e39e'), - record: 4, - status: 'new', - timestamp: ISODate('2025-08-06T04:32:11.106Z') - } -] -``` -5. Update a Document: - -Update a specific document's field to validate update capability. ```javascript db.test.updateOne({ record: 100 }, { $set: { status: "processed" } }) ``` -Above command will find the first document where record is exactly 100, and updates that document by setting its status field to "processed". -You should see an output similar to: +This finds the document where `record` is 100 and updates the `status`. + +Expected output: ```output { acknowledged: true, - insertedId: null, matchedCount: 1, - modifiedCount: 1, - upsertedCount: 0 + modifiedCount: 1 } ``` -6. View the Updated Document Before Deletion -```console +### 6. View the Updated Document + +Confirm that the document was updated: + +```javascript db.test.findOne({ record: 100 }) ``` -This retrieves the document where record is 100, allowing you to verify that its status has been updated to "processed". -You should see output similar to: +Expected output: ```output { - _id: ObjectId('689490ddb7235c65ca74e3fe'), + _id: ObjectId('...'), record: 100, status: 'processed', - timestamp: ISODate('2025-08-07T11:41:17.508Z') + timestamp: ISODate('...') } ``` -7. Delete a Document: +### 7. Delete a Document + +Remove a single document: ```javascript db.test.deleteOne({ record: 100 }) ``` -This tells MongoDB to delete one document from the test collection, where record is exactly 100. -You should see an output similar to: - -```output -{ acknowledged: true, deletedCount: 1 } -``` -Now, confirm the deletion: +Verify that it was deleted: -```console +```javascript db.test.findOne({ record: 100 }) ``` -The above command confirms that the document was successfully deleted. -You should see an output similar to: +Expected output: + ```output null ``` -8. Measure Execution Time (Optional): +### 8. Measure Execution Time (Optional) + +Measure how long it takes to insert 10,000 documents: -The below snippet measures how long it takes to insert documents for performance insight. ```javascript var start = new Date() for (let i = 0; i < 10000; i++) { @@ -174,39 +139,42 @@ for (let i = 0; i < 10000; i++) { } print("Insert duration (ms):", new Date() - start) ``` -You should see an output similar to: + +Sample output: ```output Insert duration (ms): 4427 ``` -9. Count Total Documents: -Count total entries to confirm expected data volume. +### 9. Count Total Documents + +Check the total number of documents in the collection: + ```javascript db.test.countDocuments() ``` -You should see an output similar to: + +Expected output: ```output 19999 ``` + The count **19999** reflects the total documents after inserting 10,000 initial records, adding 10,000 more (in point 8), and deleting one (record: 100). -10. Clean Up (Optional): -Deletes the **baselineDB** database and all its contents. +### 10. Clean Up (Optional) + +For the sake of resetting the environment, this following command deletes the current database you are connected to in mongosh. Drop the `baselineDB` database to remove all test data: + ```javascript db.dropDatabase() ``` -You should see an output similar to: + +Expected output: ```output { ok: 1, dropped: 'baselineDB' } ``` -The above is a destructive command that completely deletes the current database you are connected to in mongosh. - -The above operations confirm that MongoDB is installed successfully and is functioning as expected on the GCP Arm64 environment. - -Using **mongosh**, you validated key database operations such as **insert**, **read**, **update**, **delete**, and **count**. -Now, your MongoDB instance is ready for further benchmarking and production use. +These baseline operations confirm that MongoDB is functioning properly on your GCP Arm64 environment. Using `mongosh`, you validated key database capabilities including **inserts**, **queries**, **updates**, **deletes**, and **performance metrics**. Your instance is now ready for benchmarking or application integration. \ No newline at end of file diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/benchmarking.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/benchmarking.md index 2ddf4990c6..fcbe8fd10e 100644 --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/benchmarking.md +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/benchmarking.md @@ -5,13 +5,14 @@ weight: 6 ### FIXED, DO NOT MODIFY layout: learningpathall --- - ## MongoDB Benchmarking with YCSB (Yahoo! Cloud Serving Benchmark) -**YCSB (Yahoo! Cloud Serving Benchmark)** is an open-source benchmarking tool for evaluating the performance of NoSQL databases under different workloads. It supports operations like read, write, update, and scan to simulate real-world usage patterns. +**YCSB (Yahoo! Cloud Serving Benchmark)** is an open-source tool for evaluating the performance of NoSQL databases under various workloads. It simulates operations such as reads, writes, updates, and scans to mimic real-world usage patterns. ### Install YCSB (Build from Source) +First, install the required build tools and clone the YCSB repository: + ```console sudo dnf install -y git maven java-11-openjdk-devel git clone https://github.com/brianfrankcooper/YCSB.git @@ -21,85 +22,61 @@ mvn -pl site.ycsb:mongodb-binding -am clean package ### Load Phase – Insert Initial Dataset -This phase inserts documents into MongoDB to simulate a typical workload. +This phase inserts a set of documents into MongoDB to simulate a typical starting workload. By default, it inserts 1,000 records. ```console ./bin/ycsb load mongodb -s \ -P workloads/workloada \ -p mongodb.url=mongodb://127.0.0.1:27017/ycsb ``` -The core purpose of this phase is to prepare the database with initial records (default: 1,000) for benchmarking. + +This prepares the database for the actual performance test. ### Execute Benchmark Workload -This phase performs actual read/write operations and reports performance metrics. +Run the actual benchmark with the predefined workload. This command performs mixed read/write operations and collects performance metrics. + ```console ./bin/ycsb run mongodb -s \ -P workloads/workloada \ -p mongodb.url=mongodb://127.0.0.1:27017/ycsb ``` -Workload A (from workloads/workloada) simulates a balanced read/write workload: +**Workload A** is a balanced workload: - 50% reads -- 50% updates/writes +- 50% updates -This is designed to mimic many real-world systems where reads and writes are equally important (e.g., session stores, shopping carts, etc.). -The above command measures latency and throughput of mixed read/write operations. +This simulates common real-world applications like session stores or shopping carts. - -You should see an output similar to: +You’ll see performance output that looks like this: ```output -Loading workload... -Starting test. -2025-08-06 06:05:50:378 0 sec: 0 operations; est completion in 0 second -mongo client connection created with mongodb://127.0.0.1:27017/ycsb -DBWrapper: report latency for each error is false and specific error codes to track for latency are: [] -2025-08-06 06:05:50:874 0 sec: 1000 operations; 1953.12 current ops/sec; [READ: Count=534, Max=8279, Min=156, Avg=312.96, 50=261, 90=436, 99=758, 99.9=8279, 99.99=8279] [CLEANUP: Count=1, Max=4139, Min=4136, Avg=4138, 50=4139, 90=4139, 99=4139, 99.9=4139, 99.99=4139] [UPDATE: Count=466, Max=26543, Min=186, Avg=384.45, 50=296, 90=444, 99=821, 99.9=26543, 99.99=26543] -[OVERALL], RunTime(ms), 512 -[OVERALL], Throughput(ops/sec), 1953.125 -[TOTAL_GCS_G1_Young_Generation], Count, 2 -[TOTAL_GC_TIME_G1_Young_Generation], Time(ms), 3 -[TOTAL_GC_TIME_%_G1_Young_Generation], Time(%), 0.5859375 -[TOTAL_GCS_G1_Old_Generation], Count, 0 -[TOTAL_GC_TIME_G1_Old_Generation], Time(ms), 0 -[TOTAL_GC_TIME_%_G1_Old_Generation], Time(%), 0.0 -[TOTAL_GCs], Count, 2 -[TOTAL_GC_TIME], Time(ms), 3 -[TOTAL_GC_TIME_%], Time(%), 0.5859375 [READ], Operations, 534 -[READ], AverageLatency(us), 312.96067415730334 +[READ], AverageLatency(us), 312.96 [READ], MinLatency(us), 156 [READ], MaxLatency(us), 8279 -[READ], 50thPercentileLatency(us), 261 -[READ], 95thPercentileLatency(us), 524 -[READ], 99thPercentileLatency(us), 758 -[READ], Return=OK, 534 -[CLEANUP], Operations, 1 -[CLEANUP], AverageLatency(us), 4138.0 -[CLEANUP], MinLatency(us), 4136 -[CLEANUP], MaxLatency(us), 4139 -[CLEANUP], 50thPercentileLatency(us), 4139 -[CLEANUP], 95thPercentileLatency(us), 4139 -[CLEANUP], 99thPercentileLatency(us), 4139 +... [UPDATE], Operations, 466 -[UPDATE], AverageLatency(us), 384.4527896995708 +[UPDATE], AverageLatency(us), 384.45 [UPDATE], MinLatency(us), 186 [UPDATE], MaxLatency(us), 26543 -[UPDATE], 50thPercentileLatency(us), 296 -[UPDATE], 95thPercentileLatency(us), 498 -[UPDATE], 99thPercentileLatency(us), 821 -[UPDATE], Return=OK, 466 +... +[OVERALL], RunTime(ms), 512 +[OVERALL], Throughput(ops/sec), 1953.125 ``` -### YCSB Operations & Latency Metrics +### YCSB Operations & Latency Metrics Explained + +- **Operations Count**: Total operations performed for each type (e.g., READ, UPDATE). +- **Average Latency (us)**: The average time to complete each operation, measured in microseconds. +- **Min Latency / Max Latency (us)**: The fastest and slowest observed times for any single operation of that type. -- **Operations Count**: Total number of operations performed by YCSB for each type. -- **Average Latency (us**): The average time (in microseconds) it took to complete each operation type. -- **Min Latency (us)**: The fastest (minimum) time observed for any single operation of that type. -- **Max Latency (us)**: The slowest (maximum) time recorded for any single operation of that type. +With YCSB installed and benchmark results captured, you now have a baseline for MongoDB's performance under mixed workloads. + +### Benchmark summary on x86_64 + +To better understand how MongoDB behaves across architectures, YCSB benchmark workloads were run on both an **x86_64 (C3 Standard)** and an **Arm64 (C4A Standard)** virtual machine, each with 4 vCPUs and 16 GB of memory, running RHEL 9. -### Benchmark summary on x86_64: The following benchmark results are collected on a c3-standard-4 (4 vCPU, 2 core, 16 GB Memory) x86_64 environment, running RHEL 9. | Operation | Count | Avg Latency (us) | Min Latency (us) | Max Latency (us) | 50th Percentile (us) | 95th Percentile (us) | 99th Percentile (us) | @@ -121,4 +98,6 @@ The following benchmark results are collected on a c4a-standard-4 (4 vCPU, 16 G - Arm results show low **average latencies**, **READ** at **313 us** and **UPDATE** at **384 us**. - **50th** to **99th percentile** latencies remain stable, indicating consistent performance. -- **Max latency** spikes (**8279 us READ**, **26543 us UPDAT**E) suggest rare outliers. +- **Max latency** spikes (**8279 us READ**, **26543 us UPDATE**) suggest rare outliers. + +This Learning Path walked you through setting up and benchmarking MongoDB on an Arm-based GCP instance, highlighting how to run core operations, validate performance, and interpret benchmarking results with YCSB. Alongside, you explored some performance numbers, showing that Arm is a powerful and cost-efficient alternative for modern data-serving workloads like MongoDB. \ No newline at end of file diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md index 3ca28709da..f54706f908 100644 --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md @@ -1,5 +1,5 @@ --- -title: Create Google Axion C4A Arm virtual machine +title: Create Google Axion instance weight: 3 ### FIXED, DO NOT MODIFY @@ -8,22 +8,26 @@ layout: learningpathall ## Introduction -This guide walks you through provisioning **Google Axion C4A Arm virtual machine** on GCP with the **c4a-standard-4 (4 vCPUs, 16 GB Memory)** machine type, using the **Google Cloud Console**. +This section walks you through creating a **Google Axion C4A Arm virtual machine** on GCP with the **c4a-standard-4 (4 vCPUs, 16 GB Memory)** machine type, using the **Google Cloud Console**. -If you are new to Google Cloud, it is recommended to follow the [GCP Quickstart Guide to Create a virtual machine](https://cloud.google.com/compute/docs/instances/create-start-instance). - -For more details, kindly follow the Learning Path on [Getting Started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/). +If you haven't set up a Google Cloud account, check out the Learning Path on [Getting Started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/). ### Create an Arm-based Virtual Machine (C4A) To create a virtual machine based on the C4A Arm architecture: 1. Navigate to the [Google Cloud Console](https://console.cloud.google.com/). -2. Go to **Compute Engine > VM Instances** and click on **Create Instance**. +2. Go to **Compute Engine** and click on **Create Instance**. 3. Under the **Machine Configuration**: - Fill in basic details like **Instance Name**, **Region**, and **Zone**. - - Choose the **Series** as `C4A`. - - Select a machine type such as `c4a-standard-4`. -![Instance Screenshot](./image1.png) -4. Under the **OS and Storage**, click on **Change**, and select Arm64 based OS Image of your choice. For this Learning Path, we pick **Red Hat Enterprise Linux** as the Operating System with **Red Hat Enterprise Linux 9** as the Version. Make sure you pick the version of image for Arm. -5. Under **Networking**, enable **Allow HTTP traffic** to allow HTTP communications. + - Select the **Series** as `C4A`. + - Choose a machine type such as `c4a-standard-4`. +![Instance Screenshot](./select-instance.png) +4. Under the **OS and Storage**, click on **Change**, and select **Red Hat Enterprise Linux** as the Operating System with **Red Hat Enterprise Linux 9** as the Version. Make sure you pick the version of image for Arm. +5. Under **Networking**, enable **Allow HTTP traffic** to allow interacting for later steps in the Learning Path. 6. Click on **Create**, and the instance will launch. + +{{% notice Important %}} +Avoid enabling Allow HTTP traffic permanently, as it introduces a security vulnerability. Instead, configure access to allow only your own IP address for long-term use. +{{% /notice %}} + +To access the Google Cloud Console, click the SSH button in your instance overview. This will open a command line interface (CLI), which you’ll use to run the remaining commands in this Learning Path. Continue to the next section to set up MongoDB on your instance. \ No newline at end of file diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md index 0725049259..6d41947389 100644 --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md @@ -1,119 +1,106 @@ --- -title: Install MongoDB on Google Axion C4A virtual machine +title: Install MongoDB weight: 4 ### FIXED, DO NOT MODIFY layout: learningpathall --- +In this section, you’ll install MongoDB and the MongoDB Shell (`mongosh`) by downloading the necessary binaries, configuring your environment, and verifying that the database server is running correctly. -## Install MongoDB and mongosh on Google Axion C4A virtual machine +### 1. Install System Dependencies -Install MongoDB and mongosh on GCP RHEL 9 Arm64 by downloading the binaries, setting up environment paths, configuring data and log directories, and starting the server for local access and verification. +Start by installing required system packages to support MongoDB: -1. Install System Dependencies - -Install required system packages to support MongoDB: ```console +sudo dnf update sudo dnf install -y libcurl openssl tar wget curl ``` -2. Download annd Extract MongoDB +### 2. Download and Extract MongoDB + +Next, fetch and unpack the MongoDB binaries for Arm: -Fetch and unpack the MongoDB binaries for Arm64: ```console wget https://fastdl.mongodb.org/linux/mongodb-linux-aarch64-rhel93-8.0.12.tgz tar -xzf mongodb-linux-aarch64-rhel93-8.0.12.tgz ls mongodb-linux-aarch64-rhel93-8.0.12/bin ``` -3. Add MongoDB to System PATH +To make MongoDB binaries accessible from any terminal session, add them to your PATH: -Enable running mongod from any terminal session: ```console echo 'export PATH=~/mongodb-linux-aarch64-rhel93-8.0.12/bin:$PATH' >> ~/.bashrc source ~/.bashrc ``` -4. Create a data Directory +### 3. Start the MongoDB server + + + +Set up a directory to store MongoDB's data files: -Set up the database data directory: ```console mkdir -p ~/mongodb-data/db ``` +Run MongoDB in the **foreground** to verify it starts correctly: + +```console +mongod --dbpath ~/mongodb-data/db +``` + +Starting the server in the **foreground** allows you to see real-time logs and is useful for debugging or verifying that MongoDB starts correctly. However, this will occupy your terminal and stop the server if you close the terminal or interrupt it. -5. Start MongoDB Server +After stopping the server (e.g., with `Ctrl+C`), confirm that files have been created in the database directory: -Start MongoDB in the **foreground** (without --fork) to view real-time output and ensure it starts correctly: ```console -~/mongodb-linux-aarch64-rhel93-8.0.12/bin/mongod --dbpath ~/mongodb-data/db +ls ~/mongodb-data/db/ ``` -Once confirmed it's working, you can start MongoDB in the **background** with logging: + +Example output: + +```output +collection-0-7680310461694759627.wt index-3-7680310461694759627.wt mongod.lock WiredTiger.lock +``` + +Once you’ve confirmed it’s working, you can start MongoDB in the **background** using the `--fork` option and redirecting logs to a file. This allows MongoDB to run continuously without tying up your terminal session. To start MongoDB in the **background** with logging enabled: + ```console -./mongodb-linux-aarch64-rhel93-8.0.12/bin/mongod --dbpath ~/mongodb-data/db --logpath ~/mongodb-data/mongod.log --fork +mongod --dbpath ~/mongodb-data/db --logpath ~/mongodb-data/mongod.log --fork ``` -{{% notice Note %}}Make sure the **~/mongodb-data/db** directory exists before starting.{{% /notice %}} -6. Install mongosh -**mongosh** is the MongoDB Shell used to interact with your MongoDB server. It provides a modern, user-friendly CLI for running queries and database operations. +### 4. Install mongosh + +`mongosh` is the MongoDB shell used to interact with your database. Download and install it for Arm: -Download and install MongoDB’s command-line shell for Arm: ```console wget https://github.com/mongodb-js/mongosh/releases/download/v2.5.6/mongodb-mongosh-2.5.6.aarch64.rpm sudo dnf install -y ./mongodb-mongosh-2.5.6.aarch64.rpm ``` -### Verify Mongodb and mongosh Installation -Check if MongoDb and mongosh is properly installed: +Confirm that`mongosh` was installed correctly by checking that the version is printed: + ```console -mongod --version mongosh --version ``` -You should see an output similar to: -```output -db version v8.0.12 -Build Info: { - "version": "8.0.12", - "gitVersion": "b60fc6875b5fb4b63cc0dbbd8dda0d6d6277921a", - "openSSLVersion": "OpenSSL 3.2.2 4 Jun 2024", - "modules": [], - "allocator": "tcmalloc-google", - "environment": { - "distmod": "rhel93", - "distarch": "aarch64", - "target_arch": "aarch64" - } -} -$ mongosh --version -2.5.6 -``` -### Connect to MongoDB via mongosh +### 5. Connect to MongoDB via mongosh + +Finally, connect to your MongoDB server using the shell: -Start interacting with MongoDB through its shell interface: ```console mongosh mongodb://127.0.0.1:27017 ``` -You should see an output similar to: -```output -Current Mongosh Log ID: 6891ebb158db5b705d74e399 -Connecting to: mongodb://127.0.0.1:27017/?directConnection=true&serverSelectionTimeoutMS=2000&appName=mongosh+2.5.6 -Using MongoDB: 8.0.12 -Using Mongosh: 2.5.6 - -For mongosh info see: https://www.mongodb.com/docs/mongodb-shell/ - ------- - The server generated these startup warnings when booting - 2025-08-05T07:17:45.864+00:00: Access control is not enabled for the database. Read and write access to data and configuration is unrestricted - 2025-08-05T07:17:45.864+00:00: Soft rlimits for open file descriptors too low - 2025-08-05T07:17:45.864+00:00: For customers running the current memory allocator, we suggest changing the contents of the following sysfsFile - 2025-08-05T07:17:45.864+00:00: We suggest setting the contents of sysfsFile to 0. - 2025-08-05T07:17:45.864+00:00: Your system has glibc support for rseq built in, which is not yet supported by tcmalloc-google and has critical performance implications. Please set the environment variable GLIBC_TUNABLES=glibc.pthread.rseq=0 ------- +Sample output: + +```output +Connecting to: mongodb://127.0.0.1:27017/?directConnection=true&... +Using MongoDB: 8.0.12 +Using Mongosh: 2.5.6 +... test> ``` -MongoDB installation is complete. You can now proceed with the baseline testing. +With MongoDB and `mongosh` successfully installed and running, you’re now ready to proceed with baseline testing. diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/image1.png b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/select-instance.png similarity index 100% rename from content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/image1.png rename to content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/select-instance.png From 4255ad8db4d2d9bcb000ad5733fa2ac7ac1da906 Mon Sep 17 00:00:00 2001 From: Annie Tallund Date: Mon, 1 Sep 2025 15:17:59 +0200 Subject: [PATCH 04/31] Update baseline-testing.md --- .../mongodb-on-gcp/baseline-testing.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md index 02bb7c019b..6d558c9688 100644 --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md @@ -110,7 +110,7 @@ Expected output: ### 7. Delete a Document -Remove a single document: +The command below tells MongoDB to delete one document from the test collection, where record is exactly 100: ```javascript db.test.deleteOne({ record: 100 }) From 21e19ab0f554f09860d87ec78f02e3f2b98e17a5 Mon Sep 17 00:00:00 2001 From: Annie Tallund Date: Wed, 3 Sep 2025 17:00:24 +0200 Subject: [PATCH 05/31] Fix skillevels across content --- .../training-inference-pytorch/_index.md | 20 +++++++++---------- .../uvprojx-conversion/_index.md | 6 +++--- .../self_hosted_cicd_github/_index.md | 2 +- .../mobile-graphics-and-gaming/afrc/_index.md | 4 ++-- .../profiling-unity-apps-on-android/_index.md | 4 ++-- .../ray_tracing/_index.md | 4 ++-- .../_index.md | 4 ++-- 7 files changed, 22 insertions(+), 22 deletions(-) diff --git a/content/learning-paths/embedded-and-microcontrollers/training-inference-pytorch/_index.md b/content/learning-paths/embedded-and-microcontrollers/training-inference-pytorch/_index.md index 1dea9ea1e0..967482a761 100644 --- a/content/learning-paths/embedded-and-microcontrollers/training-inference-pytorch/_index.md +++ b/content/learning-paths/embedded-and-microcontrollers/training-inference-pytorch/_index.md @@ -7,41 +7,41 @@ cascade: minutes_to_complete: 90 -who_is_this_for: This topic is for machine learning engineers, embedded AI developers, and researchers interested in deploying TinyML models for NLP on Arm-based edge devices using PyTorch and ExecuTorch. +who_is_this_for: This topic is for machine learning engineers, embedded AI developers, and researchers interested in deploying TinyML models for NLP on Arm-based edge devices using PyTorch and ExecuTorch. -learning_objectives: +learning_objectives: - Train a custom CNN-based sentiment classification model implemented in PyTorch. - Optimize and convert the model using ExecuTorch for Arm-based edge devices. - Deploy and run inference on the Corstone-320 FVP. prerequisites: - - Basic knowledge of machine learning concepts. - - It is advised to complete The Learning Path, [Introduction to TinyML on Arm using PyTorch and ExecuTorch](/learning-paths/embedded-and-microcontrollers/introduction-to-tinyml-on-arm) before starting this learning path. + - Basic knowledge of machine learning concepts. + - It is advised to complete The Learning Path, [Introduction to TinyML on Arm using PyTorch and ExecuTorch](/learning-paths/embedded-and-microcontrollers/introduction-to-tinyml-on-arm) before starting this learning path. - Familiarity with Python and PyTorch. - A Linux host machine or VM running Ubuntu 22.04 or higher. - - An Arm license to run the examples on the Corstone-320 Fixed Virtual Platform (FVP), for hands-on deployment. + - An Arm license to run the examples on the Corstone-320 Fixed Virtual Platform (FVP), for hands-on deployment. author: Dominica Abena O. Amanfo ### Tags -skilllevels: Intermediate +skilllevels: Introductory subjects: ML armips: - Cortex-A tools_software_languages: - - tinyML - - CNN + - tinyML + - CNN - PyTorch - ExecuTorch - + operatingsystems: - Linux further_reading: - resource: - title: Run Llama 3 on a Raspberry Pi 5 using ExecuTorch + title: Run Llama 3 on a Raspberry Pi 5 using ExecuTorch link: /learning-paths/embedded-and-microcontrollers/rpi-llama3 type: website - resource: diff --git a/content/learning-paths/embedded-and-microcontrollers/uvprojx-conversion/_index.md b/content/learning-paths/embedded-and-microcontrollers/uvprojx-conversion/_index.md index 7ec6b4f9be..71f1f19ec4 100644 --- a/content/learning-paths/embedded-and-microcontrollers/uvprojx-conversion/_index.md +++ b/content/learning-paths/embedded-and-microcontrollers/uvprojx-conversion/_index.md @@ -5,7 +5,7 @@ minutes_to_complete: 10 who_is_this_for: This is a topic for users of µVision who want to migrate to the new project format (csolution) required by CMSIS-Toolbox. -learning_objectives: +learning_objectives: - Import, convert, and build uvprojx-based projects in Keil Studio. - Convert uvprojx-based projects in µVision. - Convert and build uvprojx-based projects on the command line. @@ -19,7 +19,7 @@ prerequisites: author: Christopher Seidl ### Tags -skilllevels: Intermediate +skilllevels: Advanced subjects: Performance and Architecture armips: - Cortex-M @@ -43,7 +43,7 @@ further_reading: link: https://community.arm.com/arm-community-blogs/b/internet-of-things-blog/posts/keil-mdk-version-6 type: blog - resource: - title: keil.arm.com + title: keil.arm.com link: https://keil.arm.com type: website diff --git a/content/learning-paths/laptops-and-desktops/self_hosted_cicd_github/_index.md b/content/learning-paths/laptops-and-desktops/self_hosted_cicd_github/_index.md index 25bf578c96..e2763e261d 100644 --- a/content/learning-paths/laptops-and-desktops/self_hosted_cicd_github/_index.md +++ b/content/learning-paths/laptops-and-desktops/self_hosted_cicd_github/_index.md @@ -18,7 +18,7 @@ prerequisites: author: Dawid Borycki ### Tags -skilllevels: Intermediate +skilllevels: Introductory subjects: Migration to Arm armips: - Cortex-A diff --git a/content/learning-paths/mobile-graphics-and-gaming/afrc/_index.md b/content/learning-paths/mobile-graphics-and-gaming/afrc/_index.md index eaa130e36a..b76fa5e727 100644 --- a/content/learning-paths/mobile-graphics-and-gaming/afrc/_index.md +++ b/content/learning-paths/mobile-graphics-and-gaming/afrc/_index.md @@ -5,7 +5,7 @@ minutes_to_complete: 25 who_is_this_for: Software developers of Android applications and mobile games who are interested in learning how to enable Arm Fixed Rate Compression (AFRC) to improve performance. -learning_objectives: +learning_objectives: - Query for fixed-rate compression support. - Specify what compression to use. - Verify that compression is applied. @@ -18,7 +18,7 @@ prerequisites: author: Jose-Emilio Munoz-Lopez ### Tags -skilllevels: Intermediate +skilllevels: Advanced subjects: Graphics armips: - Mali diff --git a/content/learning-paths/mobile-graphics-and-gaming/profiling-unity-apps-on-android/_index.md b/content/learning-paths/mobile-graphics-and-gaming/profiling-unity-apps-on-android/_index.md index 3e9882cabd..03c7d7b29f 100644 --- a/content/learning-paths/mobile-graphics-and-gaming/profiling-unity-apps-on-android/_index.md +++ b/content/learning-paths/mobile-graphics-and-gaming/profiling-unity-apps-on-android/_index.md @@ -5,7 +5,7 @@ minutes_to_complete: 40 who_is_this_for: Unity developers wanting to analyze the performance of their apps on Android devices -learning_objectives: +learning_objectives: - Deploy to Android - Profile code running on an Android device - Analyze performance data @@ -19,7 +19,7 @@ prerequisites: author: Arm ### Tags -skilllevels: Intermediate +skilllevels: Introductory subjects: Performance and Architecture armips: - armv8 diff --git a/content/learning-paths/mobile-graphics-and-gaming/ray_tracing/_index.md b/content/learning-paths/mobile-graphics-and-gaming/ray_tracing/_index.md index a7266875c7..d6ccb5c6ef 100644 --- a/content/learning-paths/mobile-graphics-and-gaming/ray_tracing/_index.md +++ b/content/learning-paths/mobile-graphics-and-gaming/ray_tracing/_index.md @@ -5,7 +5,7 @@ minutes_to_complete: 120 who_is_this_for: This Learning Path is for Vulkan developers who are familiar with rendering and are interested in deploying ray tracing in their applications. -learning_objectives: +learning_objectives: - Describe how the Vulkan ray tracing API works. - Describe how to use ray tracing to implement realistic shadows, reflections, and refractions. - Implement basic ray tracing effects in a Vulkan renderer. @@ -18,7 +18,7 @@ prerequisites: author: Iago Calvo Lista ### Tags -skilllevels: Intermediate +skilllevels: Advanced subjects: Graphics armips: - Mali diff --git a/content/learning-paths/mobile-graphics-and-gaming/using-neon-intrinsics-to-optimize-unity-on-android/_index.md b/content/learning-paths/mobile-graphics-and-gaming/using-neon-intrinsics-to-optimize-unity-on-android/_index.md index 684bcefadc..c445131929 100644 --- a/content/learning-paths/mobile-graphics-and-gaming/using-neon-intrinsics-to-optimize-unity-on-android/_index.md +++ b/content/learning-paths/mobile-graphics-and-gaming/using-neon-intrinsics-to-optimize-unity-on-android/_index.md @@ -5,7 +5,7 @@ minutes_to_complete: 90 who_is_this_for: Developers who want to optimize their Unity apps on Android -learning_objectives: +learning_objectives: - Use Arm Neon intrinsics in your Unity C# scripts - Optimize your code - Collect and compare performance data using the Unity Profiler and Analyzer tools @@ -19,7 +19,7 @@ prerequisites: author: Arm ### Tags -skilllevels: Intermediate +skilllevels: Advanced subjects: Gaming armips: - armv8 From c73ed9caeafe08ca1e45f230a904485ead986fb3 Mon Sep 17 00:00:00 2001 From: Arnaud de Grandmaison Date: Thu, 4 Sep 2025 09:49:03 +0200 Subject: [PATCH 06/31] Add a line numbering start attribute. When line numbering is enabled, this enables to start the line numbering from a specific value. This feature is useful when refering to large files for which a learning path would comment some excerpts. We want the line numbering to match the one from the file. --- .../appendix-1-formatting.md | 24 +++++++++++++++---- .../_default/_markup/render-codeblock.html | 4 ++-- .../general-formatting/prismjs-codeblock.html | 23 +++++++++++++----- .../layouts/shortcodes/tab.html | 1 + .../layouts/shortcodes/tabpane.html | 1 + 5 files changed, 40 insertions(+), 13 deletions(-) diff --git a/content/learning-paths/cross-platform/_example-learning-path/appendix-1-formatting.md b/content/learning-paths/cross-platform/_example-learning-path/appendix-1-formatting.md index 589c59fbe6..8a310fc356 100644 --- a/content/learning-paths/cross-platform/_example-learning-path/appendix-1-formatting.md +++ b/content/learning-paths/cross-platform/_example-learning-path/appendix-1-formatting.md @@ -83,12 +83,26 @@ Specify that line_numbers are true in the following way: \`\`\`bash { line_numbers = "true" } \ echo 'hello world' \ echo ‘I am line two’ \ -\`\`\` +\`\`\` + +```bash { line_numbers = "true" } +echo ‘hello world’ +echo ‘I am line two’ +``` + +In some cases, the line numbering should not start from one but from another +value, e.g. if the code excerpt is extracted from a larger file. Use the +`line_start` attribute to achieve this: -```bash { line_numbers = "true" } -echo ‘hello world’ -echo ‘I am line two’ -``` +\`\`\`bash { line_numbers = "true" line_start = "10" } \ +echo 'hello world' \ +echo ‘I am line two’ \ +\`\`\` + +```bash { line_numbers = "true" line_start = "10" } +echo ‘hello world’ +echo ‘I am line eleven’ +``` ### Output Lines diff --git a/themes/arm-design-system-hugo-theme/layouts/_default/_markup/render-codeblock.html b/themes/arm-design-system-hugo-theme/layouts/_default/_markup/render-codeblock.html index 7fbc711f19..196a6fcdfe 100644 --- a/themes/arm-design-system-hugo-theme/layouts/_default/_markup/render-codeblock.html +++ b/themes/arm-design-system-hugo-theme/layouts/_default/_markup/render-codeblock.html @@ -6,5 +6,5 @@ ``` */}} {{partial "general-formatting/prismjs-codeblock.html" (dict "input_from" "normal" "code" .Inner "language" .Type -"line_numbers" .Attributes.line_numbers "output_lines" .Attributes.output_lines "command_line" .Attributes.command_line) -}} \ No newline at end of file +"line_numbers" .Attributes.line_numbers "output_lines" .Attributes.output_lines "command_line" .Attributes.command_line "line_start" .Attributes.line_start) +}} diff --git a/themes/arm-design-system-hugo-theme/layouts/partials/general-formatting/prismjs-codeblock.html b/themes/arm-design-system-hugo-theme/layouts/partials/general-formatting/prismjs-codeblock.html index 407a4a6f66..565846f283 100644 --- a/themes/arm-design-system-hugo-theme/layouts/partials/general-formatting/prismjs-codeblock.html +++ b/themes/arm-design-system-hugo-theme/layouts/partials/general-formatting/prismjs-codeblock.html @@ -14,6 +14,7 @@ code Str: echo('Hello world').... language Str: python line_numbers Bool: true or false + line_start Str: 123 output_lines Str: 5 or 1-4, 9 command_line Str: "root@localhost" */}} @@ -42,14 +43,24 @@ {{$output_present = true}} {{end}} -

          /sys/devices/system/cpu/cpu${no}/online"; done
    -```
    -2. Use the following commands to verify that cores 0-7 are online and the remaining cores are offline.
    -```bash
    -lscpu
    -```
    -The output should look like:
    -```output
    -Architecture:                aarch64
    -  CPU op-mode(s):            64-bit
    -  Byte Order:                Little Endian
    -CPU(s):                      192
    -  On-line CPU(s) list:       0-7
    -  Off-line CPU(s) list:      8-191
    -Vendor ID:                   ARM
    -  Model name:                Neoverse-V2
    -...
    -```
    -
    -3. Now shutdown and restart `Tomcat` on your Arm Neoverse bare-metal instance as shown:
    -```bash
    -~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
    -ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
    -```
    -
    -4. On your `x86_64` bare-metal instance, run `wrk2` as shown:
    -
    -```bash
    -ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://${tomcat_ip}:8080/examples/servlets/servlet/HelloWorldExample
    -```
    -Replace `{tomcat_ip}` in the command above with the IP address of your Arm-based instance where the Tomcat server is running.
    +1. Set CPUs 8–191 offline:
     
    -The result with this baseline configuration should look like:
    -```output
    -  Thread Stats   Avg      Stdev     Max   +/- Stdev
    -    Latency    16.76s     6.59s   27.56s    56.98%
    -    Req/Sec     1.97k   165.05     2.33k    89.90%
    -  14680146 requests in 1.00m, 7.62GB read
    -  Socket errors: connect 1264, read 0, write 0, timeout 1748
    -Requests/sec: 244449.62
    -Transfer/sec:    129.90MB
    -```
    -
    -### Disable Access logging
    -To disable access logging, use a text editor to modify the `server.xml` file by commenting out or removing the **`org.apache.catalina.valves.AccessLogValve`** configuration.
    -
    -The file is at:
    -```bash
    -vi ~/apache-tomcat-11.0.10/conf/server.xml
    -```
    -
    -Either comment out or delete the configuration shown at the end of the file:
    -```xml
    -
    -```
    -
    -1. Shutdown and restart `Tomcat` on your Arm Neoverse bare-metal instance as shown:
    -```bash
    -~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
    -ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
    -```
    -
    -2. Run `wrk2` on the `x86_64` bare-metal instance:
    -```bash
    -ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://${tomcat_ip}:8080/examples/servlets/servlet/HelloWorldExample
    -```
    -
    -The result with access logging disabled should look like:
    -```bash
    -  Thread Stats   Avg      Stdev     Max   +/- Stdev
    -    Latency    16.16s     6.45s   28.26s    57.85%
    -    Req/Sec     2.16k     5.91     2.17k    77.50%
    -  16291136 requests in 1.00m, 8.45GB read
    -  Socket errors: connect 0, read 0, write 0, timeout 75
    -Requests/sec: 271675.12
    -Transfer/sec:    144.36MB
    -```
    -
    -### Set up optimal thread counts
    -To minimize resource contention between threads and overhead from thread context switching, the number of CPU-intensive threads in Tomcat should be aligned with the number of CPU cores.
    -
    -1. When using `wrk` to perform pressure testing on `Tomcat`, use `top` to identify the CPU-intensive threads :
    -```bash
    -top -H -p$(pgrep java)
    -```
    -
    -The output from `top` will look like:
    -```bash
    -top - 08:57:29 up 20 min,  1 user,  load average: 4.17, 2.35, 1.22
    -Threads: 231 total,   8 running, 223 sleeping,   0 stopped,   0 zombie
    -%Cpu(s): 31.7 us, 20.2 sy,  0.0 ni, 31.0 id,  0.0 wa,  0.0 hi, 17.2 si,  0.0 st
    -MiB Mem : 386127.8 total, 380676.0 free,   4040.7 used,   2801.1 buff/cache
    -MiB Swap:      0.0 total,      0.0 free,      0.0 used. 382087.0 avail Mem
    +    ```bash
    +    for no in {8..191}; do sudo bash -c "echo 0 > /sys/devices/system/cpu/cpu${no}/online"; done
    +    ```
    +
    +2. Confirm that CPUs `0–7` are online and the rest are offline:
    +
    +    ```bash
    +    lscpu
    +    ```
    +
    +    Example output:
    +    ```output
    +    Architecture:                aarch64
    +      CPU op-mode(s):            64-bit
    +      Byte Order:                Little Endian
    +    CPU(s):                      192
    +      On-line CPU(s) list:       0-7
    +      Off-line CPU(s) list:      8-191
    +    Vendor ID:                   ARM
    +      Model name:                Neoverse-V2
    +    ...
    +    ```
    +
    +3. Restart Tomcat on the Arm instance:
    +
    +    ```bash
    +    ~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
    +    ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
    +    ```
    +
    +4. From your `x86_64` benchmarking client, run `wrk2` (replace `` with the server’s IP):
    +
    +    ```bash
    +    ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://:8080/examples/servlets/servlet/HelloWorldExample
    +    ```
    +
    +    Example result:
    +    ```output
    +      Thread Stats   Avg      Stdev     Max   +/- Stdev
    +        Latency    16.76s     6.59s   27.56s    56.98%
    +        Req/Sec     1.97k   165.05     2.33k    89.90%
    +      14680146 requests in 1.00m, 7.62GB read
    +      Socket errors: connect 1264, read 0, write 0, timeout 1748
    +    Requests/sec: 244449.62
    +    Transfer/sec:    129.90MB
    +    ```
    +
    +### Disable access logging
    +
    +Disabling access logs removes I/O overhead during benchmarking.
    +
    +1. Edit `server.xml` and comment out (or remove) the **`org.apache.catalina.valves.AccessLogValve`** block:
    +
    +    ```bash
    +    vi ~/apache-tomcat-11.0.10/conf/server.xml
    +    ```
    +
    +    ```xml
    +    
    +    ```
    +
    +2. Restart Tomcat:
    +
    +    ```bash
    +    ~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
    +    ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
    +    ```
    +
    +3. Re-run `wrk2`:
    +
    +    ```bash
    +    ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://:8080/examples/servlets/servlet/HelloWorldExample
    +    ```
    +
    +    Example result:
    +    ```output
    +      Thread Stats   Avg      Stdev     Max   +/- Stdev
    +        Latency    16.16s     6.45s   28.26s    57.85%
    +        Req/Sec     2.16k     5.91     2.17k    77.50%
    +      16291136 requests in 1.00m, 8.45GB read
    +      Socket errors: connect 0, read 0, write 0, timeout 75
    +    Requests/sec: 271675.12
    +    Transfer/sec:    144.36MB
    +    ```
    +
    +### Set optimal thread counts
    +
    +To minimize contention and context switching, align Tomcat’s CPU‑intensive thread count with available CPU cores.
    +
    +1. While `wrk2` is running, identify CPU‑intensive Tomcat threads:
    +
    +    ```bash
    +    top -H -p "$(pgrep -n java)"
    +    ```
    +
    +    Example output:
    +    ```output
    +    top - 08:57:29 up 20 min,  1 user,  load average: 4.17, 2.35, 1.22
    +    Threads: 231 total,   8 running, 223 sleeping,   0 stopped,   0 zombie
    +    %Cpu(s): 31.7 us, 20.2 sy,  0.0 ni, 31.0 id,  0.0 wa,  0.0 hi, 17.2 si,  0.0 st
    +    MiB Mem : 386127.8 total, 380676.0 free,   4040.7 used,   2801.1 buff/cache
    +    MiB Swap:      0.0 total,      0.0 free,      0.0 used. 382087.0 avail Mem
     
         PID USER      PR  NI    VIRT    RES    SHR S  %CPU  %MEM     TIME+ COMMAND
        4677 ubuntu    20   0   36.0g   1.4g  24452 R  89.0   0.4   1:18.71 http-nio-8080-P
    @@ -186,59 +204,52 @@ MiB Swap:      0.0 total,      0.0 free,      0.0 used. 382087.0 avail Mem
     ...
     ```
     
    -You can observe from the output that **`http-nio-8080-e`** and **`http-nio-8080-P`** threads are CPU-intensive.
    -As the __`http-nio-8080-P`__ thread is fixed at 1 in current version of Tomcat, and the current number of CPU cores is 8, the `http-nio-8080-e` thread count should be configured to 7.
    -
    -To configure the `http-nio-8080-e` thread count, use a text editor to modify the `server.xml` file and update the `
    -    
    -```
    -
    -With the updated setting:
    -
    -```xml
    -
    -    
    -```
    -
    -Save the changes to `server.xml`.
    -
    -2. Now shutdown and restart `Tomcat` on your Arm Neoverse bare-metal instance as shown:
    -```bash
    -~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
    -ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
    -```
    -
    -3. Run `wrk2` on the`x86_64` bare-metal instance:
    -```bash
    -ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://${tomcat_ip}:8080/examples/servlets/servlet/HelloWorldExample
    -```
    -
    -The result with the optimal thread count settings should look like:
    -```output
    -  Thread Stats   Avg      Stdev     Max   +/- Stdev
    -    Latency    10.26s     4.55s   19.81s    62.51%
    -    Req/Sec     2.86k    89.49     3.51k    77.06%
    -  21458421 requests in 1.00m, 11.13GB read
    -Requests/sec: 357835.75
    -Transfer/sec:    190.08MB
    -```
    -
    -Now that you have established some baseline settings you can proceed to further tuning your setup.
    +    You’ll typically see **`http-nio-8080-e`** and **`http-nio-8080-P`** threads as CPU intensive. Because the **`http-nio-8080-P`** thread count is fixed at 1 (in current Tomcat releases), and you have 8 online CPU cores, set **`http-nio-8080-e`** to **7**.
    +
    +2. Edit `server.xml` and update the HTTP connector to set the worker thread counts and connection limits:
    +
    +    ```bash
    +    vi ~/apache-tomcat-11.0.10/conf/server.xml
    +    ```
    +
    +    Replace the existing connector:
    +    ```xml
    +    
    +        
    +    ```
    +
    +    With the tuned settings:
    +    ```xml
    +    
    +        
    +    ```
    +
    +3. Restart Tomcat and re-run `wrk2`:
    +
    +    ```bash
    +    ~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
    +    ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
    +
    +    ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://:8080/examples/servlets/servlet/HelloWorldExample
    +    ```
    +
    +    Example result:
    +    ```output
    +      Thread Stats   Avg      Stdev     Max   +/- Stdev
    +        Latency    10.26s     4.55s   19.81s    62.51%
    +        Req/Sec     2.86k    89.49     3.51k    77.06%
    +      21458421 requests in 1.00m, 11.13GB read
    +    Requests/sec: 357835.75
    +    Transfer/sec:    190.08MB
    +    ```
    +
    +With a solid baseline in place, you’re ready to proceed to NIC queue tuning, NUMA locality optimization, and IOMMU exploration in the next sections.
    
    From c83029dbea43d26d3fd644bc4dbdbdd1af2dd667 Mon Sep 17 00:00:00 2001
    From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
    Date: Thu, 4 Sep 2025 13:27:11 +0000
    Subject: [PATCH 09/31] Content dev
    
    ---
     .../3_nic-queue.md                            | 107 ++++++++++--------
     .../4_local-numa.md                           |  42 ++++---
     2 files changed, 83 insertions(+), 66 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/3_nic-queue.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/3_nic-queue.md
    index 4aa434ddbd..f49bad7421 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/3_nic-queue.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/3_nic-queue.md
    @@ -1,23 +1,22 @@
     ---
    -title: Tuning via NIC queue count
    +title: Tune performance with NIC queue counts
     weight: 4
     
     ### FIXED, DO NOT MODIFY
     layout: learningpathall
     ---
     
    -## Tuning via NIC queue count
    -To further optmize your settings, you can set the NIC queue count and observe the performance uplift:
    +## Overview
     
    -Typically, the number of transmit/receive queues for network cards in bare-metal environments is relatively large, reaching 63 on Arm Neoverse. Each transmit/receive queue corresponds to one interrupt number. Before CPU cores are taken offline, there are sufficient cores to handle these interrupt numbers. However, when only 8 cores are retained, it results in a single core having to handle multiple interrupt numbers, thereby triggering more context switches.
    +After establishing a baseline, you can further improve throughput and latency by tuning your network interface controller (NIC) queue count. Many bare‑metal NICs expose a relatively large number of transmit/receive queues (multi‑queue). Each queue maps to an interrupt; when you limit the server to a small number of online CPUs (for example, 8 cores), too many interrupts can land on the same core and increase context switching. Reducing the number of queues to match available CPUs can stabilize performance on Arm Neoverse systems.
     
    -### Setting NIC queue count
    +## Set the NIC queue count
     
    -1. Use the following command to find the NIC name corresponding to he IP address.
    +Use the following command to find the NIC name corresponding to the IP address:
     ```bash
     ip addr
     ```
    -From the output you can see that the NIC name `enp1s0f0np0` corresponds to the IP address `10.169.226.181`.
    +From the output you can see that the NIC name `enp1s0f0np0` corresponds to the IP address `10.169.226.181`:
     ```output
     1: lo:  mtu 65536 qdisc noqueue state UNKNOWN group default qlen 1000
         link/loopback 00:00:00:00:00:00 brd 00:00:00:00:00:00
    @@ -33,12 +32,12 @@ From the output you can see that the NIC name `enp1s0f0np0` corresponds to the I
            valid_lft forever preferred_lft forever
     ```
     
    -2. Set the network interface name variable
    +Set the network interface name variable:
     ```bash
     net=enp1s0f0np0
     ```
     
    -3. Use the following command to check the current transmit/receive queues of the ${net} network interface
    +Use the following command to check the current transmit/receive queues of the ${net} network interface:
     ```bash
     sudo ethtool -l ${net}
     ```
    @@ -57,48 +56,56 @@ Other:		n/a
     Combined:	32
     ```
     
    -4. Use the following command to reset the number of transmit/receive queues for the ${net} to match the number of CPUs, which is 8.
    -```bash
    -sudo ethtool -L ${net} combined 8
    -```
    -5. Verify whether the settings have been successfully applied.
    -```bash
    -sudo ethtool -l ${net}
    -```
    -You should see that the number of combined Rx/Tx queues has been updated to 8.
    -```output
    -Channel parameters for enP11p4s0:
    -Pre-set maximums:
    -RX:		n/a
    -TX:		n/a
    -Other:		n/a
    -Combined:	32
    -Current hardware settings:
    -RX:		n/a
    -TX:		n/a
    -Other:		n/a
    -Combined:	8
    -```
    +Set the number of combined queues to match your online CPUs (example: 8):
    +   ```bash
    +   sudo ethtool -L ${NET_IFACE} combined 8
    +   ```
     
    -### The performance uplift after tuning NIC queue count
    +Verify the change:
    +   ```bash
    +   sudo ethtool -l ${NET_IFACE}
    +   ```
     
    -1. Shutdown and restart `Tomcat` on your Arm Neoverse bare-metal instance as shown:
    -```bash
    -~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
    -ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
    -```
    +   You should see the `Combined` value updated to `8` under **Current hardware settings**:
    +   ```output
    +   Channel parameters for enP11p4s0:
    +   Pre-set maximums:
    +   RX:             n/a
    +   TX:             n/a
    +   Other:          n/a
    +   Combined:       32
    +   Current hardware settings:
    +   RX:             n/a
    +   TX:             n/a
    +   Other:          n/a
    +   Combined:       8
    +   ```
     
    -2. Run `wrk2` on your `x86_64` bare-metal instance:
    -```bash
    -ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://${tomcat_ip}:8080/examples/servlets/servlet/HelloWorldExample
    -```
    +{{% notice Note %}}
    +Queue settings applied with `ethtool -L` are not persistent across reboots. If needed, make the change persistent using a systemd unit or your distro’s NIC configuration mechanism.
    +{{% /notice %}}
     
    -Notice the performance uplift after tuning the NIC queue count:
    -```output
    -  Thread Stats   Avg      Stdev     Max   +/- Stdev
    -    Latency     8.35s     4.14s   16.33s    61.16%
    -    Req/Sec     2.96k    73.02     3.24k    89.16%
    -  22712999 requests in 1.00m, 11.78GB read
    -Requests/sec: 378782.37
    -Transfer/sec:    201.21MB
    -```
    +## Measure performance after tuning
    +
    +Restart Tomcat on your Arm Neoverse bare‑metal instance:
    +   ```bash
    +   ~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
    +   ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
    +   ```
    +
    +Run `wrk2` from your `x86_64` bare‑metal client (replace `${tomcat_ip}` with your server IP):
    +   ```bash
    +   ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://${tomcat_ip}:8080/examples/servlets/servlet/HelloWorldExample
    +   ```
    +
    +   Example results after tuning NIC queues:
    +   ```output
    +     Thread Stats   Avg      Stdev     Max   +/- Stdev
    +       Latency     8.35s     4.14s   16.33s    61.16%
    +       Req/Sec     2.96k    73.02     3.24k    89.16%
    +     22712999 requests in 1.00m, 11.78GB read
    +   Requests/sec: 378782.37
    +   Transfer/sec:    201.21MB
    +   ```
    +
    +If performance improves and latency stabilizes, keep the adjusted queue count for subsequent tuning steps (RSS/RPS/XPS, IRQ affinity, and NUMA locality).
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/4_local-numa.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/4_local-numa.md
    index de7a370226..68f1a04a28 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/4_local-numa.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/4_local-numa.md
    @@ -6,19 +6,20 @@ weight: 5
     layout: learningpathall
     ---
     
    -## Tuning via local (Non-Uniform Memory Access) NUMA
    -In this section you will learn how to configure local NUMA and assess performance uplift acheieved through tuning.
    +## Tune with local NUMA (Non-Uniform Memory Access)
     
    -Typically, cross-NUMA data transfers within the CPU incur higher latency than intra-NUMA transfers. Therefore, Tomcat should be deployed on the NUMA node where the network interface resides.
    +In this section, you configure local NUMA and assess the performance uplift achieved through tuning. Cross‑NUMA data transfers generally incur higher latency than intra‑NUMA transfers, so Tomcat should be deployed on the NUMA node where the network interface resides to reduce cross‑node memory traffic and improve throughput and latency.
     
    -### Setting local NUMA
    +### Configure local NUMA
    +
    +Check NUMA topology and relative latencies:
     
    -1. Use the following command to check that the latency for cross-NUMA transfers is greater than the latency for intra-NUMA transfers:
     ```bash
     numactl -H
     ```
     
    -It can be observed that the cross-NUMA latency to intra-NUMA latency ratio is 10:100.
    +You should see that cross‑NUMA latency is higher than intra‑NUMA latency (for example, 10:100):
    +
     ```output
     available: 2 nodes (0-1)
     node 0 cpus: 0 1 2 3 4 5 6 7
    @@ -33,28 +34,34 @@ node   0   1
       1:  100  10
     ```
     
    -2. Use the following command to check the NUMA node where the ${net} network interface resides.
    +Identify the NUMA node for your network interface (using the `${net}` variable defined earlier):
    +
     ```bash
     cat /sys/class/net/${net}/device/numa_node
     ```
    -You will notice that the NUMA node where the ${net} network interface resides is 1.
    +
    +Example output (NIC on NUMA node 1):
    +
     ```output
     1
     ```
     
    -3. As a result, allocate the reserved 8 cores to NUMA node 1.
    +Allocate the eight reserved cores to the NIC’s NUMA node (the example below keeps CPUs 96–103 online on node 1 and offlines the rest):
    +
     ```bash
     for no in {96..103}; do sudo bash -c "echo 1 > /sys/devices/system/cpu/cpu${no}/online"; done
     for no in {0..95} {104..191}; do sudo bash -c "echo 0 > /sys/devices/system/cpu/cpu${no}/online"; done
     ```
     
    -4. Verify whether the settings have been successfully applied.
    +Verify CPU online status and NUMA placement:
    +
     ```bash
     lscpu
     ```
     
    -From the output you will see that the only online CPUs are 72-79 on NUMA node 1.
    -```bash
    +You should see only CPUs 96–103 online on NUMA node 1:
    +
    +```output
     Architecture:                aarch64
       CPU op-mode(s):            64-bit
       Byte Order:                Little Endian
    @@ -71,20 +78,23 @@ NUMA:
     ...
     ```
     
    -### The result after tuning local NUMA
    +### Validate performance after NUMA tuning
    +
    +Restart Tomcat on the Arm Neoverse bare‑metal instance:
     
    -1. Shutdown and start Tomcat on the Arm Neoverse bare-metal instance:
     ```bash
     ~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
     ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
     ```
     
    -2. Run `wrk2` on the `x86_64` bare-metal instance:
    +Run `wrk2` on the `x86_64` bare‑metal client to measure throughput and latency:
    +
     ```bash
     ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://${tomcat_ip}:8080/examples/servlets/servlet/HelloWorldExample
     ```
     
    -The result after configuring NUMA node should look like:
    +Sample results after placing Tomcat on the NIC’s local NUMA node:
    +
     ```output
       Thread Stats   Avg      Stdev     Max   +/- Stdev
         Latency     9.41s     4.71s   18.02s    61.07%
    
    From 11afffdf43721fcb614226c6ef6f42ac62ef1975 Mon Sep 17 00:00:00 2001
    From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
    Date: Thu, 4 Sep 2025 14:16:49 +0000
    Subject: [PATCH 10/31] Content dev
    
    ---
     .../1_setup.md                                |  4 +--
     .../2_baseline.md                             |  8 ++---
     .../4_local-numa.md                           |  6 ++--
     .../5_iommu.md                                | 34 ++++++++++++-------
     .../6_summary.md                              | 29 +++++++++++-----
     .../_index.md                                 |  2 +-
     6 files changed, 51 insertions(+), 32 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/1_setup.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/1_setup.md
    index 0c09c6a3b5..8666e349a8 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/1_setup.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/1_setup.md
    @@ -8,7 +8,7 @@ layout: learningpathall
     
     ## Overview
     
    -Tomcat is a common client–server web workload that serves HTTP/HTTPS requests. In this section, you will set up a benchmarking environment using **Apache Tomcat** (server) and **wrk2** (client) to generate load and measure performance on an Arm-based bare‑metal instance. This guide was validated on an AWS **c8g.metal‑48xl** running Ubuntu 24.04.
    +Tomcat is a common client–server web workload that serves HTTP/HTTPS requests. In this section, you will set up a benchmarking environment using Apache Tomcat (server) and `wrk2` (client) to generate load and measure performance on an Arm-based bare‑metal instance. This guide was validated on an AWS `c8g.metal‑48xl` instance running Ubuntu 24.04.
     
     ## Set up the Tomcat benchmark server
     
    @@ -36,7 +36,7 @@ Alternatively, you can build Tomcat [from source](https://github.com/apache/tomc
     
     ## Enable access to Tomcat examples
     
    -To access the built‑in examples from your local network or external IP, modify the `context.xml` file and update the `RemoteAddrValve` to allow your clients.
    +To access the built‑in examples from your local network or external IP, modify the `context.xml` file and update `RemoteAddrValve` to allow your clients.
     
     The file is located at:
     
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/2_baseline.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/2_baseline.md
    index 75d9450f52..65811081ef 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/2_baseline.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/2_baseline.md
    @@ -26,7 +26,7 @@ This baseline includes:
     - Disabling access logging
     - Setting optimal thread counts
     
    -### Align IOMMU settings with Ubuntu defaults
    +## Align IOMMU settings with Ubuntu defaults
     
     {{% notice Note %}}
     If you are using a cloud image (for example, AWS) with non-default kernel parameters, align IOMMU settings with the Ubuntu defaults: `iommu.strict=1` and `iommu.passthrough=0`.
    @@ -60,7 +60,7 @@ You should see that under the default configuration, `iommu.strict` is enabled,
     ...
     ```
     
    -### Establish a baseline on Arm Neoverse bare-metal instances
    +## Establish a baseline on Arm Neoverse bare-metal instances
     
     {{% notice Note %}}
     To mirror a typical Tomcat deployment and simplify tuning, keep **8 CPU cores online** and set the remaining cores offline. Adjust the CPU range to match your instance. The example below assumes 192 CPUs (as on AWS `c8g.metal-48xl`).
    @@ -115,7 +115,7 @@ To mirror a typical Tomcat deployment and simplify tuning, keep **8 CPU cores on
         Transfer/sec:    129.90MB
         ```
     
    -### Disable access logging
    +## Disable access logging
     
     Disabling access logs removes I/O overhead during benchmarking.
     
    @@ -157,7 +157,7 @@ Disabling access logs removes I/O overhead during benchmarking.
         Transfer/sec:    144.36MB
         ```
     
    -### Set optimal thread counts
    +## Set optimal thread counts
     
     To minimize contention and context switching, align Tomcat’s CPU‑intensive thread count with available CPU cores.
     
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/4_local-numa.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/4_local-numa.md
    index 68f1a04a28..ce2fe4b622 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/4_local-numa.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/4_local-numa.md
    @@ -1,5 +1,5 @@
     ---
    -title: NUMA-based Tuning
    +title: NUMA-based tuning
     weight: 5
     
     ### FIXED, DO NOT MODIFY
    @@ -10,7 +10,7 @@ layout: learningpathall
     
     In this section, you configure local NUMA and assess the performance uplift achieved through tuning. Cross‑NUMA data transfers generally incur higher latency than intra‑NUMA transfers, so Tomcat should be deployed on the NUMA node where the network interface resides to reduce cross‑node memory traffic and improve throughput and latency.
     
    -### Configure local NUMA
    +## Configure local NUMA
     
     Check NUMA topology and relative latencies:
     
    @@ -78,7 +78,7 @@ NUMA:
     ...
     ```
     
    -### Validate performance after NUMA tuning
    +## Validate performance after NUMA tuning
     
     Restart Tomcat on the Arm Neoverse bare‑metal instance:
     
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/5_iommu.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/5_iommu.md
    index af6b695888..9afc55ef33 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/5_iommu.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/5_iommu.md
    @@ -6,28 +6,30 @@ weight: 6
     layout: learningpathall
     ---
     
    -## IOMMU-based tuning
    -IOMMU (Input-Output Memory Management Unit) is a hardware feature that manages how I/O devices access memory. 
    -In cloud environments, SmartNICs are typically used to offload the IOMMU workload. On bare-metal systems, to align performance with the cloud, you should disable `iommu.strict` and enable `iommu.passthrough` settings to achieve better performance.
    +## Tune with IOMMU
     
    -### Setting IOMMU
    +IOMMU (Input–Output Memory Management Unit) controls how I/O devices access memory. In many cloud environments, SmartNICs offload IOMMU-related work. On Arm Neoverse bare‑metal systems, you can often improve Tomcat networking performance by **disabling strict mode** and **enabling passthrough** (setting `iommu.strict=0` and `iommu.passthrough=1`).
     
    -1. To configure the IOMMU setting, use a text editor to modify the `grub` file by adding or updating the `GRUB_CMDLINE_LINUX` configuration.
    +## Configure IOMMU settings
    +
    +Edit the GRUB configuration to set IOMMU to passthrough and disable strict invalidations:
     
     ```bash
     sudo vi /etc/default/grub
     ```
    -then add or update:
    +Add or update the kernel command line:
     ```bash
     GRUB_CMDLINE_LINUX="iommu.strict=0 iommu.passthrough=1"
     ```
     
    -2. Update GRUB and reboot to apply the settings.
    +Update GRUB and reboot to apply the settings:
    +
     ```bash
     sudo update-grub && sudo reboot
     ```
     
    -3. Verify if the settings have been successfully applied:
    +Verify that IOMMU is in passthrough mode after reboot:
    +
     ```bash
     sudo dmesg | grep iommu
     ```
    @@ -38,24 +40,30 @@ You will notice that the IOMMU is already in passthrough mode:
     [    0.855658] iommu: Default domain type: Passthrough (set via kernel command line)
     ```
     
    -### The result after configuring IOMMU
    +## Validate performance after IOMMU tuning
    +
    +Prepare the Arm Neoverse bare‑metal server (ensure your `${net}` interface variable is set; if not, set it to your NIC name, for example `net=enP11p4s0`), align queues, and restart Tomcat:
     
    -1. Run the following command on the Arm Neoverse bare-metal where `Tomcat` is on:
     ```bash
     for no in {96..103}; do sudo bash -c "echo 1 > /sys/devices/system/cpu/cpu${no}/online"; done
     for no in {0..95} {104..191}; do sudo bash -c "echo 0 > /sys/devices/system/cpu/cpu${no}/online"; done
    -net=$(ls /sys/class/net/ | grep 'en')
    +
    +# Ensure NIC queue count matches the number of online CPUs (example: 8)
     sudo ethtool -L ${net} combined 8
    +
    +# Restart Tomcat with a higher file‑descriptor limit
     ~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
     ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
     ```
     
    -2. Run run `wrk2` on the `x86_64` bare-metal instance as shown:
    +Run `wrk2` on the `x86_64` benchmarking client to measure throughput and latency:
    +
     ```bash
     ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://${tomcat_ip}:8080/examples/servlets/servlet/HelloWorldExample
     ```
     
    -The result after iommu tuning should look like:
    +Sample results after IOMMU tuning:
    +
     ```output
       Thread Stats   Avg      Stdev     Max   +/- Stdev
         Latency     4.92s     2.49s   10.08s    62.27%
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/6_summary.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/6_summary.md
    index 0a5decc13c..8d742be719 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/6_summary.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/6_summary.md
    @@ -6,15 +6,26 @@ weight: 7
     layout: learningpathall
     ---
     
    -## Summary
    -You will observe that each tuning method can bring significant performance improvements while running Tomcat as shown in the results summary below:
    +## Review the results: Tomcat performance tuning on Arm Neoverse
     
    -| Method          | Requests/sec | Latency-Avg |
    -|:----------------|:-------------|:------------|
    -| Baseline         | 357835.75    | 10.26s      |
    -| NIC-Queue       | 378782.37    | 8.35s       |
    -| NUMA-Local      | 363744.39    | 9.41s       |
    -| IOMMU           | 428628.50    | 4.92s       |
    +Each tuning technique delivered measurable gains for the Tomcat HTTP benchmark on an Arm Neoverse bare‑metal server (workload generated with **wrk2**). The table summarizes requests per second and average latency at each stage.
     
    +| Method       | Requests/sec | Avg latency (s) |
    +|:-------------|-------------:|----------------:|
    +| Baseline     | 357,835.75   | 10.26           |
    +| NIC queues   | 378,782.37   | 8.35            |
    +| NUMA-local   | 363,744.39   | 9.41            |
    +| IOMMU        | 428,628.50   | 4.92            |
     
    -The same tuning methods can be applied as general guidance to help optimize and tune other network-based workloads.
    +### Key takeaways
    +
    +- **IOMMU passthrough** produced the largest throughput gain: **+19.8%** vs. baseline, with a **52.0%** drop in average latency.
    +- **NIC queue count alignment** improved throughput by **+5.9%** and reduced average latency by **18.6%**.
    +- **NUMA locality** yielded a smaller but consistent benefit: **+1.7%** throughput and **8.3%** lower average latency.
    +- Together, these techniques (IOMMU tuning, NIC queue optimization, and NUMA-aware placement) form a practical checklist for improving network workload performance on Arm Neoverse.
    +
    +### Next steps
    +
    +- Apply the same tuning pattern to other HTTP services and microservices (for example, NGINX, Envoy, or custom Jetty/Tomcat apps).
    +- Re‑evaluate queue counts, CPU pinning, and IOMMU mode as you scale cores, update kernels, or change NIC drivers/firmware.
    +- Track end‑to‑end SLOs (p95/p99 latency and error rates) in addition to average metrics to ensure sustained gains under real traffic.
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/_index.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/_index.md
    index 21242d6140..0c69e2ce36 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/_index.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/_index.md
    @@ -14,7 +14,7 @@ learning_objectives:
     
     prerequisites:
         - An Arm Neoverse-based bare-metal server running Ubuntu 24.04 to run Apache Tomcat (this Learning Path was tested with an AWS c8g.metal-48xl instance)
    -    - Access to an x86_64 bare-metal server running Ubuntu 24.04 to run wrk2
    +    - Access to an x86_64 bare-metal server running Ubuntu 24.04 to run `wrk2`
         - Basic familiarity with Java applications
     
     author: Ying Yu, Ker Liu, Rui Chang
    
    From eac28129d40a401fd465faf9c3964a345b7f7e5f Mon Sep 17 00:00:00 2001
    From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
    Date: Thu, 4 Sep 2025 18:30:37 +0000
    Subject: [PATCH 11/31] Final tweaks
    
    ---
     .../1_setup.md                                |   8 +-
     .../2_baseline.md                             | 130 +++++++++---------
     .../3_nic-queue.md                            |   2 +-
     .../5_iommu.md                                |   2 +-
     .../_index.md                                 |  12 +-
     5 files changed, 77 insertions(+), 77 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/1_setup.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/1_setup.md
    index 8666e349a8..2a6ed40924 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/1_setup.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/1_setup.md
    @@ -8,7 +8,7 @@ layout: learningpathall
     
     ## Overview
     
    -Tomcat is a common client–server web workload that serves HTTP/HTTPS requests. In this section, you will set up a benchmarking environment using Apache Tomcat (server) and `wrk2` (client) to generate load and measure performance on an Arm-based bare‑metal instance. This guide was validated on an AWS `c8g.metal‑48xl` instance running Ubuntu 24.04.
    +Tomcat is a common client–server web workload that serves HTTP/HTTPS requests. In this section, you will set up a benchmarking environment using Apache Tomcat (server) and `wrk2` (client) to generate load and measure performance on an Arm-based bare‑metal instance. This Learning Path was validated on an AWS `c8g.metal‑48xl` instance running Ubuntu 24.04.
     
     ## Set up the Tomcat benchmark server
     
    @@ -63,7 +63,7 @@ Allowing `.*` permits access from all IP addresses and should be used only in is
     ## Start the Tomcat server
     
     {{% notice Note %}}
    -For maximum performance, ensure the per‑process limit for open file descriptors is high enough.
    +For maximum performance, ensure the per‑process limit for open file descriptors is sufficient.
     {{% /notice %}}
     
     Start the server:
    @@ -106,7 +106,7 @@ Ensure port **8080** is open in the security group or firewall for your Arm‑ba
     [Wrk2](https://github.com/giltene/wrk2) is a high-performance HTTP benchmarking tool specialized in generating constant throughput loads and measuring latency percentiles for web services. `wrk2` is an enhanced version of `wrk` that provides accurate latency statistics under controlled request rates, ideal for performance testing of HTTP servers.
     
     {{% notice Note %}}
    -Currently, `wrk2` is only supported on **x86_64** machines. Run the client steps below on a bare‑metal x86_64 server running Ubuntu 24.04.
    +Currently, `wrk2` is only supported on x86_64 machines. Run the client steps below on a bare‑metal x86_64 server running Ubuntu 24.04.
     {{% /notice %}}
     
     ## Install dependencies
    @@ -140,7 +140,7 @@ sudo cp wrk /usr/local/bin
     As with Tomcat, set a high open‑files limit to avoid hitting FD caps during the run.
     {{% /notice %}}
     
    -Benchmark the HelloWorld servlet running on Tomcat:
    +Benchmark the `HelloWorld` servlet running on Tomcat:
     
     ```bash
     ulimit -n 65535 && wrk -c32 -t16 -R50000 -d60 http://${tomcat_ip}:8080/examples/servlets/servlet/HelloWorldExample
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/2_baseline.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/2_baseline.md
    index 65811081ef..bea750eefd 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/2_baseline.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/2_baseline.md
    @@ -11,7 +11,7 @@ layout: learningpathall
     In this section, you establish a baseline configuration before applying advanced techniques to tune the performance of Tomcat-based network workloads on an Arm Neoverse bare-metal instance.
     
     {{% notice Note %}}
    -To avoid running out of file descriptors under load, raise the file‑descriptor limit on **both** the server and the client:
    +To avoid running out of file descriptors under load, raise the file‑descriptor limit on *both* the server and the client:
     ```bash
     ulimit -n 65535
     ```
    @@ -32,24 +32,24 @@ This baseline includes:
     If you are using a cloud image (for example, AWS) with non-default kernel parameters, align IOMMU settings with the Ubuntu defaults: `iommu.strict=1` and `iommu.passthrough=0`.
     {{% /notice %}}
     
    -1. Edit GRUB and add (or update) `GRUB_CMDLINE_LINUX`:
    +Edit GRUB and add (or update) `GRUB_CMDLINE_LINUX`:
     
    -    ```bash
    +```bash
         sudo vi /etc/default/grub
    -    ```
    +```
     
    -    Add or update the line to include:
    -    ```bash
    +Add or update the line to include:
    +```bash
         GRUB_CMDLINE_LINUX="iommu.strict=1 iommu.passthrough=0"
    -    ```
    +```
     
    -2. Update GRUB and reboot to apply the settings:
    +Update GRUB and reboot to apply the settings:
     
    -    ```bash
    +```bash
         sudo update-grub && sudo reboot
    -    ```
    +```
     
    -3. Verify that the default settings have been successfully applied:
    +Verify that the default settings have been successfully applied:
     ```bash
     sudo dmesg | grep iommu
     ```
    @@ -63,23 +63,23 @@ You should see that under the default configuration, `iommu.strict` is enabled,
     ## Establish a baseline on Arm Neoverse bare-metal instances
     
     {{% notice Note %}}
    -To mirror a typical Tomcat deployment and simplify tuning, keep **8 CPU cores online** and set the remaining cores offline. Adjust the CPU range to match your instance. The example below assumes 192 CPUs (as on AWS `c8g.metal-48xl`).
    +To mirror a typical Tomcat deployment and simplify tuning, keep 8 CPU cores online and set the remaining cores offline. Adjust the CPU range to match your instance. The example below assumes 192 CPUs (as on AWS `c8g.metal-48xl`).
     {{% /notice %}}
     
    -1. Set CPUs 8–191 offline:
    +Set CPUs 8–191 offline:
     
    -    ```bash
    +```bash
         for no in {8..191}; do sudo bash -c "echo 0 > /sys/devices/system/cpu/cpu${no}/online"; done
    -    ```
    +```
     
    -2. Confirm that CPUs `0–7` are online and the rest are offline:
    +Confirm that CPUs `0–7` are online and the rest are offline:
     
    -    ```bash
    +```bash
         lscpu
    -    ```
    +```
     
    -    Example output:
    -    ```output
    +Example output:
    +```output
         Architecture:                aarch64
           CPU op-mode(s):            64-bit
           Byte Order:                Little Endian
    @@ -89,23 +89,23 @@ To mirror a typical Tomcat deployment and simplify tuning, keep **8 CPU cores on
         Vendor ID:                   ARM
           Model name:                Neoverse-V2
         ...
    -    ```
    +```
     
    -3. Restart Tomcat on the Arm instance:
    +Restart Tomcat on the Arm instance:
     
    -    ```bash
    +```bash
         ~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
         ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
    -    ```
    +```
     
    -4. From your `x86_64` benchmarking client, run `wrk2` (replace `` with the server’s IP):
    +From your `x86_64` benchmarking client, run `wrk2` (replace `` with the server’s IP):
     
    -    ```bash
    +```bash
         ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://:8080/examples/servlets/servlet/HelloWorldExample
    -    ```
    +```
     
    -    Example result:
    -    ```output
    +Example result:
    +```output
           Thread Stats   Avg      Stdev     Max   +/- Stdev
             Latency    16.76s     6.59s   27.56s    56.98%
             Req/Sec     1.97k   165.05     2.33k    89.90%
    @@ -113,41 +113,41 @@ To mirror a typical Tomcat deployment and simplify tuning, keep **8 CPU cores on
           Socket errors: connect 1264, read 0, write 0, timeout 1748
         Requests/sec: 244449.62
         Transfer/sec:    129.90MB
    -    ```
    +```
     
     ## Disable access logging
     
     Disabling access logs removes I/O overhead during benchmarking.
     
    -1. Edit `server.xml` and comment out (or remove) the **`org.apache.catalina.valves.AccessLogValve`** block:
    +Edit `server.xml` and comment out (or remove) the **`org.apache.catalina.valves.AccessLogValve`** block:
     
    -    ```bash
    +```bash
         vi ~/apache-tomcat-11.0.10/conf/server.xml
    -    ```
    +```
     
    -    ```xml
    +```xml
         
    -    ```
    +```
     
    -2. Restart Tomcat:
    +Restart Tomcat:
     
    -    ```bash
    +```bash
         ~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
         ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
    -    ```
    +```
     
    -3. Re-run `wrk2`:
    +Re-run `wrk2`:
     
    -    ```bash
    +```bash
         ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://:8080/examples/servlets/servlet/HelloWorldExample
    -    ```
    +```
     
    -    Example result:
    -    ```output
    +Example result:
    +```output
           Thread Stats   Avg      Stdev     Max   +/- Stdev
             Latency    16.16s     6.45s   28.26s    57.85%
             Req/Sec     2.16k     5.91     2.17k    77.50%
    @@ -155,20 +155,20 @@ Disabling access logs removes I/O overhead during benchmarking.
           Socket errors: connect 0, read 0, write 0, timeout 75
         Requests/sec: 271675.12
         Transfer/sec:    144.36MB
    -    ```
    +```
     
     ## Set optimal thread counts
     
     To minimize contention and context switching, align Tomcat’s CPU‑intensive thread count with available CPU cores.
     
    -1. While `wrk2` is running, identify CPU‑intensive Tomcat threads:
    +While `wrk2` is running, identify CPU‑intensive Tomcat threads:
     
    -    ```bash
    +```bash
         top -H -p "$(pgrep -n java)"
    -    ```
    +```
     
    -    Example output:
    -    ```output
    +Example output:
    +```output
         top - 08:57:29 up 20 min,  1 user,  load average: 4.17, 2.35, 1.22
         Threads: 231 total,   8 running, 223 sleeping,   0 stopped,   0 zombie
         %Cpu(s): 31.7 us, 20.2 sy,  0.0 ni, 31.0 id,  0.0 wa,  0.0 hi, 17.2 si,  0.0 st
    @@ -204,24 +204,24 @@ To minimize contention and context switching, align Tomcat’s CPU‑intensive t
     ...
     ```
     
    -    You’ll typically see **`http-nio-8080-e`** and **`http-nio-8080-P`** threads as CPU intensive. Because the **`http-nio-8080-P`** thread count is fixed at 1 (in current Tomcat releases), and you have 8 online CPU cores, set **`http-nio-8080-e`** to **7**.
    +You’ll typically see `http-nio-8080-e` and `http-nio-8080-P` threads as CPU-intensive. Because the `http-nio-8080-P` thread count is fixed at 1 (in current Tomcat releases), and you have 8 online CPU cores, set `http-nio-8080-e` to 7.
     
    -2. Edit `server.xml` and update the HTTP connector to set the worker thread counts and connection limits:
    +Edit `server.xml` and update the HTTP connector to set the worker thread counts and connection limits:
     
    -    ```bash
    +```bash
         vi ~/apache-tomcat-11.0.10/conf/server.xml
    -    ```
    +```
     
    -    Replace the existing connector:
    -    ```xml
    +Replace the existing connector:
    +```xml
         
             
    -    ```
    +```
     
    -    With the tuned settings:
    -    ```xml
    +With the tuned settings:
    +```xml
         
             
    -    ```
    +```
     
    -3. Restart Tomcat and re-run `wrk2`:
    +Restart Tomcat and re-run `wrk2`:
     
    -    ```bash
    +```bash
         ~/apache-tomcat-11.0.10/bin/shutdown.sh 2>/dev/null
         ulimit -n 65535 && ~/apache-tomcat-11.0.10/bin/startup.sh
     
         ulimit -n 65535 && wrk -c1280 -t128 -R500000 -d60 http://:8080/examples/servlets/servlet/HelloWorldExample
    -    ```
    +```
     
    -    Example result:
    -    ```output
    +Example result:
    +```output
           Thread Stats   Avg      Stdev     Max   +/- Stdev
             Latency    10.26s     4.55s   19.81s    62.51%
             Req/Sec     2.86k    89.49     3.51k    77.06%
           21458421 requests in 1.00m, 11.13GB read
         Requests/sec: 357835.75
         Transfer/sec:    190.08MB
    -    ```
    +```
     
     With a solid baseline in place, you’re ready to proceed to NIC queue tuning, NUMA locality optimization, and IOMMU exploration in the next sections.
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/3_nic-queue.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/3_nic-queue.md
    index f49bad7421..d552fd065a 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/3_nic-queue.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/3_nic-queue.md
    @@ -41,7 +41,7 @@ Use the following command to check the current transmit/receive queues of the ${
     ```bash
     sudo ethtool -l ${net}
     ```
    -It can be observed that the number of transmit/receive queues for the ${net} network interface is currently 63.
    +You can see that the number of transmit/receive queues for the ${net} network interface is currently 63:
     ```bash
     Channel parameters for enP11p4s0:
     Pre-set maximums:
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/5_iommu.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/5_iommu.md
    index 9afc55ef33..4eab3abdb3 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/5_iommu.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/5_iommu.md
    @@ -8,7 +8,7 @@ layout: learningpathall
     
     ## Tune with IOMMU
     
    -IOMMU (Input–Output Memory Management Unit) controls how I/O devices access memory. In many cloud environments, SmartNICs offload IOMMU-related work. On Arm Neoverse bare‑metal systems, you can often improve Tomcat networking performance by **disabling strict mode** and **enabling passthrough** (setting `iommu.strict=0` and `iommu.passthrough=1`).
    +IOMMU (Input–Output Memory Management Unit) controls how I/O devices access memory. In many cloud environments, SmartNICs offload IOMMU-related work. On Arm Neoverse bare‑metal systems, you can often improve Tomcat networking performance by disabling strict mode and enabling passthrough (setting `iommu.strict=0` and `iommu.passthrough=1`).
     
     ## Configure IOMMU settings
     
    diff --git a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/_index.md b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/_index.md
    index 0c69e2ce36..af33b1c966 100644
    --- a/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/_index.md
    +++ b/content/learning-paths/servers-and-cloud-computing/tune-network-workloads-on-bare-metal/_index.md
    @@ -6,14 +6,14 @@ minutes_to_complete: 60
     who_is_this_for: This is an advanced topic for engineers who want to tune the performance of network workloads on Arm Neoverse-based bare-metal instances.
     
     learning_objectives: 
    -    - Set up a benchmarking environment using Apache Tomcat and wrk2 on an Arm Neoverse bare‑metal host
    -    - Establish a reproducible baseline performance configuration (throughput and latency) before tuning
    -    - Tune NIC multi‑queue, RSS/RPS/XPS, and IRQ affinity to increase throughput and stabilize latency
    -    - Optimize NUMA locality by pinning Tomcat workers and interrupts to local CPUs and memory
    -    - Evaluate IOMMU configuration options and select the setting that maximizes networking performance
    +    - Set up Apache Tomcat and wrk2 to benchmark HTTP on an Arm Neoverse bare‑metal host
    +    - Establish a reproducible baseline baseline (file‑descriptor limits, logging, thread counts, fixed core set)
    +    - Tune NIC queue count to match available cores and measure impact
    +    - Improve NUMA locality by placing Tomcat on the NIC’s NUMA node and aligning worker threads with cores
    +    - Compare IOMMU strict mode and IOMMU passthrough mode, and select the configuration that delivers the best performance for your workload
     
     prerequisites:
    -    - An Arm Neoverse-based bare-metal server running Ubuntu 24.04 to run Apache Tomcat (this Learning Path was tested with an AWS c8g.metal-48xl instance)
    +    - An Arm Neoverse-based bare-metal server running Ubuntu 24.04 to run Apache Tomcat
         - Access to an x86_64 bare-metal server running Ubuntu 24.04 to run `wrk2`
         - Basic familiarity with Java applications
     
    
    From 19dccf9aff412d8a9b9e6925399dd7b18a80eecb Mon Sep 17 00:00:00 2001
    From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
    Date: Fri, 5 Sep 2025 11:39:11 +0000
    Subject: [PATCH 12/31] Content dev
    
    ---
     .../github-on-arm/_index.md                   | 38 +++++++++----------
     1 file changed, 17 insertions(+), 21 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md
    index 3c68beb5c2..428dfd3196 100644
    --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md
    +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md
    @@ -1,13 +1,9 @@
     ---
     title: Deploy GitHub Actions Self-Hosted Runner on Google Axion C4A virtual machine
     
    -draft: true
    -cascade:
    -    draft: true
    -    
     minutes_to_complete: 15
     
    -who_is_this_for: This is an introductory topic for developers who want to deploy GitHub Actions Self-Hosted Runner on an Arm-based Google Axion C4A instance.
    +who_is_this_for: This is an introductory topic for developers who want to deploy a GitHub Actions self-hosted runner on an Arm-based Google Axion C4A instance.
     
     learning_objectives:
            - Provision an Arm virtual machine on the Google Cloud Platform using the C4A Google Axion instance family.
    @@ -15,8 +11,8 @@ learning_objectives:
            - Deploy a basic CI workflow with NGINX and verify execution on Arm infrastructure.
     
     prerequisites:
    -     - A [Google Cloud Platform (GCP)](https://cloud.google.com/free?utm_source=google&hl=en) account with billing enabled.
    -     - A GitHub account. You can sign up [here](https://github.com/signup).
    +  - A [Google Cloud Platform (GCP)](https://cloud.google.com/free?utm_source=google&hl=en) account with billing enabled
    +  - A GitHub account (you can sign up [here](https://github.com/signup))
     
     author: Annie Tallund
     
    @@ -39,20 +35,20 @@ operatingsystems:
     #       FIXED, DO NOT MODIFY
     # ================================================================================
     further_reading:
    -    - resource:
    -        title: Google Cloud official website and documentation
    -        link: https://cloud.google.com/docs
    -        type: documentation
    -
    -    - resource:
    -        title: Github-action official website and documentation
    -        link: https://docs.github.com/en/actions
    -        type: documentation
    -
    -    - resource:
    -        title: GitHub Actions Arm runners
    -        link: https://github.blog/news-insights/product-news/arm64-on-github-actions-powering-faster-more-efficient-build-systems/
    -        type: website
    +  - resource:
    +      title: Google Cloud documentation
    +      link: https://cloud.google.com/docs
    +      type: documentation
    +
    +  - resource:
    +      title: GitHub Actions documentation
    +      link: https://docs.github.com/en/actions
    +      type: documentation
    +
    +  - resource:
    +      title: GitHub Actions Arm runners (announcement)
    +      link: https://github.blog/news-insights/product-news/arm64-on-github-actions-powering-faster-more-efficient-build-systems/
    +      type: website
     
         - resource:
             title: GCP Quickstart Guide to Create a virtual machine
    
    From 3ba1bd3b33d46718212ded84a051c1f7ca75b0a9 Mon Sep 17 00:00:00 2001
    From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
    Date: Fri, 5 Sep 2025 12:02:29 +0000
    Subject: [PATCH 13/31] Content development
    
    ---
     .../github-on-arm/_index.md                   |  2 +-
     .../github-on-arm/background.md               |  8 ++---
     .../github-on-arm/instance.md                 | 34 ++++++++++---------
     3 files changed, 23 insertions(+), 21 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md
    index 428dfd3196..7cd61c1a8d 100644
    --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md
    +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md
    @@ -50,7 +50,7 @@ further_reading:
           link: https://github.blog/news-insights/product-news/arm64-on-github-actions-powering-faster-more-efficient-build-systems/
           type: website
     
    -    - resource:
    +  - resource:
             title: GCP Quickstart Guide to Create a virtual machine
             link: https://cloud.google.com/compute/docs/instances/create-start-instance
             type: website
    diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/background.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/background.md
    index e450977285..6c10d96544 100644
    --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/background.md
    +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/background.md
    @@ -8,11 +8,11 @@ layout: "learningpathall"
     
     ## Google Axion C4A series
     
    -The Google Axion C4A series is a family of Arm-based virtual machines built on Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high-performance and energy-efficient computing, these virtual machines offer strong performance ideal for modern cloud workloads such as CI/CD pipelines, microservices, media processing, and general-purpose applications.
    +The Google Axion C4A series is a family of Arm-based virtual machines (VMs) built on Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high-performance and energy-efficient computing, these virtual machines offer strong performance ideal for modern cloud workloads such as CI/CD pipelines, microservices, media processing, and general-purpose applications.
     
    -The C4A series provides offer a cost-effective virtual machine while leveraging the scalability and performance benefits of the Arm architecture in Google Cloud.
    +The C4A series provides cost-effective VMs while leveraging the scalability and performance benefits of the Arm architecture on Google Cloud.
     
    -To learn more about Google Axion, refer to the blog [Introducing Google Axion Processors, our new Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu).
    +Learn more in Google’s announcement: [Introducing Google Axion processors, our new Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu).
     
     ## GitHub Actions and CI/CD
     
    @@ -24,4 +24,4 @@ A key feature of GitHub Actions is [self-hosted runners](https://docs.github.com
     - Private network access, allowing secure interaction with internal services or databases.
     - Faster execution, especially for resource-intensive workflows, by using dedicated or high-performance machines.
     
    -Self-hosted runners provide more control, flexibility, and cost-efficiency—making them ideal for advanced CI/CD pipelines and platform-specific testing.
    +Self-hosted runners give you more control, flexibility, and cost efficiency - ideal for advanced CI/CD pipelines and platform-specific testing.
    diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md
    index 632266e2d3..cc1b201f40 100644
    --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md
    +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md
    @@ -8,26 +8,28 @@ layout: learningpathall
     
     ## Introduction
     
    -This section walks you through creating **Google Axion C4A Arm virtual machine** on GCP with the **c4a-standard-4 (4 vCPUs, 16 GB Memory)** machine type, using the **Google Cloud Console**.
    +This section walks you through creating a **Google Axion C4A Arm virtual machine** on Google Cloud with the **c4a-standard-4 (4 vCPUs, 16 GB memory)** machine type using the **Google Cloud Console**. You will use this VM later as the host for a GitHub Actions self-hosted runner.
     
    -If you haven't got a Google Cloud account, you can follow the Learning Path on [Getting Started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/) to get started.
    +If you don't have a Google Cloud account, see the Learning Path [Getting started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/).
     
    -### Create an Arm-based Virtual Machine (C4A)
    +### Create an Arm-based virtual machine (C4A)
     
    -To create a virtual machine based on the C4A Arm architecture:
    -1. Open the [Google Cloud Console](https://console.cloud.google.com/).
    -2. Navigate to the card **Compute Engine** and click on **Create Instance**.
    -3. Under the **Machine Configuration**:
    -      - Fill in basic details like **Instance Name**, **Region**, and **Zone**.
    -      - Choose the **Series** as `C4A`.
    -      - Select a machine type such as `c4a-standard-4`.
    -![Instance Screenshot](./images/select-instance.png)
    -4. Under the **OS and Storage**, click on **Change**, pick **Ubuntu** as the Operating System with **Ubuntu 24.04 LTS Minimal** as the Version. Make sure you pick the version of image for Arm.
    -5. Under **Networking**, enable **Allow HTTP traffic** to test workloads like NGINX later.
    -6. Click on **Create**, and the instance will launch.
    +Follow these steps in the Google Cloud Console:
    +
    +- Open the [Google Cloud Console](https://console.cloud.google.com/).
    +- Go to **Navigation menu ▸ Compute Engine ▸ VM instances**, then select **Create instance**.
    +- Under **Machine configuration**:
    +  - Enter **Instance name**, **Region**, and **Zone**.
    +  - Set **Series** to `C4A`.
    +  - Choose a machine type such as `c4a-standard-4`.
    +- Under **OS and storage**, select **Change**, pick **Ubuntu** as the operating system, and choose **Ubuntu 24.04 LTS Minimal**. Make sure you select the Arm image variant.
    +- Under **Networking**, enable **Allow HTTP traffic** so you can test workloads like NGINX later.
    +- Select **Create** to launch the instance.
    +
    +![Google Cloud Console page showing C4A VM creation with c4a-standard-4 selected](./images/select-instance.png "Create a C4A VM in the Google Cloud Console")
     
     {{% notice Important %}}
    -You should not enable the **Allow HTTP traffic** permanently, since this poses a security risk. For the long-term, you should only allow traffic from the IP address you use to connect to the instance.
    +Do not leave **Allow HTTP traffic** enabled permanently. For long-term use, allow traffic only from the IP addresses you use to connect to the instance.
     {{% /notice %}}
     
    -You can access the Google Cloud Console by clicking the **SSH** button in the instance overview. Use this command line interface (CLI) to run the commands in the remainder of this Learning Path.
    +Access the VM from the instance list by selecting **SSH** in the instance overview. Use this command line interface (CLI) to run the commands in the remainder of this Learning Path.
    
    From 82e59f923aa20c354c8e2f6cd49e984ce113ef52 Mon Sep 17 00:00:00 2001
    From: Arnaud de Grandmaison 
    Date: Fri, 5 Sep 2025 16:37:26 +0200
    Subject: [PATCH 14/31] Fix verify_index_fields.py so it splits input on yaml's
     '---'
    
    and not any '---' that appears in the file.
    ---
     tools/verify_index_fields.py | 8 ++++----
     1 file changed, 4 insertions(+), 4 deletions(-)
    
    diff --git a/tools/verify_index_fields.py b/tools/verify_index_fields.py
    index 58808669a4..f887c5af73 100644
    --- a/tools/verify_index_fields.py
    +++ b/tools/verify_index_fields.py
    @@ -33,10 +33,10 @@ def extract_frontmatter(path):
             content = f.read()
         if not content.startswith('---'):
             return None
    -    parts = content.split('---', 2)
    -    if len(parts) < 3:
    -        return None
    -    return yaml.safe_load(parts[1])
    +    parts = list(yaml.safe_load_all(content))
    +    if len(parts) >= 2:
    +        return parts[0]
    +    return None
     
     def get_category_from_path(path):
         match = re.match(r"content/learning-paths/([^/]+)/", path)
    
    From 1f04511c0e4d2f76064979739aca824826da7440 Mon Sep 17 00:00:00 2001
    From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
    Date: Fri, 5 Sep 2025 14:58:46 +0000
    Subject: [PATCH 15/31] Content dev
    
    ---
     .../github-on-arm/_index.md                   |   8 +-
     .../github-on-arm/background.md               |   8 +-
     .../github-on-arm/deploy.md                   | 194 +++++++++++++-----
     .../github-on-arm/instance.md                 |   8 +-
     4 files changed, 153 insertions(+), 65 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md
    index 7cd61c1a8d..5a5c0314a7 100644
    --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md
    +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/_index.md
    @@ -6,13 +6,13 @@ minutes_to_complete: 15
     who_is_this_for: This is an introductory topic for developers who want to deploy a GitHub Actions self-hosted runner on an Arm-based Google Axion C4A instance.
     
     learning_objectives:
    -       - Provision an Arm virtual machine on the Google Cloud Platform using the C4A Google Axion instance family.
    -       - Set up and validate a GitHub Actions self-hosted runner on the Arm virtual machine.
    -       - Deploy a basic CI workflow with NGINX and verify execution on Arm infrastructure.
    +       - Provision an Arm virtual machine on the Google Cloud Platform using the C4A Google Axion instance family
    +       - Set up and validate a GitHub Actions self-hosted runner on the Arm virtual machine
    +       - Deploy a basic CI workflow with NGINX and verify execution on Arm infrastructure
     
     prerequisites:
       - A [Google Cloud Platform (GCP)](https://cloud.google.com/free?utm_source=google&hl=en) account with billing enabled
    -  - A GitHub account (you can sign up [here](https://github.com/signup))
    +  - A GitHub account; you can sign up [here](https://github.com/signup)
     
     author: Annie Tallund
     
    diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/background.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/background.md
    index 6c10d96544..a193194968 100644
    --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/background.md
    +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/background.md
    @@ -16,12 +16,12 @@ Learn more in Google’s announcement: [Introducing Google Axion processors, our
     
     ## GitHub Actions and CI/CD
     
    -GitHub Actions is a powerful CI/CD (Continuous Integration and Continuous Delivery) platform built into GitHub. It allows developers to automate tasks such as building, testing, and deploying code in response to events like code pushes, pull requests, or scheduled jobs—directly from their GitHub repositories. This helps improve development speed, reliability, and collaboration.
    +GitHub Actions is a powerful CI/CD (Continuous Integration and Continuous Delivery) platform built into GitHub. It allows developers to automate tasks such as building, testing, and deploying code in response to events like code pushes, pull requests, or scheduled jobs - directly from their GitHub repositories. This helps improve development speed, reliability, and collaboration.
     
     A key feature of GitHub Actions is [self-hosted runners](https://docs.github.com/en/actions/concepts/runners/about-self-hosted-runners), which let you run workflows on your own infrastructure instead of GitHub’s hosted servers. This is especially useful for:
     
    -- Running on custom hardware, including Arm64-based systems (e.g., Google Axion virtual machine), to optimize performance and ensure architecture-specific compatibility.
    -- Private network access, allowing secure interaction with internal services or databases.
    -- Faster execution, especially for resource-intensive workflows, by using dedicated or high-performance machines.
    +- Running on custom hardware, including Arm64-based systems (for example, Google Axion virtual machine), to optimize performance and ensure architecture-specific compatibility
    +- Private network access, allowing secure interaction with internal services or databases
    +- Faster execution, especially for resource-intensive workflows, by using dedicated or high-performance machines
     
     Self-hosted runners give you more control, flexibility, and cost efficiency - ideal for advanced CI/CD pipelines and platform-specific testing.
    diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/deploy.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/deploy.md
    index 348852d98b..b275f2b2ca 100644
    --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/deploy.md
    +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/deploy.md
    @@ -6,10 +6,11 @@ weight: 4
     layout: learningpathall
     ---
     
    +## Overview
     
    -This section shows how to deploy a self-hosted GitHub Actions runner on your instance. It covers installing Git and GitHub CLI, authenticating with GitHub and configuring the runner on an Arm64 environment for optimized CI/CD workflows.
    +This section showsyou how to deploy a GitHub Actions self-hosted runner on your Arm64 Google Axion C4A instance. You will install Git and GitHub CLI, authenticate with GitHub, and register the runner so CI/CD workflows run on Arm infrastructure.
     
    -### Set up development environment
    +## Set up your development environment
     
     Start by installing the required dependencies using the `apt` package manager:
     
    @@ -18,7 +19,7 @@ sudo apt update
     sudo apt install -y git gh vim
     ```
     
    -Next step is to configure your git credentials. Update the command with your name and email.
    +Configure your Git identity:
     
     ```bash
     git config --global user.email "you@example.com"
    @@ -27,14 +28,101 @@ git config --global user.name "Your Name"
     
     Now you are ready to connect the machine to GitHub. The command below is used to authenticate the GitHub CLI with your GitHub account. It allows you to securely log in using a web browser or token, enabling the CLI to interact with repositories, actions, and other GitHub features on your behalf.
     
    +Authenticate with GitHub:
     
     ```console
     gh auth login
     ```
     
    -The command will prompt you to make a few choices. For this use-case, you can use the default ones as shown in the image below.
    +Follow the prompts and accept the defaults.
     
    -![Login to GitHub](./images/gh-auth.png)
    +![Login to GitHub alt-text#center](./images/gh-auth.png "Screenshot of GitHub authentication prompt")
    +
    +{{% notice %}}
    +If you get an error opening the browser on your virtual machine, you can navigate to the following URL on the host machine and enter the device code displayed in the CLI of the virtual machine: 
    +```
    +https://github.com/login/device
    +```
    +{{% /notice %}}
    +
    +When authentication succeeds, you will see a confirmation screen in your browser:
    +
    +![GitHub UIalt-text#center](./images/login-page.png "Screenshot of successful GitHub login confirmation")
    +
    +## Test GitHub CLI and Git
    +
    +The command below creates a new public GitHub repository named **test-repo** using the GitHub CLI. It sets the repository visibility to public, meaning that anyone can view it:
    +
    +```console
    +gh repo create test-repo --public
    +```
    +You should see an output similar to:
    +```output
    +✓ Created repository /test-repo on GitHub
    +  https://github.com//test-repo
    +  ```
    +
    +
    +  ## Configure the self-hosted runner
    +
    +  In your repository, go to **Settings** → **Actions** → **Runners** and select **Add runner**, or view existing self-hosted runners.
    +
    +  {{% notice Note %}}
    +  If the **Actions** tab is not visible, enable Actions under **Settings** → **Actions** → **General** by selecting **Allow all actions and reusable workflows**.
    +  {{% /notice %}}
    +
    +  ![runner](./images/newsh-runner.png)
    +
    +  Then, click on the **New self-hosted runner** button. In the **Add new self-hosted runner** section. Select Linux for the operating system, and choose ARM64 for the architecture. This will generate commands to set up the runner. Copy and run them on your Google Axion C4A virtual machine.
    +
    +  ![new-runner](./images/new-runner.png)
    +
    +  The final command links the runner to your GitHub repo using a one-time registration token.
    +
    +  During the command’s execution, you will be prompted to provide the runner group, the name of the runner, and the work folder name. You can accept the defaults by pressing **Enter** at each step. The output will resemble as below:
    +
    +  ```output
    +  --------------------------------------------------------------------------------
    +  |        ____ _ _   _   _       _          _        _   _                      |
    +  |       / ___(_) |_| | | |_   _| |__      / \   ___| |_(_) ___  _ __  ___      |
    +  |      | |  _| | __| |_| | | | | '_ \    / _ \ / __| __| |/ _ \| '_ \/ __|     |
    +  |      | |_| | | |_|  _  | |_| | |_) |  / ___ \ (__| |_| | (_) | | | \__ \     |
    +  |       \____|_|\__|_| |_|\__,_|_.__/  /_/   \_\___|\__|_|\___/|_| |_|___/     |
    +  |                                                                              |
    +  |                       Self-hosted runner registration                        |
    +  |                                                                              |
    +  --------------------------------------------------------------------------------
    +
    +  # Authentication
    +
    +  √ Connected to GitHub
    +  # Runner Registration
    +  Enter the name of the runner group to add this runner to: [press Enter for Default]
    +  Enter the name of runner: [press Enter for lpprojectubuntuarm64]
    +  This runner will have the following labels: 'self-hosted', 'Linux', 'ARM64'
    +  Enter any additional labels (ex. label-1,label-2): [press Enter to skip]
    +  √ Runner successfully added
    +  √ Runner connection is good
    +  ```
    +
    +  Finally, start the runner by executing:
    +  ```console
    +  ./run.sh
    +  ```
    +  You should see an output similar to:
    +
    +  ```output
    +  √ Connected to GitHub
    +
    +  Current runner version: '2.326.0'
    +  2025-07-15 05:51:13Z: Listening for Jobs
    +  ```
    +  The runner will now be visible in the GitHub actions:
    +
    +  ![final-runner](./images/final-runner.png)
    +
    +  For now, you can terminate the `./run.sh` command with `Ctrl+C`. Move on to the next section to set up a simple web server using the runner.
    +](./images/gh-auth.png)
     
     {{% notice %}}
     If you get an error opening the browser on your virtual machine, you can navigate to the following URL on the host machine.
    @@ -59,66 +147,66 @@ You should see an output similar to:
     ```output
     ✓ Created repository /test-repo on GitHub
       https://github.com//test-repo
    -```
    +  ```
     
     
    -### Configure the Self-Hosted Runner
    +  ### Configure the Self-Hosted Runner
     
    -* Go to your repository's **Settings > Actions**, and under the **Runners** section
    -* Click on **Add Runner** or view existing self-hosted runners.
    +  * Go to your repository's **Settings > Actions**, and under the **Runners** section
    +  * Click on **Add Runner** or view existing self-hosted runners.
     
    -{{% notice Note %}}
    -If the **Actions** tab is not visible, ensure Actions are enabled by navigating to **Settings > Actions > General**, and select **Allow all actions and reusable workflows**.
    -{{% /notice %}}
    +  {{% notice Note %}}
    +  If the **Actions** tab is not visible, ensure Actions are enabled by navigating to **Settings > Actions > General**, and select **Allow all actions and reusable workflows**.
    +  {{% /notice %}}
     
    -![runner](./images/newsh-runner.png)
    +  ![runner](./images/newsh-runner.png)
     
    -Then, click on the **New self-hosted runner** button. In the **Add new self-hosted runner** section. Select Linux for the operating system, and choose ARM64 for the architecture. This will generate commands to set up the runner. Copy and run them on your Google Axion C4A virtual machine.
    +  Then, click on the **New self-hosted runner** button. In the **Add new self-hosted runner** section. Select Linux for the operating system, and choose ARM64 for the architecture. This will generate commands to set up the runner. Copy and run them on your Google Axion C4A virtual machine.
     
    -![new-runner](./images/new-runner.png)
    +  ![new-runner](./images/new-runner.png)
     
    -The final command links the runner to your GitHub repo using a one-time registration token.
    +  The final command links the runner to your GitHub repo using a one-time registration token.
     
    -During the command’s execution, you will be prompted to provide the runner group, the name of the runner, and the work folder name. You can accept the defaults by pressing **Enter** at each step. The output will resemble as below:
    +  During the command’s execution, you will be prompted to provide the runner group, the name of the runner, and the work folder name. You can accept the defaults by pressing **Enter** at each step. The output will resemble as below:
     
    -```output
    ---------------------------------------------------------------------------------
    -|        ____ _ _   _   _       _          _        _   _                      |
    -|       / ___(_) |_| | | |_   _| |__      / \   ___| |_(_) ___  _ __  ___      |
    -|      | |  _| | __| |_| | | | | '_ \    / _ \ / __| __| |/ _ \| '_ \/ __|     |
    -|      | |_| | | |_|  _  | |_| | |_) |  / ___ \ (__| |_| | (_) | | | \__ \     |
    -|       \____|_|\__|_| |_|\__,_|_.__/  /_/   \_\___|\__|_|\___/|_| |_|___/     |
    -|                                                                              |
    -|                       Self-hosted runner registration                        |
    -|                                                                              |
    ---------------------------------------------------------------------------------
    -
    -# Authentication
    -
    -√ Connected to GitHub
    -# Runner Registration
    -Enter the name of the runner group to add this runner to: [press Enter for Default]
    -Enter the name of runner: [press Enter for lpprojectubuntuarm64]
    -This runner will have the following labels: 'self-hosted', 'Linux', 'ARM64'
    -Enter any additional labels (ex. label-1,label-2): [press Enter to skip]
    -√ Runner successfully added
    -√ Runner connection is good
    -```
    +  ```output
    +  --------------------------------------------------------------------------------
    +  |        ____ _ _   _   _       _          _        _   _                      |
    +  |       / ___(_) |_| | | |_   _| |__      / \   ___| |_(_) ___  _ __  ___      |
    +  |      | |  _| | __| |_| | | | | '_ \    / _ \ / __| __| |/ _ \| '_ \/ __|     |
    +  |      | |_| | | |_|  _  | |_| | |_) |  / ___ \ (__| |_| | (_) | | | \__ \     |
    +  |       \____|_|\__|_| |_|\__,_|_.__/  /_/   \_\___|\__|_|\___/|_| |_|___/     |
    +  |                                                                              |
    +  |                       Self-hosted runner registration                        |
    +  |                                                                              |
    +  --------------------------------------------------------------------------------
     
    -Finally, start the runner by executing:
    -```console
    -./run.sh
    -```
    -You should see an output similar to:
    +  # Authentication
     
    -```output
    -√ Connected to GitHub
    +  √ Connected to GitHub
    +  # Runner Registration
    +  Enter the name of the runner group to add this runner to: [press Enter for Default]
    +  Enter the name of runner: [press Enter for lpprojectubuntuarm64]
    +  This runner will have the following labels: 'self-hosted', 'Linux', 'ARM64'
    +  Enter any additional labels (ex. label-1,label-2): [press Enter to skip]
    +  √ Runner successfully added
    +  √ Runner connection is good
    +  ```
     
    -Current runner version: '2.326.0'
    -2025-07-15 05:51:13Z: Listening for Jobs
    -```
    -The runner will now be visible in the GitHub actions:
    +  Finally, start the runner by executing:
    +  ```console
    +  ./run.sh
    +  ```
    +  You should see an output similar to:
    +
    +  ```output
    +  √ Connected to GitHub
    +
    +  Current runner version: '2.326.0'
    +  2025-07-15 05:51:13Z: Listening for Jobs
    +  ```
    +  The runner will now be visible in the GitHub actions:
     
    -![final-runner](./images/final-runner.png)
    +  ![final-runner](./images/final-runner.png)
     
    -For now, you can terminate the `./run.sh` command with `Ctrl+C`. Move on to the next section to set up a simple web server using the runner.
    +  For now, you can terminate the `./run.sh` command with `Ctrl+C`. Move on to the next section to set up a simple web server using the runner.
    diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md
    index cc1b201f40..5a637ee637 100644
    --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md
    +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md
    @@ -6,13 +6,13 @@ weight: 3
     layout: learningpathall
     ---
     
    -## Introduction
    +## Overview
     
    -This section walks you through creating a **Google Axion C4A Arm virtual machine** on Google Cloud with the **c4a-standard-4 (4 vCPUs, 16 GB memory)** machine type using the **Google Cloud Console**. You will use this VM later as the host for a GitHub Actions self-hosted runner.
    +This section walks you through creating a Google Axion C4A Arm virtual machine on Google Cloud with the `c4a-standard-4` (4 vCPUs, 16 GB memory) machine type using the Google Cloud Console. You will use this VM later as the host for a GitHub Actions self-hosted runner.
     
     If you don't have a Google Cloud account, see the Learning Path [Getting started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/).
     
    -### Create an Arm-based virtual machine (C4A)
    +## Create an Arm-based virtual machine (C4A)
     
     Follow these steps in the Google Cloud Console:
     
    @@ -26,7 +26,7 @@ Follow these steps in the Google Cloud Console:
     - Under **Networking**, enable **Allow HTTP traffic** so you can test workloads like NGINX later.
     - Select **Create** to launch the instance.
     
    -![Google Cloud Console page showing C4A VM creation with c4a-standard-4 selected](./images/select-instance.png "Create a C4A VM in the Google Cloud Console")
    +![Google Cloud Console page showing C4A VM creation with c4a-standard-4 selectedalt-text#center](./images/select-instance.png "Create a C4A VM in the Google Cloud Console")
     
     {{% notice Important %}}
     Do not leave **Allow HTTP traffic** enabled permanently. For long-term use, allow traffic only from the IP addresses you use to connect to the instance.
    
    From 4a422d39cb1a40bd1fea303029a0b8c7134aeca0 Mon Sep 17 00:00:00 2001
    From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
    Date: Fri, 5 Sep 2025 15:42:28 +0000
    Subject: [PATCH 16/31] Content dev
    
    ---
     .../github-on-arm/deploy.md                   | 110 ++----------------
     1 file changed, 11 insertions(+), 99 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/deploy.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/deploy.md
    index b275f2b2ca..8814e55903 100644
    --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/deploy.md
    +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/deploy.md
    @@ -8,7 +8,7 @@ layout: learningpathall
     
     ## Overview
     
    -This section showsyou how to deploy a GitHub Actions self-hosted runner on your Arm64 Google Axion C4A instance. You will install Git and GitHub CLI, authenticate with GitHub, and register the runner so CI/CD workflows run on Arm infrastructure.
    +This section shows you how to deploy a GitHub Actions self-hosted runner on your Arm64 Google Axion C4A instance. You will install Git and GitHub CLI, authenticate with GitHub, and register the runner so CI/CD workflows run on Arm infrastructure.
     
     ## Set up your development environment
     
    @@ -34,11 +34,11 @@ Authenticate with GitHub:
     gh auth login
     ```
     
    -Follow the prompts and accept the defaults.
    +Follow the prompts and accept the defaults:
     
     ![Login to GitHub alt-text#center](./images/gh-auth.png "Screenshot of GitHub authentication prompt")
     
    -{{% notice %}}
    +{{% notice Note %}}
     If you get an error opening the browser on your virtual machine, you can navigate to the following URL on the host machine and enter the device code displayed in the CLI of the virtual machine: 
     ```
     https://github.com/login/device
    @@ -51,7 +51,7 @@ When authentication succeeds, you will see a confirmation screen in your browser
     
     ## Test GitHub CLI and Git
     
    -The command below creates a new public GitHub repository named **test-repo** using the GitHub CLI. It sets the repository visibility to public, meaning that anyone can view it:
    +The command below creates a new public GitHub repository named `test-repo` using the GitHub CLI. It sets the repository visibility to public, meaning that anyone can view it:
     
     ```console
     gh repo create test-repo --public
    @@ -71,15 +71,14 @@ You should see an output similar to:
       If the **Actions** tab is not visible, enable Actions under **Settings** → **Actions** → **General** by selecting **Allow all actions and reusable workflows**.
       {{% /notice %}}
     
    -  ![runner](./images/newsh-runner.png)
    +  ![runner alt-text#center](./images/newsh-runner.png "Screenshot of repository Runners settings page")
     
    -  Then, click on the **New self-hosted runner** button. In the **Add new self-hosted runner** section. Select Linux for the operating system, and choose ARM64 for the architecture. This will generate commands to set up the runner. Copy and run them on your Google Axion C4A virtual machine.
    +  Click **New self-hosted runner**. In the setup panel, choose `Linux` as the operating system and `ARM64` as the architecture. Copy the generated setup commands and run them on your C4A VM.
    +  
    +  ![new-runner alt-text#center](./images/new-runner.png "Screenshot of the Add new self-hosted runner panel")
     
    -  ![new-runner](./images/new-runner.png)
    -
    -  The final command links the runner to your GitHub repo using a one-time registration token.
    -
    -  During the command’s execution, you will be prompted to provide the runner group, the name of the runner, and the work folder name. You can accept the defaults by pressing **Enter** at each step. The output will resemble as below:
    +  The final command links the runner to your GitHub repository using a one-time registration token.
    +  During setup, you will be prompted for the runner group, runner name, and work folder. Press **Enter** at each prompt to accept the defaults. The output should look similar to:
     
       ```output
       --------------------------------------------------------------------------------
    @@ -119,94 +118,7 @@ You should see an output similar to:
       ```
       The runner will now be visible in the GitHub actions:
     
    -  ![final-runner](./images/final-runner.png)
    +  ![final-runner alt-text#center](./images/final-runner.png "Screenshot of runner visible in GitHub")
     
       For now, you can terminate the `./run.sh` command with `Ctrl+C`. Move on to the next section to set up a simple web server using the runner.
    -](./images/gh-auth.png)
    -
    -{{% notice %}}
    -If you get an error opening the browser on your virtual machine, you can navigate to the following URL on the host machine.
    -```
    -https://github.com/login/device
    -```
    -From there, you can enter the code displayed in the CLI of the virtual machine.
    -{{% /notice %}}
    -
    -If the log in was successful, you will see the following confirmation in your browser window.
    -
    -![GitHub UI](./images/login-page.png)
    -
    -### Test GitHub CLI and Git
    -
    -The command below creates a new public GitHub repository named **test-repo** using the GitHub CLI. It sets the repository visibility to public, meaning anyone can view it
    -
    -```console
    -gh repo create test-repo --public
    -```
    -You should see an output similar to:
    -```output
    -✓ Created repository /test-repo on GitHub
    -  https://github.com//test-repo
    -  ```
    -
    -
    -  ### Configure the Self-Hosted Runner
    -
    -  * Go to your repository's **Settings > Actions**, and under the **Runners** section
    -  * Click on **Add Runner** or view existing self-hosted runners.
    -
    -  {{% notice Note %}}
    -  If the **Actions** tab is not visible, ensure Actions are enabled by navigating to **Settings > Actions > General**, and select **Allow all actions and reusable workflows**.
    -  {{% /notice %}}
    -
    -  ![runner](./images/newsh-runner.png)
     
    -  Then, click on the **New self-hosted runner** button. In the **Add new self-hosted runner** section. Select Linux for the operating system, and choose ARM64 for the architecture. This will generate commands to set up the runner. Copy and run them on your Google Axion C4A virtual machine.
    -
    -  ![new-runner](./images/new-runner.png)
    -
    -  The final command links the runner to your GitHub repo using a one-time registration token.
    -
    -  During the command’s execution, you will be prompted to provide the runner group, the name of the runner, and the work folder name. You can accept the defaults by pressing **Enter** at each step. The output will resemble as below:
    -
    -  ```output
    -  --------------------------------------------------------------------------------
    -  |        ____ _ _   _   _       _          _        _   _                      |
    -  |       / ___(_) |_| | | |_   _| |__      / \   ___| |_(_) ___  _ __  ___      |
    -  |      | |  _| | __| |_| | | | | '_ \    / _ \ / __| __| |/ _ \| '_ \/ __|     |
    -  |      | |_| | | |_|  _  | |_| | |_) |  / ___ \ (__| |_| | (_) | | | \__ \     |
    -  |       \____|_|\__|_| |_|\__,_|_.__/  /_/   \_\___|\__|_|\___/|_| |_|___/     |
    -  |                                                                              |
    -  |                       Self-hosted runner registration                        |
    -  |                                                                              |
    -  --------------------------------------------------------------------------------
    -
    -  # Authentication
    -
    -  √ Connected to GitHub
    -  # Runner Registration
    -  Enter the name of the runner group to add this runner to: [press Enter for Default]
    -  Enter the name of runner: [press Enter for lpprojectubuntuarm64]
    -  This runner will have the following labels: 'self-hosted', 'Linux', 'ARM64'
    -  Enter any additional labels (ex. label-1,label-2): [press Enter to skip]
    -  √ Runner successfully added
    -  √ Runner connection is good
    -  ```
    -
    -  Finally, start the runner by executing:
    -  ```console
    -  ./run.sh
    -  ```
    -  You should see an output similar to:
    -
    -  ```output
    -  √ Connected to GitHub
    -
    -  Current runner version: '2.326.0'
    -  2025-07-15 05:51:13Z: Listening for Jobs
    -  ```
    -  The runner will now be visible in the GitHub actions:
    -
    -  ![final-runner](./images/final-runner.png)
    -
    -  For now, you can terminate the `./run.sh` command with `Ctrl+C`. Move on to the next section to set up a simple web server using the runner.
    
    From afb93759b595fb54622fea34e99c2b6c496aa53b Mon Sep 17 00:00:00 2001
    From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
    Date: Fri, 5 Sep 2025 16:05:22 +0000
    Subject: [PATCH 17/31] Final tweaks
    
    ---
     .../github-on-arm/instance.md                 |  6 +++---
     .../github-on-arm/nginx-deployment.md         | 19 ++++++++++---------
     2 files changed, 13 insertions(+), 12 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md
    index 5a637ee637..753d92cbca 100644
    --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md
    +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/instance.md
    @@ -19,9 +19,9 @@ Follow these steps in the Google Cloud Console:
     - Open the [Google Cloud Console](https://console.cloud.google.com/).
     - Go to **Navigation menu ▸ Compute Engine ▸ VM instances**, then select **Create instance**.
     - Under **Machine configuration**:
    -  - Enter **Instance name**, **Region**, and **Zone**.
    -  - Set **Series** to `C4A`.
    -  - Choose a machine type such as `c4a-standard-4`.
    +  - Enter **Instance name**, **Region**, and **Zone**
    +  - Set **Series** to `C4A`
    +  - Choose a machine type such as `c4a-standard-4`
     - Under **OS and storage**, select **Change**, pick **Ubuntu** as the operating system, and choose **Ubuntu 24.04 LTS Minimal**. Make sure you select the Arm image variant.
     - Under **Networking**, enable **Allow HTTP traffic** so you can test workloads like NGINX later.
     - Select **Create** to launch the instance.
    diff --git a/content/learning-paths/servers-and-cloud-computing/github-on-arm/nginx-deployment.md b/content/learning-paths/servers-and-cloud-computing/github-on-arm/nginx-deployment.md
    index 8569893dfc..bd0b3c28ad 100644
    --- a/content/learning-paths/servers-and-cloud-computing/github-on-arm/nginx-deployment.md
    +++ b/content/learning-paths/servers-and-cloud-computing/github-on-arm/nginx-deployment.md
    @@ -1,29 +1,30 @@
     ---
    -title: Deploy NGINX the GitHub Runner
    +title: Deploy NGINX with the GitHub runner
     weight: 5
     
     ### FIXED, DO NOT MODIFY
     layout: learningpathall
     ---
     
    +## Overview
     
     This workflow installs and starts a basic NGINX web server on a self-hosted runner whenever code is pushed to the main branch.
     
    -In your instance's console, create a directory for the repository:
    +In your instance console, create a directory for the repository:
     
     ```console
     mkdir test-repo && cd test-repo
     echo "# test-repo" >> README.md
     ```
     
    -Then, create the GitHub Actions workflow file at `.github/workflows/deploy-nginx.yaml`.
    +Create the GitHub Actions workflow file at `.github/workflows/deploy-nginx.yaml`:
     
     ```console
     mkdir .github  && mkdir .github/workflows/
     vim .github/workflows/deploy-nginx.yaml
     ```
     
    -Paste the following code block into the file and save it.
    +Paste the following content into the file:
     
     ```yaml
     name: Deploy NGINX
    @@ -45,7 +46,7 @@ jobs:
             run: sudo systemctl start nginx
     ```
     
    -Now it's time to initiate your repository and push the changes.
    +Initialize your repository and push the changes:
     
     ```console
     git init
    @@ -63,15 +64,15 @@ cd ..
     ./run.sh
     ```
     
    -You will see in the output of the command that it identifies the a job called `deploy`, and that it finishes after having run the two steps.
    +The output shows a job called `deploy` and confirms that both steps ran successfully.
     
    -### Access the NGINX Server
    +## Access the NGINX server
     Once the workflow completes, open your browser and navigate to your machine's external IP address. You will find the information in your instance overview, under **Network interfaces**.
     ```
     http://
     ```
     You should see the NGINX welcome page confirming a successful deployment.
     
    -![nginx](./images/nginx.png)
    +![nginx alt-text#center](./images/nginx.png "Screenshot of the NGINX welcome page in a browser")
     
    -You should now know how to set up a self-hosted runner with an Arm-based Google Cloud instance, and use it to run GitHub Actions workflows. From here, you can modify the workflow file to try out different commands.
    +You now know how to set up a self-hosted runner with an Arm-based Google Cloud instance, and use it to run GitHub Actions workflows. From here, you can modify the workflow file to try out different commands.
    
    From 1998ca59d8ae2c6245a93763bae53f6c67759af8 Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Fri, 5 Sep 2025 19:19:30 -0400
    Subject: [PATCH 18/31] Update _index.md
    
    ---
     .../servers-and-cloud-computing/envoy-gcp/_index.md           | 4 ++++
     1 file changed, 4 insertions(+)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md
    index 81bb86d21e..710d54fcf6 100644
    --- a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md
    +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md
    @@ -1,5 +1,9 @@
     ---
     title: Deploy Envoy on Google Axion processors
    +
    +draft: true
    +cascade:
    +    draft: true
        
     minutes_to_complete: 30
     
    
    From 6be58c3f1181db76d21a76bc57acde8a2a5feba3 Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Mon, 8 Sep 2025 09:13:13 -0400
    Subject: [PATCH 19/31] Update .wordlist.txt
    
    ---
     .wordlist.txt | 36 ++++++++++++++++++++++++++++++++++++
     1 file changed, 36 insertions(+)
    
    diff --git a/.wordlist.txt b/.wordlist.txt
    index 22e016cbb0..b78c36b0ee 100644
    --- a/.wordlist.txt
    +++ b/.wordlist.txt
    @@ -4666,5 +4666,41 @@ crosh
     Sommelier
     chromeos
     linuxcontainers
    +XPS
    +NIC's 
    +offlines
    +passthrough
    +SLOs
    +Ker
    +Rui
    +SmartNICs
    +selectedalt
    +UIalt
    +lpprojectubuntuarm
    +RDV
    +chiplet
    +BMC
    +upstreams
    +rdv
    +Initrd
    +handoff
    +ACPI
    +PCRs
    +MHU
    +Handoff
    +userland
    +CXL
    +DDR
    +PHYs
    +UCIe
    +handoffs
    +CCG
    +CML
    +Codespaces
    +Cheng
    +GDM
    +LPI
    +nsec
    +shortcode
     
     
    
    From 64b95538e417bc34546c90330dbb2c280af52109 Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Mon, 8 Sep 2025 13:14:30 +0000
    Subject: [PATCH 20/31] typo fixes
    
    ---
     .../_example-learning-path/appendix-1-formatting.md             | 2 +-
     1 file changed, 1 insertion(+), 1 deletion(-)
    
    diff --git a/content/learning-paths/cross-platform/_example-learning-path/appendix-1-formatting.md b/content/learning-paths/cross-platform/_example-learning-path/appendix-1-formatting.md
    index 8a310fc356..f5a43c2979 100644
    --- a/content/learning-paths/cross-platform/_example-learning-path/appendix-1-formatting.md
    +++ b/content/learning-paths/cross-platform/_example-learning-path/appendix-1-formatting.md
    @@ -114,7 +114,7 @@ There are three ways you can specify command outputs in code:
     {{% notice Note %}}
     In each of the three situations, code marked as 'output' will:
     - not be copied when clicking the 'copy' button
    -- not be highlightable by a cursor
    +- not be highlighted by a cursor
     - appear slightly darker
     {{% /notice %}}
     
    
    From 37859eda0678a8ef52efcf3eae340c075564100d Mon Sep 17 00:00:00 2001
    From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
    Date: Mon, 8 Sep 2025 13:15:02 +0000
    Subject: [PATCH 21/31] Content development review
    
    ---
     .../mongodb-on-gcp/_index.md                  | 16 +++----
     .../mongodb-on-gcp/background.md              |  9 ++--
     .../mongodb-on-gcp/baseline-testing.md        | 36 ++++++++-------
     .../mongodb-on-gcp/benchmarking.md            | 46 ++++++++++---------
     .../mongodb-on-gcp/create-instance.md         | 33 ++++++-------
     .../mongodb-on-gcp/mongodb-deploy.md          | 44 +++++++++---------
     6 files changed, 93 insertions(+), 91 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/_index.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/_index.md
    index 78c9482bfc..27a3011c93 100644
    --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/_index.md
    +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/_index.md
    @@ -1,21 +1,17 @@
     ---
    -title: Deploy MongoDB on Google Axion C4A virtual machine
    +title: Deploy MongoDB on an Arm-based Google Axion C4A VM
     
     minutes_to_complete: 15
     
    -draft: true
    -cascade:
    -    draft: true
    -
    -who_is_this_for: This is an introductory topic for software developers looking to migrate their MongoDB workloads from x86_64 to Arm-based platforms, specifically on Google Axion-based C4A virtual machines.
    +who_is_this_for: This introductory topic is for software developers who want to migrate MongoDB workloads from x86_64 to Arm-based platforms, specifically on Google Axion-based C4A virtual machines.
     
     learning_objectives:
    -       - Create an Arm cloud instance on the Google Cloud Platform
    -       - Install and run MongoDB on the Arm-based GCP C4A instance.
    -       - Benchmark the MongoDB performance on Arm using Yahoo Cloud Serving Benchmark (YCSB).
    +  - Create an Arm virtual machine on Google Cloud (C4A Axion family)
    +  - Install and run MongoDB on the Arm-based C4A instance
    +  - Benchmark MongoDB performance with Yahoo Cloud Serving Benchmark (YCSB)
     
     prerequisites:
    -     - A [Google Cloud Platform (GCP)](https://cloud.google.com/free?utm_source=google&hl=en) account with billing enabled.
    +     - A [Google Cloud Platform (GCP)](https://cloud.google.com/free?utm_source=google&hl=en) account with billing enabled
     
     author: Annie Tallund
     
    diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md
    index a576e38b4f..51543abfce 100644
    --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md
    +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md
    @@ -8,15 +8,14 @@ layout: "learningpathall"
     
     ## Google Axion C4A series
     
    -The C4A series is a family of Arm-based instance types for Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high-performance and energy-efficient computing, these virtual machine offer strong performance suitable for modern cloud workloads such as CI/CD pipelines, microservices, media processing, and general-purpose applications.
    +The C4A series is a family of Arm-based instance types for Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high performance and energy-efficient computing, these virtual machine offer strong performance suitable for modern cloud workloads such as CI/CD pipelines, microservices, media processing, and general-purpose applications.
     
     The C4A series provides a cost-effective virtual machine while leveraging the scalability and performance benefits of the Arm architecture in Google Cloud.
     
    -To learn more about Google Axion, refer to the blog [Introducing Google Axion Processors, our new Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu).
    +To learn more about Google Axion, see the blog post [Introducing Google Axion Processors, our new Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu).
     
     ## MongoDB
    -MongoDB is a popular open-source NoSQL database designed for high performance, scalability, and flexibility.
     
    -It stores data in JSON-like BSON documents, making it ideal for modern applications that require dynamic, schema-less data structures.
    +MongoDB is a popular open-source NoSQL database designed for performance, scalability, and flexibility. It stores data in JSON-like BSON documents, making it well suited to applications that require dynamic, schema-less data models.
     
    -MongoDB is widely used for web, mobile, IoT, and real-time analytics workloads. Learn more from the [MongoDB official website](https://www.mongodb.com/) and its [official documentation](https://www.mongodb.com/docs/).
    +MongoDB is widely used for web, mobile, IoT, and real-time analytics workloads. Learn more on the [MongoDB website](https://www.mongodb.com/) and in the [official documentation](https://www.mongodb.com/docs/).
    diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md
    index 6d558c9688..c41d519372 100644
    --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md
    +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md
    @@ -6,17 +6,17 @@ weight: 5
     layout: learningpathall
     ---
     
    -Now that MongoDB is successfully installed on your GCP C4A Arm virtual machine, follow these steps to verify that the server is running correctly and accepting local connections.
    +Now that MongoDB is installed on your Google Axion C4A Arm VM, verify that the server is running and accepting local connections.
     
    -### 1. Connect to MongoDB
    +## Connect to MongoDB
     
     Open a shell session to the local MongoDB instance:
     
     ```console
     mongosh mongodb://127.0.0.1:27017
    -```
     
    -### 2. Create a Test Database and Collection
    +
    +## Create a test database and collection
     
     Switch to a new database and create a collection:
     
    @@ -34,7 +34,7 @@ switched to db baselineDB
     { ok: 1 }
     ```
     
    -### 3. Insert 10,000 Test Documents
    +## Insert 10,000 test documents
     
     Populate the collection with 10,000 timestamped documents:
     
    @@ -48,9 +48,9 @@ for (let i = 0; i < 10000; i++) {
     }
     ```
     
    -Each document will contain:
    +Each document contains:
     - `record`: a counter from 0 to 9999
    -- `status`: always `"new"`
    +- `status`: `"new"`
     - `timestamp`: the current date/time of insertion
     
     Sample output:
    @@ -59,7 +59,7 @@ Sample output:
     { acknowledged: true, insertedId: ObjectId('...') }
     ```
     
    -### 4. Read a Subset of Documents
    +## Read a subset of documents
     
     Verify read functionality by querying the first few documents:
     
    @@ -69,7 +69,7 @@ db.test.find({ status: "new" }).limit(5)
     
     This returns the first 5 documents where `status` is `"new"`.
     
    -### 5. Update a Document
    +## Update a document
     
     Update a specific document by changing its status:
     
    @@ -89,7 +89,7 @@ Expected output:
     }
     ```
     
    -### 6. View the Updated Document
    +## View the updated document
     
     Confirm that the document was updated:
     
    @@ -108,7 +108,7 @@ Expected output:
     }
     ```
     
    -### 7. Delete a Document
    +## Delete a document
     
     The command below tells MongoDB to delete one document from the test collection, where record is exactly 100:
     
    @@ -116,7 +116,7 @@ The command below tells MongoDB to delete one document from the test collection,
     db.test.deleteOne({ record: 100 })
     ```
     
    -Verify that it was deleted:
    +Verify deletion:
     
     ```javascript
     db.test.findOne({ record: 100 })
    @@ -128,7 +128,7 @@ Expected output:
     null
     ```
     
    -### 8. Measure Execution Time (Optional)
    +## Measure execution time (optional)
     
     Measure how long it takes to insert 10,000 documents:
     
    @@ -146,7 +146,7 @@ Sample output:
     Insert duration (ms): 4427
     ```
     
    -### 9. Count Total Documents
    +## Count total documents
     
     Check the total number of documents in the collection:
     
    @@ -163,9 +163,11 @@ Expected output:
     The count **19999** reflects the total documents after inserting 10,000 initial records, adding 10,000 more (in point 8), and deleting one (record: 100).
     
     
    -### 10. Clean Up (Optional)
    +## Clean up (optional)
    +
    +For the sake of resetting the environment, this following command deletes the current database you are connected to in mongosh. 
     
    -For the sake of resetting the environment, this following command deletes the current database you are connected to in mongosh. Drop the `baselineDB` database to remove all test data:
    +Drop the `baselineDB` database to remove all test data:
     
     ```javascript
     db.dropDatabase()
    @@ -177,4 +179,4 @@ Expected output:
     { ok: 1, dropped: 'baselineDB' }
     ```
     
    -These baseline operations confirm that MongoDB is functioning properly on your GCP Arm64 environment. Using `mongosh`, you validated key database capabilities including **inserts**, **queries**, **updates**, **deletes**, and **performance metrics**. Your instance is now ready for benchmarking or application integration.
    \ No newline at end of file
    +These baseline operations confirm that MongoDB is functioning properly on your GCP Arm64 environment. Using `mongosh`, you validated inserts, queries, updates, deletes, and basic performance timing. Your instance is now ready for benchmarking or application integration.
    \ No newline at end of file
    diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/benchmarking.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/benchmarking.md
    index fcbe8fd10e..eff06a9a06 100644
    --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/benchmarking.md
    +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/benchmarking.md
    @@ -5,36 +5,36 @@ weight: 6
     ### FIXED, DO NOT MODIFY
     layout: learningpathall
     ---
    -## MongoDB Benchmarking with YCSB (Yahoo! Cloud Serving Benchmark)
     
    -**YCSB (Yahoo! Cloud Serving Benchmark)** is an open-source tool for evaluating the performance of NoSQL databases under various workloads. It simulates operations such as reads, writes, updates, and scans to mimic real-world usage patterns.
    +## Benchmark MongoDB with YCSB
     
    -### Install YCSB (Build from Source)
    +YCSB (Yahoo! Cloud Serving Benchmark) is an open-source tool for evaluating NoSQL databases under various workloads. It simulates operations such as writes, updates, and scans to mimic production traffic.
     
    -First, install the required build tools and clone the YCSB repository:
    +## Install YCSB from source
    +
    +Install build tools and clone YCSB, then build the MongoDB binding:
     
     ```console
     sudo dnf install -y git maven java-11-openjdk-devel
     git clone https://github.com/brianfrankcooper/YCSB.git
     cd YCSB
     mvn -pl site.ycsb:mongodb-binding -am clean package
    -```
     
    -### Load Phase – Insert Initial Dataset
     
    -This phase inserts a set of documents into MongoDB to simulate a typical starting workload. By default, it inserts 1,000 records.
    +## Load initial data 
     
    +Load a starter dataset (defaults to 1,000 records) into MongoDB:
     ```console
     ./bin/ycsb load mongodb -s \
       -P workloads/workloada \
       -p mongodb.url=mongodb://127.0.0.1:27017/ycsb
     ```
     
    -This prepares the database for the actual performance test.
    +This prepares the database for the performance test.
     
    -### Execute Benchmark Workload
    +## Run a mixed workload
     
    -Run the actual benchmark with the predefined workload. This command performs mixed read/write operations and collects performance metrics.
    +Run Workload A (50% reads, 50% updates) and collect metrics:
     
     ```console
     ./bin/ycsb run mongodb -s \
    @@ -48,7 +48,7 @@ Run the actual benchmark with the predefined workload. This command performs mix
     
     This simulates common real-world applications like session stores or shopping carts.
     
    -You’ll see performance output that looks like this:
    +Sample output:
     
     ```output
     [READ], Operations, 534
    @@ -65,19 +65,19 @@ You’ll see performance output that looks like this:
     [OVERALL], Throughput(ops/sec), 1953.125
     ```
     
    -### YCSB Operations & Latency Metrics Explained
    +## Understand YCSB metrics
     
    -- **Operations Count**: Total operations performed for each type (e.g., READ, UPDATE).
    +- **Operations Count**: Total operations performed for each type (for example, READ, UPDATE).
     - **Average Latency (us)**: The average time to complete each operation, measured in microseconds.
     - **Min Latency / Max Latency (us)**: The fastest and slowest observed times for any single operation of that type.
     
     With YCSB installed and benchmark results captured, you now have a baseline for MongoDB's performance under mixed workloads.
     
    -### Benchmark summary on x86_64
    +## Benchmark summary on x86_64
     
     To better understand how MongoDB behaves across architectures, YCSB benchmark workloads were run on both an **x86_64 (C3 Standard)** and an **Arm64 (C4A Standard)** virtual machine, each with 4 vCPUs and 16 GB of memory, running RHEL 9.
     
    -The following  benchmark results are collected on a c3-standard-4 (4 vCPU, 2 core, 16 GB Memory) x86_64 environment, running RHEL 9.
    +Results from a c3-standard-4 instance (4 vCPUs, 16 GB RAM) on RHEL 9:
     
     | Operation | Count | Avg Latency (us) | Min Latency (us) | Max Latency (us) | 50th Percentile (us) | 95th Percentile (us) | 99th Percentile (us) |
     |-----------|-------|------------------|------------------|------------------|-----------------------|----------------------|-----------------------|
    @@ -85,8 +85,8 @@ The following  benchmark results are collected on a c3-standard-4 (4 vCPU, 2 cor
     | UPDATE    | 528   | 621.27           | 214              | 12855            | 554                   | 971                  | 1224                  |
     | CLEANUP   | 1     | 4702             | 4700             | 4703             | 4703                  | 4703                 | 4703                  |
     
    -### Benchmark summary on Arm64:
    -The following  benchmark results are collected on a c4a-standard-4 (4 vCPU, 16 GB Memory) Arm64 environment, running RHEL 9.
    +## Benchmark summary on Arm64 (Google Axion C4A):
    +Results from a c4a-standard-4 instance (4 vCPUs, 16 GB RAM) on RHEL 9:
     
     | Operation | Count | Avg Latency (us) | Min Latency (us) | Max Latency (us) | 50th Percentile (us) | 95th Percentile (us) | 99th Percentile (us) |
     |----------|------------------|------------------|------------------|------------------|----------------------|----------------------|----------------------|
    @@ -94,10 +94,12 @@ The following  benchmark results are collected on a c4a-standard-4 (4 vCPU, 16 G
     | UPDATE    |               466 |           384.45  |               186 |             26543 |                   296 |                   498 |                   821 |
     | CLEANUP   |                 1 |          4138     |              4136 |              4139 |                  4139 |                  4139 |                  4139 |
     
    -### **Highlights from GCP C4A Arm virtual machine**
    +## Highlights from the C4A Arm VM
    +
    +- Lower average latencies on Arm: ~313 µs (READ) and ~384 µs (UPDATE).
    +
    +- Stable p50–p99 latencies indicate consistent performance.
     
    -- Arm results show low **average latencies**, **READ** at **313 us** and **UPDATE** at **384 us**.
    -- **50th** to **99th percentile** latencies remain stable, indicating consistent performance.
    -- **Max latency** spikes (**8279 us READ**, **26543 us UPDATE**) suggest rare outliers.
    +- Occasional max-latency outliers suggest transient spikes common in mixed workloads.
     
    -This Learning Path walked you through setting up and benchmarking MongoDB on an Arm-based GCP instance, highlighting how to run core operations, validate performance, and interpret benchmarking results with YCSB. Alongside, you explored some performance numbers, showing that Arm is a powerful and cost-efficient alternative for modern data-serving workloads like MongoDB.
    \ No newline at end of file
    +With YCSB built and results captured, you now have a baseline for MongoDB performance on Arm-based Google Axion C4A. You can iterate on dataset size, thread counts, and workloads (A–F) to profile additional scenarios and compare cost-performance across architectures.
    \ No newline at end of file
    diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md
    index f54706f908..1ab2d3735e 100644
    --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md
    +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md
    @@ -8,26 +8,27 @@ layout: learningpathall
     
     ## Introduction
     
    -This section walks you through creating a **Google Axion C4A Arm virtual machine** on GCP with the **c4a-standard-4 (4 vCPUs, 16 GB Memory)** machine type, using the **Google Cloud Console**.
    +This section walks you through creating a Google Axion C4A Arm virtual machine on GCP with the `c4a-standard-4` (4 vCPUs, 16 GB Memory) machine type, using the **Google Cloud Console**.
     
    -If you haven't set up a Google Cloud account, check out the Learning Path on [Getting Started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/).
    +If you haven't set up a Google Cloud account, see the Learning Path [Getting started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/).
     
    -### Create an Arm-based Virtual Machine (C4A)
    +## Create an Arm-based virtual machine (C4A)
     
    -To create a virtual machine based on the C4A Arm architecture:
    -1. Navigate to the [Google Cloud Console](https://console.cloud.google.com/).
    -2. Go to **Compute Engine** and click on **Create Instance**.
    -3. Under the **Machine Configuration**:
    -      - Fill in basic details like **Instance Name**, **Region**, and **Zone**.
    -      - Select the **Series** as `C4A`.
    -      - Choose a machine type such as `c4a-standard-4`.
    -![Instance Screenshot](./select-instance.png)
    -4. Under the **OS and Storage**, click on **Change**, and select **Red Hat Enterprise Linux** as the Operating System with **Red Hat Enterprise Linux 9** as the Version. Make sure you pick the version of image for Arm.
    -5. Under **Networking**, enable **Allow HTTP traffic** to allow interacting for later steps in the Learning Path.
    -6. Click on **Create**, and the instance will launch.
    +To create a VM based on the C4A Arm architecture:
    +
    +1. Open the [Google Cloud Console](https://console.cloud.google.com/).
    +2. Go to **Compute Engine** and select **Create instance**.
    +3. In **Machine configuration**:
    +   - Enter the **Instance name**, **Region**, and **Zone**.
    +   - Set **Series** to `C4A`.
    +   - Choose a machine type such as `c4a-standard-4`.  
    +     ![Screenshot of GCP Create instance page showing C4A series and c4a-standard-4 selected](./select-instance.png "Select the C4A series and c4a-standard-4 machine type")
    +4. In **OS and storage**, select **Change**, choose **Red Hat Enterprise Linux** as the operating system and **Red Hat Enterprise Linux 9** as the version. Make sure you select the **Arm** image.
    +5. In **Networking**, enable **Allow HTTP traffic** so you can test services later in this Learning Path.
    +6. Select **Create** to launch the instance.
     
     {{% notice Important %}}
    -Avoid enabling Allow HTTP traffic permanently, as it introduces a security vulnerability. Instead, configure access to allow only your own IP address for long-term use.
    +Do not leave **Allow HTTP traffic** enabled permanently. For long-term use, restrict access to only the IP addresses you need.
     {{% /notice %}}
     
    -To access the Google Cloud Console, click the SSH button in your instance overview. This will open a command line interface (CLI), which you’ll use to run the remaining commands in this Learning Path. Continue to the next section to set up MongoDB on your instance.
    \ No newline at end of file
    +To open a shell on the VM, select **SSH** in the instance details page. Use this terminal for the commands in the next sections, where you will install and configure MongoDB on your Axion C4A instance.
    diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md
    index 6d41947389..6d752a7013 100644
    --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md
    +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md
    @@ -6,20 +6,22 @@ weight: 4
     layout: learningpathall
     ---
     
    -In this section, you’ll install MongoDB and the MongoDB Shell (`mongosh`) by downloading the necessary binaries, configuring your environment, and verifying that the database server is running correctly.
    +## Overview
     
    -### 1. Install System Dependencies
    +This section shows how to install MongoDB and the MongoDB Shell (`mongosh`) on an Arm-based Google Axion C4A instance running Red Hat Enterprise Linux. You will download the Arm64 binaries, update your environment, and verify that the database server runs correctly.
     
    -Start by installing required system packages to support MongoDB:
    +## Install system dependencies
    +
    +Install the required system packages:
     
     ```console
    -sudo dnf update
    +sudo dnf update -y
     sudo dnf install -y libcurl openssl tar wget curl
    -```
     
    -### 2. Download and Extract MongoDB
     
    -Next, fetch and unpack the MongoDB binaries for Arm:
    +Download and extract MongoDB
    +
    +Fetch and unpack the MongoDB Arm64 (aarch64) binaries for RHEL 9.3:
     
     ```console
     wget https://fastdl.mongodb.org/linux/mongodb-linux-aarch64-rhel93-8.0.12.tgz
    @@ -27,31 +29,31 @@ tar -xzf mongodb-linux-aarch64-rhel93-8.0.12.tgz
     ls mongodb-linux-aarch64-rhel93-8.0.12/bin
     ```
     
    -To make MongoDB binaries accessible from any terminal session, add them to your PATH:
    +Add the binaries to your `PATH` so they are available in every shell session:
     
     ```console
     echo 'export PATH=~/mongodb-linux-aarch64-rhel93-8.0.12/bin:$PATH' >> ~/.bashrc
     source ~/.bashrc
     ```
     
    -### 3. Start the MongoDB server
    +## Start the MongoDB server
     
     
     
    -Set up a directory to store MongoDB's data files:
    +Create a data directory for MongoDB files:
     
     ```console
     mkdir -p ~/mongodb-data/db
     ```
    -Run MongoDB in the **foreground** to verify it starts correctly:
    +Start mongod in the foreground to verify that it launches and to view logs directly:
     
     ```console
     mongod --dbpath ~/mongodb-data/db
     ```
     
    -Starting the server in the **foreground** allows you to see real-time logs and is useful for debugging or verifying that MongoDB starts correctly. However, this will occupy your terminal and stop the server if you close the terminal or interrupt it.
    +Starting the server in the foreground allows you to see real-time logs and is useful for debugging or verifying that MongoDB starts correctly. However, this will occupy your terminal and stop the server if you close the terminal or interrupt it.
     
    -After stopping the server (e.g., with `Ctrl+C`), confirm that files have been created in the database directory:
    +Stop the server (for example, with **Ctrl+C**), then confirm that data files were created:
     
     ```console
     ls ~/mongodb-data/db/
    @@ -63,31 +65,31 @@ Example output:
     collection-0-7680310461694759627.wt  index-3-7680310461694759627.wt  mongod.lock      WiredTiger.lock
     ```
     
    -Once you’ve confirmed it’s working, you can start MongoDB in the **background** using the `--fork` option and redirecting logs to a file. This allows MongoDB to run continuously without tying up your terminal session. To start MongoDB in the **background** with logging enabled:
    +Once you’ve confirmed it’s working, you can start MongoDB in the background using the `--fork` option and redirecting logs to a file. This allows MongoDB to run continuously without tying up your terminal session. 
    +
    +Start mongod in the background with logging enabled so it continues to run after you close the terminal:
     
     ```console
     mongod --dbpath ~/mongodb-data/db --logpath ~/mongodb-data/mongod.log --fork
     ```
     
    +## Install MongoDB Shell (mongosh)
     
    -### 4. Install mongosh
    -
    -`mongosh` is the MongoDB shell used to interact with your database. Download and install it for Arm:
    +`mongosh` is the MongoDB shell used to interact with your database. Download and install mongosh for Arm64:
     
     ```console
     wget https://github.com/mongodb-js/mongosh/releases/download/v2.5.6/mongodb-mongosh-2.5.6.aarch64.rpm
     sudo dnf install -y ./mongodb-mongosh-2.5.6.aarch64.rpm
     ```
     
    -Confirm that`mongosh` was installed correctly by checking that the version is printed:
    -
    +Verify the installation:
     ```console
     mongosh --version
     ```
     
    -### 5. Connect to MongoDB via mongosh
    +## Connect to MongoDB with mongosh
     
    -Finally, connect to your MongoDB server using the shell:
    +Connect to the local server:
     
     ```console
     mongosh mongodb://127.0.0.1:27017
    
    From f972632bf179a3e7b6d372dbc9ff12e1966f3866 Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Mon, 8 Sep 2025 13:16:06 +0000
    Subject: [PATCH 22/31] Type fixes
    
    ---
     .../servers-and-cloud-computing/neoverse-rdv3-swstack/_index.md | 2 +-
     1 file changed, 1 insertion(+), 1 deletion(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/neoverse-rdv3-swstack/_index.md b/content/learning-paths/servers-and-cloud-computing/neoverse-rdv3-swstack/_index.md
    index 170db4c0df..473bd2f67e 100644
    --- a/content/learning-paths/servers-and-cloud-computing/neoverse-rdv3-swstack/_index.md
    +++ b/content/learning-paths/servers-and-cloud-computing/neoverse-rdv3-swstack/_index.md
    @@ -34,7 +34,7 @@ tools_software_languages:
         - C
         - Docker
         - FVP
    -peratingsystems:
    +operatingsystems:
         - Linux
     
     further_reading:
    
    From 74e74cfac3f69026235115251e2a95b748ca1b61 Mon Sep 17 00:00:00 2001
    From: Maddy Underwood <167196745+madeline-underwood@users.noreply.github.com>
    Date: Mon, 8 Sep 2025 13:52:15 +0000
    Subject: [PATCH 23/31] Tweaks
    
    ---
     .../mongodb-on-gcp/background.md                            | 2 +-
     .../mongodb-on-gcp/baseline-testing.md                      | 5 +++++
     .../mongodb-on-gcp/create-instance.md                       | 6 +++---
     .../mongodb-on-gcp/mongodb-deploy.md                        | 2 +-
     4 files changed, 10 insertions(+), 5 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md
    index 51543abfce..e3c0cbb163 100644
    --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md
    +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/background.md
    @@ -18,4 +18,4 @@ To learn more about Google Axion, see the blog post [Introducing Google Axion Pr
     
     MongoDB is a popular open-source NoSQL database designed for performance, scalability, and flexibility. It stores data in JSON-like BSON documents, making it well suited to applications that require dynamic, schema-less data models.
     
    -MongoDB is widely used for web, mobile, IoT, and real-time analytics workloads. Learn more on the [MongoDB website](https://www.mongodb.com/) and in the [official documentation](https://www.mongodb.com/docs/).
    +MongoDB is widely used for web, mobile, IoT, and real-time analytics workloads. Learn more on the [MongoDB website](https://www.mongodb.com/) and in the [MongoDB documentation](https://www.mongodb.com/docs/).
    diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md
    index c41d519372..4e99c74930 100644
    --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md
    +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/baseline-testing.md
    @@ -6,14 +6,19 @@ weight: 5
     layout: learningpathall
     ---
     
    +## Overview
    +
     Now that MongoDB is installed on your Google Axion C4A Arm VM, verify that the server is running and accepting local connections.
     
    +Use mongosh to create a test database, run basic CRUD operations, and capture a quick insert-time baseline before you start benchmarking.
    +
     ## Connect to MongoDB
     
     Open a shell session to the local MongoDB instance:
     
     ```console
     mongosh mongodb://127.0.0.1:27017
    +```
     
     
     ## Create a test database and collection
    diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md
    index 1ab2d3735e..33af64d5a6 100644
    --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md
    +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/create-instance.md
    @@ -6,7 +6,7 @@ weight: 3
     layout: learningpathall
     ---
     
    -## Introduction
    +## Overview
     
     This section walks you through creating a Google Axion C4A Arm virtual machine on GCP with the `c4a-standard-4` (4 vCPUs, 16 GB Memory) machine type, using the **Google Cloud Console**.
     
    @@ -22,8 +22,8 @@ To create a VM based on the C4A Arm architecture:
        - Enter the **Instance name**, **Region**, and **Zone**.
        - Set **Series** to `C4A`.
        - Choose a machine type such as `c4a-standard-4`.  
    -     ![Screenshot of GCP Create instance page showing C4A series and c4a-standard-4 selected](./select-instance.png "Select the C4A series and c4a-standard-4 machine type")
    -4. In **OS and storage**, select **Change**, choose **Red Hat Enterprise Linux** as the operating system and **Red Hat Enterprise Linux 9** as the version. Make sure you select the **Arm** image.
    +     ![Screenshot of GCP Create instance page showing C4A series and c4a-standard-4 selected alt-text#center](./select-instance.png "Selecting the C4A series and c4a-standard-4 machine type")
    +4. In **OS and storage**, select **Change**, choose **Red Hat Enterprise Linux** as the operating system, and **Red Hat Enterprise Linux 9** as the version. Make sure you select the **Arm** image.
     5. In **Networking**, enable **Allow HTTP traffic** so you can test services later in this Learning Path.
     6. Select **Create** to launch the instance.
     
    diff --git a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md
    index 6d752a7013..d2799361f1 100644
    --- a/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md
    +++ b/content/learning-paths/servers-and-cloud-computing/mongodb-on-gcp/mongodb-deploy.md
    @@ -8,7 +8,7 @@ layout: learningpathall
     
     ## Overview
     
    -This section shows how to install MongoDB and the MongoDB Shell (`mongosh`) on an Arm-based Google Axion C4A instance running Red Hat Enterprise Linux. You will download the Arm64 binaries, update your environment, and verify that the database server runs correctly.
    +This section shows you how to install MongoDB and the MongoDB Shell (`mongosh`) on an Arm-based Google Axion C4A instance running Red Hat Enterprise Linux. You will download the Arm64 binaries, update your environment, and verify that the database server runs correctly.
     
     ## Install system dependencies
     
    
    From f4da3c0411867c73f019dece6d56e0c76fa51e2d Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Mon, 8 Sep 2025 17:30:00 +0000
    Subject: [PATCH 24/31] Tech review of Envoy LP
    
    ---
     .../envoy-gcp/_index.md                       |    4 +-
     .../envoy-gcp/baseline-testing.md             |   22 +-
     .../envoy-gcp/benchmarking.md                 | 1042 +----------------
     .../envoy-gcp/deploy.md                       |   13 +-
     .../envoy-gcp/instance.md                     |    6 +-
     5 files changed, 36 insertions(+), 1051 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md
    index 710d54fcf6..75351eaac2 100644
    --- a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md
    +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/_index.md
    @@ -7,10 +7,10 @@ cascade:
        
     minutes_to_complete: 30
     
    -who_is_this_for: This introductory topic is for software developers interested in migrating their Envoy workloads from x86_64 platforms to Arm-based platforms, specifically on Google Axion–based C4A virtual machines.  
    +who_is_this_for: This is an introductory topic is for software developers interested in migrating their Envoy workloads from x86_64 servers to Arm-based servers, specifically on Google Axion–based C4A virtual machines.  
     
     learning_objectives:
    -  - Start an Arm virtual machine on Google Cloud Platform (GCP) using the C4A Google Axion instance family with RHEL 9 as the base image
    +  - Start an Arm virtual machine on Google Cloud Platform (GCP) using the C4A Google Axion instance 
       - Install and configure Envoy on Arm-based GCP C4A instances
       - Validate Envoy functionality through baseline testing
       - Benchmark Envoy performance on Arm
    diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/baseline-testing.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/baseline-testing.md
    index 16b53ba8c6..ec16a99ec4 100644
    --- a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/baseline-testing.md
    +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/baseline-testing.md
    @@ -7,16 +7,16 @@ layout: learningpathall
     ---
     
     
    -Since Envoy is installed successfully on your GCP C4A Arm virtual machine, follow these steps to validate that the Envoy is running.
    +With Envoy installed successfully on your GCP C4A Arm virtual machine, you will proceed to validate that the Envoy is running as expected.
     
     ## Validate Envoy installation with a baseline test
     
    -In this section, we covered how to create a minimal Envoy config, start Envoy with it, and verify functionality using `curl`. 
    -The test confirmed that Envoy listens on port **10000**, forwards requests to `httpbin.org`, and returns a successful **200 OK** response.
    +In this section, you will learn how to create a minimal Envoy config, start Envoy with it, and verify functionality using `curl`. 
    +The test will confirm that Envoy listens on port **10000**, forwards requests to `httpbin.org`, and returns a successful **200 OK** response.
     
     ### Create a Minimal Configuration File
     
    -Using a file editor of your choice, create a file named `envoy_config.yaml`, and add the below content to it. This file configures Envoy to listen on port **10000** and forward all traffic to `http://httpbin.org`. The host_rewrite_literal is essential to prevent 404 Not Found errors from the upstream server.
    +Using a file editor of your choice, create a file named `envoy_config.yaml`, and add the below content to it. This file configures Envoy to listen on port **10000** and forward all traffic to `http://httpbin.org`. The `host_rewrite_literal` is essential to prevent 404 Not Found errors from the upstream server.
     
     ```YAML
     static_resources:
    @@ -72,7 +72,7 @@ static_resources:
     ### Run and Test Envoy
     
     This is the final phase of functional validation, confirming that the proxy is operational.
    -Start the Envoy proxy using your configuration file. This command will keep the terminal occupied, so you will need a new terminal for the next step.
    +Start the Envoy proxy using your configuration file as shown on your current terminal:
     
     ```console
      envoy -c envoy_config.yaml --base-id 1
    @@ -90,12 +90,12 @@ The output should look similar to:
     [2025-08-21 11:53:51.599][67137][info][config] [source/common/listener_manager/listener_manager_impl.cc:930] all dependencies initialized. starting workers
     ```
     
    -Now, **Send a test request** from another terminal window to the Envoy listener using `curl`.
    +Now, open a new terminal and send a test request to the Envoy listener using `curl`.
     
     ```console
     curl -v http://localhost:10000/get
     ```
    -The `-v` flag provides verbose output, showing the full request and response headers. A successful test will show a **HTTP/1.1 200 OK** response with a JSON body from httpbin.org.
    +The `-v` flag provides verbose output, showing the full request and response headers. A successful test will show a **HTTP/1.1 200 OK** response with a JSON body from `httpbin.org`.
     
     The output should look similar to:
     
    @@ -133,9 +133,9 @@ The output should look similar to:
     ```
     #### Summary of the curl Output
     
    -- **Successful Connection:** The **curl** command successfully connected to the Envoy proxy on **localhost:10000**.
    -- **Correct Status Code:** Envoy successfully forwarded the request and received a healthy **200 OK** response from the upstream server.
    -- **Host Header Rewrite:** The **Host** header was correctly rewritten from **localhost:10000** to **httpbin.org** as defined in the configuration.
    +- **Successful Connection:** The `curl` command successfully connected to the Envoy proxy on `localhost:10000`.
    +- **Correct Status Code:** Envoy successfully forwarded the request and received a successful `200 OK` response from the upstream server.
    +- **Host Header Rewrite:** The Host header was correctly modified from `localhost:10000` to `httpbin.org` as defined in the configuration.
     - **End-to-End Success:** The proxy is fully operational, proving that requests are correctly received, processed, and forwarded to the intended backend.
     
    -This confirms the end-to-end flow is working correctly.
    +This confirms the end-to-end flow with Envoy server is working correctly.
    diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md
    index 530ee5ce12..e74e355e36 100644
    --- a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md
    +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md
    @@ -8,9 +8,10 @@ layout: learningpathall
     
     ## How to run Envoy benchmarks with Siege on Arm64 in GCP
     
    -**Siege** is a lightweight HTTP load testing and benchmarking tool that simulates concurrent users making requests to a target service. It is useful for **Envoy benchmarking** because it measures availability, throughput, response time, and failure rates under load—helping evaluate Envoy’s performance as a proxy under real-world traffic conditions.
    +**Siege** is a lightweight HTTP load testing and benchmarking tool that simulates concurrent users making requests to a target service. It is useful for Envoy benchmarking because it measures availability, throughput, response time, and failure rates under load, thus helping evaluate Envoy’s performance as a proxy under real-world traffic conditions.
    +
    +Follow the steps outlined to run Envoy benchmarks using Siege.
     
    -Follow the steps outlined to run Envoy benchmarks using the Siege.
     ### Install Siege(Build from Source)
     
     1. Install required build tools
    @@ -29,7 +30,7 @@ cd siege-4.1.6
     make
     sudo make install
     ```
    -These commands prepare Siege for your system, build (compile) it, and then install it so you can run it from anywhere.
    +You have now successfully built and installed Seige on your Arm-based machine.
     
     3. Verify installation
     
    @@ -47,16 +48,15 @@ FOR A PARTICULAR PURPOSE.
     ```
     ### Envoy Benchmarking
     
    -1. Ensure Envoy is Running
    +1. To start, make sure Envoy is up and running with your config file (listening on port 10000):
     
    -To make sure your Envoy proxy is up with your config file (listening on port 10000 for example):
     
     ```console
     envoy -c envoy_config.yaml --base-id 1
     ```
     This runs the Envoy proxy with your configuration file (envoy_config.yaml) so it can start listening for requests.
     
    -2. Verify with curl from the another terminal:
    +2. On another terminal, verify that envoy is running as expected with curl:
     
     ```
     curl -v http://127.0.0.1:10000/get
    @@ -65,1030 +65,16 @@ Running from another terminal returns a **200 OK** status, confirming that Envoy
     
     3. Run a Time-based Load Test
     
    -Benchmark for a fixed time instead of request count:
    +There are different ways you can setup your benchmark tests. Here you will run a Benchmark for a fixed time instead of using request count:
     
     ```console
     siege -c30 -t10S http://127.0.0.1:10000/get
     ```
     This runs a load test where 30 users hit Envoy continuously for 10 seconds. After this, Siege will show performance results.
     
    -The output should look similar to:
    +The output should show a list of HTTP requests and responses followed by a summary as shown:
     
     ```output
    -** SIEGE 4.1.6
    -** Preparing 30 concurrent users for battle.
    -The server is now under siege...
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.06 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.06 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.06 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.09 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.06 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.09 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.16 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.10 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.47 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.40 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.46 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.86 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.92 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 502     0.07 secs:     122 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.77 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.05 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.32 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.21 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     1.34 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.91 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.17 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.05 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.05 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.19 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.05 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.09 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.06 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.48 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.07 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.08 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.47 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.39 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.05 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     1.05 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     1.17 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.48 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.74 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.32 secs:     383 bytes ==> GET  /get
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    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.24 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.14 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.69 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     2.35 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.83 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.67 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.55 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.60 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.73 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.07 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.28 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.28 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.08 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.56 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.73 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.07 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.39 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.53 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.33 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.12 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.78 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.57 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.61 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.08 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.49 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.90 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.05 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.13 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.02 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.26 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.45 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.20 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.08 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.98 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.53 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     2.10 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.27 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     2.45 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.74 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.46 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.31 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.39 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.48 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.99 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.26 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.53 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.12 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.02 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.80 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.67 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.37 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.07 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.26 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.21 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.38 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.53 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.20 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.64 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     2.89 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.20 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.04 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     1.05 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.08 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.64 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.46 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.81 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.51 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.61 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.35 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.91 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.35 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.91 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.05 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.53 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.51 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    -HTTP/1.1 200     0.37 secs:     383 bytes ==> GET  /get
     HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
     HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
     HTTP/1.1 200     0.03 secs:     383 bytes ==> GET  /get
    @@ -1131,7 +117,7 @@ Shortest transaction:           0.02
     - **Shortest Transaction**: Minimum response time observed for a single request.
     
     ### Benchmark summary on x86_64:
    -The following benchmark results were collected by running the same benchmark on a c3-standard-4 (4 vCPU, 2 core, 16 GB Memory) x86_64 virtual machine in GCP, running RHEL 9.
    +To compare the benchmark results, the following results were collected by running the same benchmark on a `c3-standard-4` (4 vCPU, 2 core, 16 GB Memory) x86_64 virtual machine in GCP, running RHEL 9.
     
     | Metric                 | Value        | Metric                   | Value           |
     |-------------------------|--------------|---------------------------|-----------------|
    @@ -1155,9 +141,9 @@ Results from the earlier run on the c4a-standard-4 (4 vCPU, 16 GB memory) Arm64
     | Longest transaction     | 2.89 secs     | Shortest transaction      | 0.02 secs       |
     
     ### Envoy performance benchmarking comparison on Arm64 and x86_64
    -When you compare the benchmarking results you will notice that on the Google Axion C4A Arm-based instances:
    +When you compare the benchmarking performance results between the two instance types with the same vCPUs, you will notice that on the Google Axion C4A Arm-based instances:
    +
    +- You have more successful transactions, fewer failures.
    +- Lower response times, higher transaction rate, better throughput.
     
    -- Achieved **1019 successful transactions** with only **2 failures**, ensuring **99.80%** availability.
    -- Delivered a strong **transaction rate of 98.17 trans/sec** and throughput of **0.04 MB/sec**.
    -- Maintained low **response times (0.29 secs average)**, with a shortest transaction of **0.02 secs**.
    -- Demonstrated **stable concurrency handling (28.07)** and controlled latency, with the longest transaction completing in **2.89 secs.**
    +You have successfully learned how to use Siege to benchmark Envoy on your Arm-based Axion Google cloud instance, validating both performance and reliability against similar x86 instances.
    diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/deploy.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/deploy.md
    index 72adb14d9f..b932b53b36 100644
    --- a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/deploy.md
    +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/deploy.md
    @@ -8,7 +8,7 @@ layout: learningpathall
     
     
     ## How to deploy Envoy on a Google Axion C4A Arm virtual machine
    -This guide shows you how to install Envoy Proxy v1.30.0 on a Google Cloud Axion C4A virtual machine running RHEL 9. You’ll install the basic tools, download the official static Arm64 Envoy binary, give it executable permissions, and check the version. By the end, Envoy will be installed and ready to use on your GCP virtual machine — without needing Docker or building from source.
    +In this section you will learn how to install Envoy Proxy v1.30.0 on a Google Cloud Axion C4A virtual machine running RHEL 9. You will install the dependencies, download the official static Arm64 Envoy binary and check the installed version. 
     
     1. Install Dependencies
     
    @@ -27,7 +27,7 @@ pip3 install virtualenv
     
     2. Install Envoy (Static Arm64 Binary)
     
    -This step downloads and installs the Envoy binary.
    +You will now download and install the Envoy binary on your Arm-based instance.
     Download the binary directly to **/usr/local/bin/envoy**. The `-L` flag is crucial as it follows any redirects from the download URL.
     
     ```console
    @@ -35,7 +35,7 @@ sudo curl -L \
       -o /usr/local/bin/envoy \
       https://github.com/envoyproxy/envoy/releases/download/v1.30.0/envoy-1.30.0-linux-aarch_64
     ```
    -Make it executable so the system can run the binary as a command.
    +Change the permissions on the downloaded binary to make it an executable:
     
     ```console
     sudo chmod +x /usr/local/bin/envoy
    @@ -47,11 +47,10 @@ envoy --version
     ```
     This confirms the binary is correctly placed and executable.
     
    -You should see an output similar to:
    +The output should look like:
     
     ```output
     envoy  version: 50ea83e602d5da162df89fd5798301e22f5540cf/1.30.0/Clean/RELEASE/BoringSSL
     ```
    -This confirms the binary is correctly placed and executable.
    -
    -Envoy installation is complete. You can now proceed with the baseline testing ahead.
    +This confirms the installation of Envoy.
    +You can now proceed with the baseline testing in the next section.
    diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/instance.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/instance.md
    index aa39cf2bf1..87db47d57e 100644
    --- a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/instance.md
    +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/instance.md
    @@ -8,13 +8,13 @@ layout: learningpathall
     
     ## How to create a Google Axion C4A Arm VM on Google Cloud
     
    -In this section, you learn how to provision a **Google Axion C4A Arm virtual machine** on Google Cloud Platform (GCP) using the **c4a-standard-4 (4 vCPUs, 16 GB memory)** machine type in the **Google Cloud Console**.  
    +In this section, you will learn how to provision a Google Axion C4A Arm virtual machine on Google Cloud Platform (GCP) using the **c4a-standard-4 (4 vCPUs, 16 GB memory)** machine type in the Google Cloud Console.  
     
    -For background on GCP setup, see the Learning Path [Getting started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/).
    +For details on GCP setup, refer to the [Getting started with Google Cloud Platform](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/google/) Learning Path.
     
     ### Create a Google Axion C4A Arm VM in Google Cloud Console
     
    -To create a virtual machine based on the C4A Arm architecture:
    +To create a virtual machine based on the C4A instance type:
     1. Navigate to the [Google Cloud Console](https://console.cloud.google.com/).
     2. Go to **Compute Engine > VM Instances** and select **Create Instance**. 
     3. Under **Machine configuration**:
    
    From fa7caae2da03c730a2c2ce75ddbce13f2cb33205 Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Mon, 8 Sep 2025 17:47:05 +0000
    Subject: [PATCH 25/31] Moving FP learning path to draft until Google feedback
     is addressed
    
    ---
     .../cross-platform/floating-point-rounding-errors/_index.md   | 4 ++++
     1 file changed, 4 insertions(+)
    
    diff --git a/content/learning-paths/cross-platform/floating-point-rounding-errors/_index.md b/content/learning-paths/cross-platform/floating-point-rounding-errors/_index.md
    index 9c5431b21f..923b028e69 100644
    --- a/content/learning-paths/cross-platform/floating-point-rounding-errors/_index.md
    +++ b/content/learning-paths/cross-platform/floating-point-rounding-errors/_index.md
    @@ -1,6 +1,10 @@
     ---
     title: Explore floating-point differences between x86 and Arm
     
    +draft: true
    +cascade:
    +    draft: true
    +
     minutes_to_complete: 30
     
     who_is_this_for: This is an introductory topic for developers who are porting applications from x86 to Arm and want to understand how floating-point behavior differs between these architectures - particularly in the context of numerical consistency, performance, and debugging subtle bugs.
    
    From 6e48b239d359dc4d062a04df150ee40aec84f7a3 Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Mon, 8 Sep 2025 14:44:21 -0400
    Subject: [PATCH 26/31] Update benchmarking.md
    
    ---
     .../servers-and-cloud-computing/envoy-gcp/benchmarking.md       | 2 +-
     1 file changed, 1 insertion(+), 1 deletion(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md
    index e74e355e36..bb9675b17d 100644
    --- a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md
    +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/benchmarking.md
    @@ -61,7 +61,7 @@ This runs the Envoy proxy with your configuration file (envoy_config.yaml) so it
     ```
     curl -v http://127.0.0.1:10000/get
     ```
    -Running from another terminal returns a **200 OK** status, confirming that Envoy is running and successfully proxying requests.
    +Running from another terminal returns a **200 OK** status, confirming that Envoy is running and successfully processing requests.
     
     3. Run a Time-based Load Test
     
    
    From c76faebace9f3079cfe3a6ec0f17083b61b33d95 Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Mon, 8 Sep 2025 14:44:54 -0400
    Subject: [PATCH 27/31] Update background.md
    
    ---
     .../servers-and-cloud-computing/envoy-gcp/background.md         | 2 +-
     1 file changed, 1 insertion(+), 1 deletion(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/background.md b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/background.md
    index 97dafae372..633ea96aa0 100644
    --- a/content/learning-paths/servers-and-cloud-computing/envoy-gcp/background.md
    +++ b/content/learning-paths/servers-and-cloud-computing/envoy-gcp/background.md
    @@ -14,7 +14,7 @@ The C4A series provides a cost-effective alternative to x86 virtual machines whi
     
     To learn more about Google Axion, refer to the [Introducing Google Axion Processors, our new Arm-based CPUs](https://cloud.google.com/blog/products/compute/introducing-googles-new-arm-based-cpu) blog.
     
    -## Envoy for service proxying and traffic management on Arm
    +## Envoy for service proxy and traffic management on Arm
     
     Envoy is an open-source, high-performance edge and service proxy designed for cloud-native applications.
     
    
    From 455bc458ec54748c736c32ab07df8e6934dc592c Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Mon, 8 Sep 2025 14:47:41 -0400
    Subject: [PATCH 28/31] Update flow.md
    
    ---
     .../servers-and-cloud-computing/cca-trustee/flow.md             | 2 +-
     1 file changed, 1 insertion(+), 1 deletion(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/cca-trustee/flow.md b/content/learning-paths/servers-and-cloud-computing/cca-trustee/flow.md
    index 49f06e54db..63c5b033a7 100644
    --- a/content/learning-paths/servers-and-cloud-computing/cca-trustee/flow.md
    +++ b/content/learning-paths/servers-and-cloud-computing/cca-trustee/flow.md
    @@ -199,7 +199,7 @@ Using JWK key from JWT header
     Error: verifying signed EAR from "ear.jwt" using "JWK header" key: failed verifying JWT message: jwt.Parse: failed to parse token: jwt.Validate: validation failed: "exp" not satisfied: token is expired
     ```
     
    -Please obtain a new EAR message by re-runing the attestation command.
    +Please obtain a new EAR message by re-running the attestation command.
     {{% /notice %}}
     
     
    
    From 378e1bfd8940ff2453abfd310cf3922648d979bb Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Mon, 8 Sep 2025 14:48:20 -0400
    Subject: [PATCH 29/31] Update cca-trustee.md
    
    ---
     .../servers-and-cloud-computing/cca-trustee/cca-trustee.md      | 2 +-
     1 file changed, 1 insertion(+), 1 deletion(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/cca-trustee/cca-trustee.md b/content/learning-paths/servers-and-cloud-computing/cca-trustee/cca-trustee.md
    index 428f0677d0..884f89e6ae 100644
    --- a/content/learning-paths/servers-and-cloud-computing/cca-trustee/cca-trustee.md
    +++ b/content/learning-paths/servers-and-cloud-computing/cca-trustee/cca-trustee.md
    @@ -86,7 +86,7 @@ A verifier driver parses the attestation evidence provided by the hardware TEE.
     1. Verifies the hardware TEE signature of the TEE quote and report provided in the evidence
     2. Receives the evidence and organizes the status into a JSON format to be returned
     
    -In this Learning Path, the AS is configured to use an external CCA verifer.
    +In this Learning Path, the AS is configured to use an external CCA verifier.
     
     [Linaro](https://www.linaro.org) provides such an attestation verifier for use with pre-silicon Arm CCA platforms.
     This verifier is built from the Open-Source [Veraison project](https://github.com/veraison).
    
    From 6c25d004063e28a93f8e335b0594ad31d43066f8 Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Mon, 8 Sep 2025 14:49:11 -0400
    Subject: [PATCH 30/31] Update cca-trustee.md
    
    ---
     .../servers-and-cloud-computing/cca-trustee/cca-trustee.md    | 4 ++--
     1 file changed, 2 insertions(+), 2 deletions(-)
    
    diff --git a/content/learning-paths/servers-and-cloud-computing/cca-trustee/cca-trustee.md b/content/learning-paths/servers-and-cloud-computing/cca-trustee/cca-trustee.md
    index 884f89e6ae..0eded26191 100644
    --- a/content/learning-paths/servers-and-cloud-computing/cca-trustee/cca-trustee.md
    +++ b/content/learning-paths/servers-and-cloud-computing/cca-trustee/cca-trustee.md
    @@ -138,8 +138,8 @@ FVP and the reference software stack, see the
     Learning Path.
     
     When the AS receives an attestation token from the realm via KBS:
    -- it calls an external CCA verifer (the Linaro attestation verifier service) to obtain an attestation result.
    -- the external CCA verifer checks the token's cryptographic signature,
    +- it calls an external CCA verifier (the Linaro attestation verifier service) to obtain an attestation result.
    +- the external CCA verifier checks the token's cryptographic signature,
       verifies that it denotes a confidential computing platform and provides an attestation result.
     - it also checks the token evidences against its own attestation policies and updates attestation result status and trustworthiness vectors.
     
    
    From 324815cf286bd15eaa3315e65d8ce0a9f2fd620d Mon Sep 17 00:00:00 2001
    From: pareenaverma 
    Date: Mon, 8 Sep 2025 14:52:10 -0400
    Subject: [PATCH 31/31] Update .wordlist.txt
    
    ---
     .wordlist.txt | 21 ++++++++++++++++++++-
     1 file changed, 20 insertions(+), 1 deletion(-)
    
    diff --git a/.wordlist.txt b/.wordlist.txt
    index b78c36b0ee..306ba0bdeb 100644
    --- a/.wordlist.txt
    +++ b/.wordlist.txt
    @@ -4702,5 +4702,24 @@ GDM
     LPI
     nsec
     shortcode
    -
    +BSON
    +joedog
    +Seige
    +Antonov
    +jwt
    +kbs
    +Nfpl
    +ZjnAMjLk
    +hCpeYsarnnGv
    +kbs
    +rvps
    +xcbTMTBX
    +CDH
    +RVPS
    +Attester
    +attester
    +ATtestation
    +CoCo
    +procedureS
    +NIC’s