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This project demonstrates how a third party solution, like Datadog, can be used to monitor a Kubernetes Engine cluster and its workloads. Using the provided manifest, you will install Datadog and a simple nginx workload into your cluster. The Datadog agents will be configured to monitor the nginx workload, and ship metrics to your own Datadog ac…
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README.md

README.md

Kubernetes Engine Datadog Monitoring POC

Table of Contents

Introduction

A common goal of cloud computing is to abstract away operational tasks from applications so that developer efforts can be focused on providing business value. One feature common to most applications is the need to monitor application and hardware metrics. On Google Cloud Platform (GCP) the Stackdriver suite of products addresses the need for monitoring and alerting. Some companies may already have a third party solution, however, and this project demonstrates configuring the use of Datadog in a Kubernetes Engine environment. We show you how to collect nginx metrics and pipe them to your existing Datadog account.

This demo contains a simple deployment script for Kubernetes Engine using personal accounts and Terraform. There is one manifest that deploys the Datadog agents and nginx.

NOTE: Personal account should never be used in a CI/CD pipeline. Provision a service account with all permissions needed to run this when automated.

Architecture

There is a single Kubernetes Engine cluster with 2 nodes. The datadog-agent.yaml manifest creates a DaemonSet that runs the Datadog agent on each node in the cluster. Alongside the Datadog agents are nginx processes that feed metrics to Datadog.

Prerequisites

Run Demo in a Google Cloud Shell

Click the button below to run the demo in a Google Cloud Shell.

Open in Cloud Shell

All the tools for the demo are installed. When using Cloud Shell execute the following command in order to setup gcloud cli. When executing this command please setup your region and zone.

gcloud init

Run Demo in a SSH Terminal

Tools

  1. Terraform >= 0.11.7
  2. Google Cloud SDK version >= 204.0.0
  3. kubectl matching the latest GKE version
  4. Apache Bench

The specific versions used may not be absolutely required but if you run into issues this may help.

Install Cloud SDK

The Google Cloud SDK is used to interact with your GCP resources. Installation instructions for multiple platforms are available online.

Install kubectl CLI

The kubectl CLI is used to interteract with both Kubernetes Engine and kubernetes in general. Installation instructions for multiple platforms are available online.

Install Terraform

Terraform is used to automate the manipulation of cloud infrastructure. Its installation instructions are also available online.

Install Apache Bench

For many users this won't be necessary as many operating systems have Apache Bench pre-installed. However it is contained within the apache2-utils package for Ubuntu/Debian users, and the httpd-tools package for CentOS/Redhat users.

Configure Authentication

Use gcloud auth login <your.account@example.com> --no-launch-browser to get a link to log in your gcloud cli to your personal account.

Deployment

Set up Datadog

  1. Create a free account on Datadog or use an existing one.
  2. Login to the DatadogHQ site and go to Agent Installation to display the text for the Datadog agent Kubernetes manifest. Scroll down until you see DD_API_KEY. Copy the value and paste it into manifests/datadog-agent.yaml at the same key.
  3. In DatadogHQ site go to "Integrations" -> Type "nginx" in the search bar -> Click on the "NGINX" Tile -> "Configuration" Tab -> "Install Integration" -- NGINX dashboards will now be available in the "Dashboards List"

Set up Kubernetes Engine Cluster Using Terraform and Deploy Services

 make create

Validation

  1. Log into your Datadog account.
  2. Go to the Dashboards page.
  3. You will see two pre-built Nginx dashboards that contain metrics for the nginx containers.
  4. Click on NGINX - Metrics.
  5. From a terminal execute EXT_IP=http://$(kubectl get svc nginx -n default -ojsonpath='{.status.loadBalancer.ingress[0].ip}/'); echo $EXT_IP. - If it displays a valid url with an IP address the service is deployed and ready to use. You can access the provided address in a browser to verify that nginx is handling requests.
  6. Run ab -n 1000 $EXT_IP - This will run a load test against nginx and generate metrics that will be forwarded to Datadog.
  7. In a few moments you should see data coming into your Datadog dashboard.

Tear Down

Run cd terraform to get back to the Terraform directory and run terraform destroy to remove all resources created by this demo.

Troubleshooting

** No data is displaying in Datadog **

  • Make sure you grabbed the DD_API_KEY value from the generated datadog-agent.yaml from the Datadog site. It is generated for you for your specific account.

** Terraform fails due to issues with zone or project **

  • Make sure your gcloud config has values for core/project and compute/zone.
gcloud config set core/project <YOUR PROJECT>
gcloud config set compute/zone <THE ZONE YOU WANT>

** The install script fails with a Permission denied when running Terraform **

  • The credentials that Terraform is using do not provide the necessary permissions to create resources in the selected projects. Ensure that the account listed in gcloud config list has necessary permissions to create resources. If it does, regenerate the application default credentials using gcloud auth application-default login.

Relevant Material

You can find additional information at the following locations

This is not an officially supported Google product

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