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Stackdriver Sandbox is an open source tool that helps practitioners to learn Service Reliability Engineering practices from Google and apply them on their cloud services using Stackdriver.
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Stackdriver Sandbox (Alpha)

Stackdriver Sandbox is an open-source tool that helps practitioners to learn Service Reliability Engineering practices from Google and apply them on their cloud services using Stackdriver. It is based on Hipster Shop, a cloud-native microservices application.

Sandbox offers:

  • Demo Service - an application built using microservices architecture on modern, cloud-native stack.
  • One-click deployment - a script handles the work of deploying the service to Google Cloud Platform.
  • Load Generator - a component that produces synthetic traffic on a demo service.
  • (Soon) SRE Runbook - pre-built routine procedures for operating the deployed sample service that follow best SRE practices using Stackdriver.

Why Sandbox

Google Stackdriver is a suite of tools that helps you gain full observability of your code and applications. You might want to take Stackdriver to a "test drive" in order to answer the question, "will it work for my application needs"? The most effective way to learn is by testing the tool in "real-life" conditions, but without risking a production system. With Sandbox, we provide a tool that automatically provisions a new demo cluster, which receives traffic, simulating real users. Practicioners can experiment with various Stackdriver tools to solve problems and accomplish standard SRE tasks in a sandboxed environment.

Getting Started

Using Sandbox


Set Up

  1. Click the Cloud Shell button for automated one-click installation of a new Stackdriver Sandbox cluster in a new Google Cloud Project.

Open in Cloud Shell

  1. In the Cloud Shell command prompt, type:

Next Steps

Clean Up

When you are done using Stackdriver Sandbox, you can tear down the environment by deleting the GCP project that was set up for you. This can be accomplished in any of the following ways:

  • Use the Stackdriver Sandbox destroy script:
  • If you no longer have the Stackdriver Sandbox files downloaded, delete your project manually using gcloud
gcloud projects delete $YOUR_PROJECT_ID

Service Overview

This project contains a 10-tier microservices application. It is a web-based e-commerce app called “Hipster Shop”, where users can browse items, add them to the cart, and purchase them.


Home Page Checkout Screen
Screenshot of store homepage Screenshot of checkout screen

Service Architecture

Hipster Shop is composed of many microservices, written in different languages, that talk to each other over gRPC.

We are not endorsing the architecture of Hipster Shop as the best way to build such a shop! The architecture is optimized for learning purposes and includes modern stack: Kubernetes, GKE, Istio, Stackdriver, gRPC, OpenCensus, and similar cloud-native technologies.

Architecture of microservices

Find the Protocol Buffers Descriptions in the ./pb directory.

Service Language Description
frontend Go Exposes an HTTP server to serve the website. Does not require signup/login, and generates session IDs for all users automatically.
cartservice C# Manages the items in the user's shipping cart by using Redis.
productcatalogservice Go Provides the list of products from a JSON file and the ability to search and retrieve products.
currencyservice Node.js Converts one currency to another, using real values fetched from the European Central Bank. It's the highest QPS service.
paymentservice Node.js Charges the given credit card info (hypothetically😇) with the given amount and returns a transaction ID.
shippingservice Go Gives shipping-cost estimates based on the shopping cart. Ships items to the given address (hypothetically😇).
emailservice Python Sends users an order-confirmation email (hypothetically😇).
checkoutservice Go Retrieves a user's cart, prepares the order, and orchestrates payment, shipping, and email notification.
recommendationservice Python Recommends other products based on what's in the user's cart.
adservice Java Provides text ads based on given context words.
loadgenerator Python/Locust Continuously sends requests that imitate realistic shopping flows to the frontend.


  • Kubernetes/GKE: The app is designed to run on Google Kubernetes Engine.
  • gRPC: Microservices use a high volume of gRPC calls to communicate to each other.
  • OpenCensus Tracing: Most services are instrumented using OpenCensus trace interceptors for gRPC/HTTP.
  • Stackdriver APM: Many services are instrumented with Profiling, Tracing and Debugging. Metrics and Context Graph out of the box.
  • Skaffold: A tool used for doing repeatable deployments. You can deploy to Kubernetes with a single command using Skaffold.
  • Synthetic Load Generation: The application demo comes with dedicated load generation service that creates realistic usage patterns on Hipster Shop website using Locust load generator.

For Developers

Note: The first build can take up to 30 minutes. Subsequent builds will be faster.

Option 1: Running locally with “Docker for Desktop”

💡 Recommended if you're planning to develop the application.

  1. Install tools to run a Kubernetes cluster locally:

    • kubectl (can be installed via gcloud components install kubectl)
    • Docker for Desktop (Mac/Windows): It provides Kubernetes support as noted here.
    • skaffold (ensure version ≥v0.20)
  2. Launch “Docker for Desktop”. Go to Preferences:

    • Choose Enable Kubernetes
    • Set CPUs to at least 3
    • Set Memory to at least 6.0 GiB
  3. Run kubectl get nodes to verify you're connected to “Kubernetes on Docker”.

  4. Run skaffold run (first time will be slow; it can take up to 30 minutes). This will build and deploy the application. If you need to rebuild the images automatically as you refactor he code, run the skaffold dev command.

  5. Run kubectl get pods to verify the Pods are ready and running. The application frontend should be available at http://localhost:80 on your machine.

Option 2: Running on Google Kubernetes Engine (GKE)

💡 Recommended for demos and making it available publicly.

  1. Install tools specified in the previous section (Docker, kubectl, skaffold)

  2. Create a Google Kubernetes Engine cluster and make sure kubectl is pointing to the cluster:

     gcloud services enable
     gcloud container clusters create demo --enable-autoupgrade \
         --enable-autoscaling --min-nodes=3 --max-nodes=10 --num-nodes=5 --zone=us-central1-a
     kubectl get nodes
  3. Enable Google Container Registry (GCR) on your GCP project and configure the docker CLI to authenticate to GCR:

    gcloud services enable
    gcloud auth configure-docker -q
  4. In the root of this repository, run skaffold run[PROJECT_ID], where [PROJECT_ID] is the identifier for your GCP project.

    This command:

    • Builds the container images.
    • Pushes them to GCR.
    • Applies the ./kubernetes-manifests deploying the application to Kubernetes.

    Troubleshooting: If you get the error "No space left on device" on Google Cloud Shell, you can build the images on Google Cloud Build. To do this:

    1. Enable the Cloud Build API.

    2. Run skaffold run -p gcb[PROJECT_ID].

  5. Find the IP address of your application, then visit the application on your browser to confirm installation.

     kubectl get service frontend-external

    Troubleshooting: A Kubernetes bug (will be fixed in 1.12) combined with a Skaffold bug causes the load balancer to not work, even after getting an IP address. If you are seeing this, run kubectl get service frontend-external -o=yaml | kubectl apply -f- to trigger load-balancer reconfiguration.

Option 3: Using Static Images

💡 Recommended for test-driving the application on an existing cluster.

Prerequisite: a running Kubernetes cluster.

  1. Clone this repository.

  2. Deploy the application: kubectl apply -f ./release/kubernetes-manifests

  3. Run kubectl get pods to see pods are in a healthy and ready state.

  4. Find the IP address of your application, then visit the application on your browser to confirm installation.

     kubectl get service frontend-external

Generate Synthetic Traffic

  1. If you want to create synthetic load manually, use the loadgenerator-tool executable found in the root of the repository. For example:
./loadgenerator-tool startup --zone us-central1-c [SANDBOX_FRONTEND_ADDRESS]

(Optional) Deploying on a Istio-installed GKE cluster

Note: If you followed GKE deployment steps above, run skaffold delete first to delete what's deployed.

  1. Create a GKE cluster (described above).

  2. Use Istio on GKE add-on to install Istio to your existing GKE cluster.

    gcloud beta container clusters update demo \
        --zone=us-central1-a \
        --update-addons=Istio=ENABLED \

    NOTE: If you need to enable MTLS_STRICT mode, you will need to update several manifest files:

    • kubernetes-manifests/frontend.yaml: delete "livenessProbe" and "readinessProbe" fields.
    • kubernetes-manifests/loadgenerator.yaml: delete "initContainers" field.
  3. (Optional) Enable Stackdriver Tracing/Logging with Istio Stackdriver Adapter by following this guide.

  4. Install the automatic sidecar injection (annotate the default namespace with the label):

    kubectl label namespace default istio-injection=enabled
  5. Apply the manifests in ./istio-manifests directory.

    kubectl apply -f ./istio-manifests

    This is required only once.

  6. Deploy the application with skaffold run[PROJECT_ID].

  7. Run kubectl get pods to see pods are in a healthy and ready state.

  8. Find the IP address of your Istio gateway Ingress or Service, and visit the application.

    INGRESS_HOST="$(kubectl -n istio-system get service istio-ingressgateway -o jsonpath='{.status.loadBalancer.ingress[0].ip}')"
    echo "$INGRESS_HOST"
    curl -v "http://$INGRESS_HOST"

This is not an official Google project.

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