This application was forked from microservices-demo, used to demonstrate how to build micro servics with go-micro.
Online Boutique is a cloud-native microservices demo application. Online Boutique consists of a 11-tier microservices application. The application is a web-based e-commerce app where users can browse items, add them to the cart, and purchase them.
Google uses this application to demonstrate use of technologies like Kubernetes/GKE, Istio, Stackdriver, gRPC and OpenTelemetry. This application works on any Kubernetes cluster, as well as Google Kubernetes Engine. It’s easy to deploy with little to no configuration.
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Home Page | Checkout Screen |
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- Workload Identity: See these instructions.
- Istio: See these instructions.
- Anthos Service Mesh: ASM requires Workload Identity to be enabled in your GKE cluster. See the workload identity instructions to configure and deploy the app. Then, use the service mesh guide.
- non-GKE clusters (Minikube, Kind): see the Development Guide
- Memorystore: See these instructions to replace the in-cluster
redis
database with hosted Google Cloud Memorystore (redis). - Cymbal Shops Branding: See these instructions
- NetworkPolicies: See these instructions
- Jaeger: See these instructions
Online Boutique is composed of 11 microservices written in different languages that talk to each other over gRPC. See the Development Principles doc for more information.
Service | Language | Description |
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frontend | Go | Exposes an HTTP server to serve the website. Does not require signup/login and generates session IDs for all users automatically. |
cartservice | Go | Stores the items in the user's shopping cart in Redis and retrieves it. |
productcatalogservice | Go | Provides the list of products from a JSON file and ability to search products and get individual products. |
currencyservice | Go | Converts one money amount to another currency. Uses real values fetched from European Central Bank. It's the highest QPS service. |
paymentservice | Go | Charges the given credit card info (mock) 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 (mock) |
emailservice | Go | Sends users an order confirmation email (mock). |
checkoutservice | Go | Retrieves user cart, prepares order and orchestrates the payment, shipping and the email notification. |
recommendationservice | Go | Recommends other products based on what's given in the cart. |
adservice | Go | Provides text ads based on given context words. |
loadgenerator | Python+Locust | Continuously sends requests imitating realistic user shopping flows to the frontend. |
- Kubernetes/GKE: The app is designed to run on Kubernetes (both locally on "Docker for Desktop", as well as on the cloud with GKE).
- gRPC: Microservices use a high volume of gRPC calls to communicate to each other.
- Istio: Application works on Istio service mesh.
- OpenTelemetry Tracing: Most services are instrumented using OpenTelemetry trace interceptors for gRPC/HTTP.
- Skaffold: Application is deployed to Kubernetes with a single command using Skaffold.
- Synthetic Load Generation: The application demo comes with a background job that creates realistic usage patterns on the website using Locust load generator.
If you would like to contribute features or fixes to this app, see the Development Guide on how to build this demo locally.
- From edge to mesh: Exposing service mesh applications through GKE Ingress
- Take the first step toward SRE with Cloud Operations Sandbox
- Deploying the Online Boutique sample application on Anthos Service Mesh
- Anthos Service Mesh Workshop: Lab Guide
- KubeCon EU 2019 - Reinventing Networking: A Deep Dive into Istio's Multicluster Gateways - Steve Dake, Independent
- Google Cloud Next'18 SF
- Day 1 Keynote showing GKE On-Prem
- Day 3 Keynote showing Stackdriver APM (Tracing, Code Search, Profiler, Google Cloud Build)
- Introduction to Service Management with Istio
- Google Cloud Next'18 London – Keynote showing Stackdriver Incident Response Management