Augmented-Online Boutique

Online Boutique is open sourced by google cloud. But the initial microservice application open-sourced by Google Cloud is not equipped with adequate observability instrumentation (e.g., Trace, Log does not contain TraceID). In this study, we instrument the Opentelemetry API for each service to obtain traces and insert Trace ID and Span ID into each log to enhance observability.

This Augmented-Online Boutique is open-sourced by submited FSE 2023 paper Nezha

Screenshots

Home Page	Checkout Screen

Service Architecture

Online Boutique is composed of many microservices written in different languages that talk to each other over gRPC.

Find Protocol Buffers Descriptions at 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#	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	Node.js	Converts one money amount to another currency. Uses real values fetched from European Central Bank. It's the highest QPS service.
paymentservice	Node.js	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	Python	Sends users an order confirmation email (mock).
checkoutservice	Go	Retrieves user cart, prepares order and orchestrates the payment, shipping and the email notification.
recommendationservice	Python	Recommends other products based on what's given in the cart.
adservice	Java	Provides text ads based on given context words.
loadgenerator	Python/Locust	Continuously sends requests imitating realistic user shopping flows to the frontend.

Features

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.
OpenCensus Tracing: Most services are instrumented using OpenCensus trace interceptors for gRPC/HTTP.
Stackdriver APM: Many services are instrumented with Profiling, Tracing and Debugging. In addition to these, using Istio enables features like Request/Response Metrics and Context Graph out of the box. When it is running out of Google Cloud, this code path remains inactive.
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.

Deploy

cd kubernetes-manifests

bash start_demo_with_istio.sh

fallingleaflun / augmented-onlineboutique Goto Github PK