Hipster Shop: Cloud-Native Microservices Demo Application

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

Google uses this application to demonstrate Kubernetes, GKE, Istio,
Stackdriver, gRPC, OpenCensus and similar cloud-native technologies.

Note to Googlers: Please fill out the form at
go/microservices-demo if you are using this
application.

Screenshots

Home Page	Checkout Screen

Service Architecture

Hipster Shop 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 shipping 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 (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 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.

Installation

Note: that the first build can take up to 20-30 minutes. Consequent builds
will be faster.

Option 1: Running locally with “Docker for Desktop”

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

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)
Launch “Docker for Desktop”. Go to Preferences:
- choose “Enable Kubernetes”,
- set CPUs to at least 3, and Memory to at least 6.0 GiB
Run kubectl get nodes to verify you're connected to “Kubernetes on Docker”.
Run skaffold run (first time will be slow, it can take ~20-30 minutes).
This will build and deploy the application. If you need to rebuild the images
automatically as you refactor he code, run skaffold dev command.
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.

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

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

 gcloud services enable container.googleapis.com

 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

Enable Google Container Registry (GCR) on your GCP project and configure the
docker CLI to authenticate to GCR:
```
gcloud services enable containerregistry.googleapis.com

gcloud auth configure-docker -q
```
In the root of this repository, run skaffold run --default-repo=gcr.io/[PROJECT_ID],
where [PROJECT_ID] is your GCP project ID.

This command:
- builds the container images
- pushes them to GCR
- applies the ./kubernetes-manifests deploying the application to
  Kubernetes.
Troubleshooting: If you get "No space left on device" error on Google
Cloud Shell, you can build the images on Google Cloud Build: Enable the
Cloud Build
API,
then run skaffold run -p gcb --default-repo=gcr.io/[PROJECT_ID] instead.
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 load balancer to not to 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.

Clone this repository.
Deploy the application: kubectl apply -f ./release/kubernetes-manifests
Run kubectl get pods to see pods are in a healthy and ready state.
Find the IP address of your application, then visit the application on your
browser to confirm installation.
```
kubectl get service frontend-external
```

(Optional) Deploying on a Istio-installed GKE cluster

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

Create a GKE cluster (described above).
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 \
    --istio-config=auth=MTLS_PERMISSIVE
```
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.
(Optional) Enable Stackdriver Tracing/Logging with Istio Stackdriver Adapter
by following this guide.
Install the automatic sidecar injection (annotate the default namespace
with the label):
```
kubectl label namespace default istio-injection=enabled
```
Apply the manifests in ./istio-manifests directory.
```
kubectl apply -f ./istio-manifests
```
This is required only once.
Deploy the application with skaffold run --default-repo=gcr.io/[PROJECT_ID].
Run kubectl get pods to see pods are in a healthy and ready state.

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"

Conferences featuring Hipster Shop

Google Cloud Next'18 London – Keynote
showing Stackdriver Incident Response Management
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

This is not an official Google project.

benking84/microservices-demo