333 lines
15 KiB
Markdown
333 lines
15 KiB
Markdown
<p align="center">
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<img src="src/frontend/static/icons/Hipster_HeroLogoCyan.svg" width="300"/>
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</p>
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**Online Boutique** is a cloud-native microservices demo application.
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Online Boutique consists of a 10-tier microservices application. The application is a
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web-based e-commerce app where users can browse items,
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add them to the cart, and purchase them.
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**Google uses this application to demonstrate use of technologies like
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Kubernetes/GKE, Istio, Stackdriver, gRPC and OpenCensus**. This application
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works on any Kubernetes cluster (such as a local one), as well as Google
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Kubernetes Engine. It’s **easy to deploy with little to no configuration**.
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If you’re using this demo, please **★Star** this repository to show your interest!
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> 👓**Note to Googlers:** Please fill out the form at
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> [go/microservices-demo](http://go/microservices-demo) if you are using this
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> application.
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Looking for the old Hipster Shop frontend interface? Use the [manifests](https://github.com/GoogleCloudPlatform/microservices-demo/tree/v0.1.5/kubernetes-manifests) in release [v0.1.5](https://github.com/GoogleCloudPlatform/microservices-demo/releases/v0.1.5).
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## Screenshots
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| Home Page | Checkout Screen |
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| ----------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------ |
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| [![Screenshot of store homepage](./docs/img/online-boutique-frontend-1.png)](./docs/img/online-boutique-frontend-1.png) | [![Screenshot of checkout screen](./docs/img/online-boutique-frontend-2.png)](./docs/img/online-boutique-frontend-2.png) |
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## Service Architecture
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**Online Boutique** is composed of many microservices written in different
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languages that talk to each other over gRPC.
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[![Architecture of
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microservices](./docs/img/architecture-diagram.png)](./docs/img/architecture-diagram.png)
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Find **Protocol Buffers Descriptions** at the [`./pb` directory](./pb).
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| Service | Language | Description |
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| ---------------------------------------------------- | ------------- | --------------------------------------------------------------------------------------------------------------------------------- |
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| [frontend](./src/frontend) | Go | Exposes an HTTP server to serve the website. Does not require signup/login and generates session IDs for all users automatically. |
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| [cartservice](./src/cartservice) | C# | Stores the items in the user's shopping cart in Redis and retrieves it. |
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| [productcatalogservice](./src/productcatalogservice) | Go | Provides the list of products from a JSON file and ability to search products and get individual products. |
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| [currencyservice](./src/currencyservice) | Node.js | Converts one money amount to another currency. Uses real values fetched from European Central Bank. It's the highest QPS service. |
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| [paymentservice](./src/paymentservice) | Node.js | Charges the given credit card info (mock) with the given amount and returns a transaction ID. |
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| [shippingservice](./src/shippingservice) | Go | Gives shipping cost estimates based on the shopping cart. Ships items to the given address (mock) |
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| [emailservice](./src/emailservice) | Python | Sends users an order confirmation email (mock). |
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| [checkoutservice](./src/checkoutservice) | Go | Retrieves user cart, prepares order and orchestrates the payment, shipping and the email notification. |
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| [recommendationservice](./src/recommendationservice) | Python | Recommends other products based on what's given in the cart. |
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| [adservice](./src/adservice) | Java | Provides text ads based on given context words. |
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| [loadgenerator](./src/loadgenerator) | Python/Locust | Continuously sends requests imitating realistic user shopping flows to the frontend. |
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## Features
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- **[Kubernetes](https://kubernetes.io)/[GKE](https://cloud.google.com/kubernetes-engine/):**
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The app is designed to run on Kubernetes (both locally on "Docker for
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Desktop", as well as on the cloud with GKE).
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- **[gRPC](https://grpc.io):** Microservices use a high volume of gRPC calls to
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communicate to each other.
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- **[Istio](https://istio.io):** Application works on Istio service mesh.
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- **[OpenCensus](https://opencensus.io/) Tracing:** Most services are
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instrumented using OpenCensus trace interceptors for gRPC/HTTP.
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- **[Stackdriver APM](https://cloud.google.com/stackdriver/):** Many services
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are instrumented with **Profiling**, **Tracing** and **Debugging**. In
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addition to these, using Istio enables features like Request/Response
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**Metrics** and **Context Graph** out of the box. When it is running out of
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Google Cloud, this code path remains inactive.
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- **[Skaffold](https://skaffold.dev):** Application
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is deployed to Kubernetes with a single command using Skaffold.
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- **Synthetic Load Generation:** The application demo comes with a background
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job that creates realistic usage patterns on the website using
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[Locust](https://locust.io/) load generator.
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## Installation
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We offer the following installation methods:
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1. **Running locally** (~20 minutes) You will build
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and deploy microservices images to a single-node Kubernetes cluster running
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on your development machine. There are three options to run a Kubernetes
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cluster locally for this demo:
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- [Minikube](https://github.com/kubernetes/minikube). Recommended for
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Linux hosts (also supports Mac/Windows).
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- [Docker for Desktop](https://www.docker.com/products/docker-desktop).
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Recommended for Mac/Windows.
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- [Kind](https://www.docker.com/products/docker-desktop). Supports Mac/Windows/Linux.
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1. **Running on Google Kubernetes Engine (GKE)”** (~30 minutes) You will build,
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upload and deploy the container images to a Kubernetes cluster on Google
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Cloud.
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1. **Using pre-built container images:** (~10 minutes, you will still need to
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follow one of the steps above up until `skaffold run` command). With this
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option, you will use pre-built container images that are available publicly,
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instead of building them yourself, which takes a long time).
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### Option 1: Running locally
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> 💡 Recommended if you're planning to develop the application or giving it a
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> try on your local cluster.
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1. Install tools to run a Kubernetes cluster locally:
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- kubectl (can be installed via `gcloud components install kubectl`)
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- Local Kubernetes cluster deployment tool:
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- [Minikube (recommended for
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Linux)](https://kubernetes.io/docs/setup/minikube/)
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- [Docker for Desktop (recommended for Mac/Windows)](https://www.docker.com/products/docker-desktop)
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- It provides Kubernetes support as [noted
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here](https://docs.docker.com/docker-for-mac/kubernetes/)
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- [Kind](https://github.com/kubernetes-sigs/kind)
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- [skaffold]( https://skaffold.dev/docs/install/) (ensure version ≥v0.20)
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1. Launch the local Kubernetes cluster with one of the following tools:
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- To launch **Minikube** (tested with Ubuntu Linux). Please, ensure that the
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local Kubernetes cluster has at least:
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- 4 CPU's
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- 4.0 GiB memory
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```shell
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minikube start --cpus=4 --memory 4096
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```
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- To launch **Docker for Desktop** (tested with Mac/Windows). Go to Preferences:
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- choose “Enable Kubernetes”,
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- set CPUs to at least 3, and Memory to at least 6.0 GiB
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- on the "Disk" tab, set at least 32 GB disk space
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- To launch a **Kind** cluster:
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```shell
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kind create cluster
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```
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1. Run `kubectl get nodes` to verify you're connected to “Kubernetes on Docker”.
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1. Run `skaffold run` (first time will be slow, it can take ~20 minutes).
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This will build and deploy the application. If you need to rebuild the images
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automatically as you refactor the code, run `skaffold dev` command.
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1. Run `kubectl get pods` to verify the Pods are ready and running.
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1. Access the web frontend through your browser
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- **Minikube** requires you to run a command to access the frontend service:
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```shell
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minikube service frontend-external
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```
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- **Docker For Desktop** should automatically provide the frontend at http://localhost:80
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- **Kind** does not provision an IP address for the service.
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You must run a port-forwarding process to access the frontend at http://localhost:8080:
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```shell
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kubectl port-forward deployment/frontend 8080:8080
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```
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### Option 2: Running on Google Kubernetes Engine (GKE)
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> 💡 Recommended if you're using Google Cloud Platform and want to try it on
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> a realistic cluster.
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1. Install tools specified in the previous section (Docker, kubectl, skaffold)
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1. Create a Google Kubernetes Engine cluster and make sure `kubectl` is pointing
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to the cluster.
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```sh
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gcloud services enable container.googleapis.com
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```
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```sh
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gcloud container clusters create demo --enable-autoupgrade \
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--enable-autoscaling --min-nodes=3 --max-nodes=10 --num-nodes=5 --zone=us-central1-a
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```
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```
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kubectl get nodes
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```
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1. Enable Google Container Registry (GCR) on your GCP project and configure the
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`docker` CLI to authenticate to GCR:
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```sh
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gcloud services enable containerregistry.googleapis.com
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```
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```sh
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gcloud auth configure-docker -q
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```
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1. In the root of this repository, run `skaffold run --default-repo=gcr.io/[PROJECT_ID]`,
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where [PROJECT_ID] is your GCP project ID.
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This command:
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- builds the container images
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- pushes them to GCR
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- applies the `./kubernetes-manifests` deploying the application to
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Kubernetes.
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**Troubleshooting:** If you get "No space left on device" error on Google
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Cloud Shell, you can build the images on Google Cloud Build: [Enable the
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Cloud Build
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API](https://console.cloud.google.com/flows/enableapi?apiid=cloudbuild.googleapis.com),
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then run `skaffold run -p gcb --default-repo=gcr.io/[PROJECT_ID]` instead.
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1. Find the IP address of your application, then visit the application on your
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browser to confirm installation.
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kubectl get service frontend-external
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**Troubleshooting:** A Kubernetes bug (will be fixed in 1.12) combined with
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a Skaffold [bug](https://github.com/GoogleContainerTools/skaffold/issues/887)
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causes load balancer to not to work even after getting an IP address. If you
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are seeing this, run `kubectl get service frontend-external -o=yaml | kubectl apply -f-`
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to trigger load balancer reconfiguration.
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### Option 3: Using Pre-Built Container Images
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> 💡 Recommended if you want to deploy the app faster in fewer steps to an
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> existing cluster.
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**NOTE:** If you need to create a Kubernetes cluster locally or on the cloud,
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follow "Option 1" or "Option 2" until you reach the `skaffold run` step.
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This option offers you pre-built public container images that are easy to deploy
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by deploying the [release manifest](./release) directly to an existing cluster.
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**Prerequisite**: a running Kubernetes cluster (either local or on cloud).
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1. Clone this repository, and go to the repository directory
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1. Run `kubectl apply -f ./release/kubernetes-manifests.yaml` to deploy the app.
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1. Run `kubectl get pods` to see pods are in a Ready state.
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1. Find the IP address of your application, then visit the application on your
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browser to confirm installation.
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```sh
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kubectl get service/frontend-external
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```
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### (Optional) Deploying on a Istio-installed GKE cluster
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> **Note:** you followed GKE deployment steps above, run `skaffold delete` first
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> to delete what's deployed.
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1. Create a GKE cluster (described in "Option 2").
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1. Use [Istio on GKE add-on](https://cloud.google.com/istio/docs/istio-on-gke/installing)
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to install Istio to your existing GKE cluster.
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```sh
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gcloud beta container clusters update demo \
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--zone=us-central1-a \
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--update-addons=Istio=ENABLED \
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--istio-config=auth=MTLS_PERMISSIVE
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```
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2. (Optional) Enable Stackdriver Tracing/Logging with Istio Stackdriver Adapter
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by [following this guide](https://cloud.google.com/istio/docs/istio-on-gke/installing#enabling_tracing_and_logging).
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3. Install the automatic sidecar injection (annotate the `default` namespace
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with the label):
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```sh
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kubectl label namespace default istio-injection=enabled
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```
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4. Apply the manifests in [`./istio-manifests`](./istio-manifests) directory.
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(This is required only once.)
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```sh
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kubectl apply -f ./istio-manifests
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```
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5. In the root of this repository, run `skaffold run --default-repo=gcr.io/[PROJECT_ID]`,
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where [PROJECT_ID] is your GCP project ID.
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This command:
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- builds the container images
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- pushes them to GCR
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- applies the `./kubernetes-manifests` deploying the application to
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Kubernetes.
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**Troubleshooting:** If you get "No space left on device" error on Google
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Cloud Shell, you can build the images on Google Cloud Build: [Enable the
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Cloud Build
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API](https://console.cloud.google.com/flows/enableapi?apiid=cloudbuild.googleapis.com),
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then run `skaffold run -p gcb --default-repo=gcr.io/[PROJECT_ID]` instead.
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6. Run `kubectl get pods` to see pods are in a healthy and ready state.
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7. Find the IP address of your Istio gateway Ingress or Service, and visit the
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application.
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```sh
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INGRESS_HOST="$(kubectl -n istio-system get service istio-ingressgateway \
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-o jsonpath='{.status.loadBalancer.ingress[0].ip}')"
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echo "$INGRESS_HOST"
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```
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```sh
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curl -v "http://$INGRESS_HOST"
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```
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### Cleanup
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If you've deployed the application with `skaffold run` command, you can run
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`skaffold delete` to clean up the deployed resources.
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If you've deployed the application with `kubectl apply -f [...]`, you can
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run `kubectl delete -f [...]` with the same argument to clean up the deployed
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resources.
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## Conferences featuring Online Boutique
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- [Google Cloud Next'18 London – Keynote](https://youtu.be/nIq2pkNcfEI?t=3071)
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showing Stackdriver Incident Response Management
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- Google Cloud Next'18 SF
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- [Day 1 Keynote](https://youtu.be/vJ9OaAqfxo4?t=2416) showing GKE On-Prem
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- [Day 3 – Keynote](https://youtu.be/JQPOPV_VH5w?t=815) showing Stackdriver
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APM (Tracing, Code Search, Profiler, Google Cloud Build)
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- [Introduction to Service Management with Istio](https://www.youtube.com/watch?v=wCJrdKdD6UM&feature=youtu.be&t=586)
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- [KubeCon EU 2019 - Reinventing Networking: A Deep Dive into Istio's Multicluster Gateways - Steve Dake, Independent](https://youtu.be/-t2BfT59zJA?t=982)
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---
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This is not an official Google project.
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