https://github.com/Azure-Samples/aks-store-demo
Sample microservices app for AKS demos, tutorials, and experiments
https://github.com/Azure-Samples/aks-store-demo
Last synced: about 1 year ago
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Sample microservices app for AKS demos, tutorials, and experiments
- Host: GitHub
- URL: https://github.com/Azure-Samples/aks-store-demo
- Owner: Azure-Samples
- License: mit
- Created: 2023-06-02T16:49:30.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-08-03T06:15:38.000Z (almost 2 years ago)
- Last Synced: 2024-08-03T07:27:54.442Z (almost 2 years ago)
- Language: Bicep
- Homepage:
- Size: 8.36 MB
- Stars: 134
- Watchers: 16
- Forks: 207
- Open Issues: 9
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
- Code of conduct: .github/CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
---
page_type: sample
languages:
- azdeveloper
- go
- javascript
- rust
- nodejs
- python
- bicep
- terraform
- dockerfile
products:
- azure
- azure-kubernetes-service
- azure-openai
- azure-cosmos-db
- azure-container-registry
- azure-service-bus
- azure-monitor
- azure-log-analytics
- azure-managed-grafana
- azure-key-vault
urlFragment: aks-store-demo
name: AKS Store Demo
description: This sample demo app consists of a group of containerized microservices that can be easily deployed into an Azure Kubernetes Service (AKS) cluster.
---
# AKS Store Demo
This sample demo app consists of a group of containerized microservices that can be easily deployed into an Azure Kubernetes Service (AKS) cluster. This is meant to show a realistic scenario using a polyglot architecture, event-driven design, and common open source back-end services (eg - RabbitMQ, MongoDB). The application also leverages OpenAI's GPT-3 models to generate product descriptions. This can be done using either [Azure OpenAI](https://learn.microsoft.com/azure/ai-services/openai/overview) or [OpenAI](https://openai.com/).
This application is inspired by another demo app called [Red Dog](https://github.com/Azure/reddog-code).
> [!NOTE]
> This is not meant to be an example of perfect code to be used in production, but more about showing a realistic application running in AKS.
## Architecture
The application has the following services:
| Service | Description |
| --- | --- |
| `makeline-service` | This service handles processing orders from the queue and completing them (Golang) |
| `order-service` | This service is used for placing orders (Javascript) |
| `product-service` | This service is used to perform CRUD operations on products (Rust) |
| `store-front` | Web app for customers to place orders (Vue.js) |
| `store-admin` | Web app used by store employees to view orders in queue and manage products (Vue.js) |
| `virtual-customer` | Simulates order creation on a scheduled basis (Rust) |
| `virtual-worker` | Simulates order completion on a scheduled basis (Rust) |
| `ai-service` | Optional service for adding generative text and graphics creation (Python) |
| `mongodb` | MongoDB instance for persisted data |
| `rabbitmq` | RabbitMQ for an order queue |
## Run the app on Azure Kubernetes Service (AKS)
To learn how to deploy this app on AKS, see [Quickstart: Deploy an Azure Kubernetes Service (AKS) cluster using Azure CLI](https://learn.microsoft.com/azure/aks/learn/quick-kubernetes-deploy-cli).
> [!NOTE]
> The above article shows a simplified version of the store app with some services removed. For the full application, you can use the `aks-store-all-in-one.yaml` file in this repo.
## Run on any Kubernetes
This application uses public images stored in GitHub Container Registry and Microsoft Container Registry (MCR). Once your Kubernetes cluster of choice is setup, you can deploy the full app with the below commands.
This deployment deploys everything except the `ai-service` that integrates OpenAI. If you want to try integrating the OpenAI component, take a look at this article: [Deploy an application that uses OpenAI on Azure Kubernetes Service (AKS)](https://learn.microsoft.com/azure/aks/open-ai-quickstart?tabs=aoai).
```bash
kubectl create ns pets
kubectl apply -f https://raw.githubusercontent.com/Azure-Samples/aks-store-demo/main/aks-store-all-in-one.yaml -n pets
```
## Run the app locally
The application is designed to be [run in an AKS cluster](#run-the-app-on-aks), but can also be run locally using Docker Compose.
> [!TIP]
> You must have [Docker Desktop](https://www.docker.com/products/docker-desktop) installed to run this app locally. If you do not have it installed locally, you can try opening this repo in a [GitHub Codespace instead](#run-the-app-with-github-codespaces)
To run this app locally:
Clone the repo to your development computer and navigate to the directory:
```console
git clone https://github.com/Azure-Samples/aks-store-demo.git
cd aks-store-demo
```
Configure your Azure OpenAI or OpenAI API keys in [`docker-compose.yml`](./docker-compose.yml) using the environment variables in the `ai-service` section:
```yaml
ai-service:
build: src/ai-service
container_name: 'ai-service'
...
environment:
- USE_AZURE_OPENAI=True # set to False if you are not using Azure OpenAI
- AZURE_OPENAI_DEPLOYMENT_NAME= # required if using Azure OpenAI
- AZURE_OPENAI_ENDPOINT= # required if using Azure OpenAI
- OPENAI_API_KEY= # always required
- OPENAI_ORG_ID= # required if using OpenAI
...
```
Alternatively, if you do not have access to Azure OpenAI or OpenAI API keys, you can run the app without the `ai-service` by commenting out the `ai-service` section in [`docker-compose.yml`](./docker-compose.yml). For example:
```yaml
# ai-service:
# build: src/ai-service
# container_name: 'ai-service'
...
# networks:
# - backend_services
```
Start the app using `docker compose`. For example:
```bash
docker compose up
```
To stop the app, you can hit the `CTRL+C` key combination in the terminal window where the app is running.
## Run the app with GitHub Codespaces
This repo also includes [DevContainer configuration](./.devcontainer/devcontainer.json), so you can open the repo using [GitHub Codespaces](https://docs.github.com/en/codespaces/overview). This will allow you to run the app in a container in the cloud, without having to install Docker on your local machine. When the Codespace is created, you can run the app using the same instructions as above.
[](https://github.com/codespaces/new?hide_repo_select=true&ref=main&repo=648726487)
## Deploy the app to Azure using Azure Developer CLI
See the [Azure Developer CLI](./docs/azd.md) documentation for instructions on how to quickly deploy the app to Azure.
## Additional Resources
- AKS Documentation. https://learn.microsoft.com/azure/aks
- Kubernetes Learning Path. https://azure.microsoft.com/resources/kubernetes-learning-path