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Merge pull request #2085 from github/deployment-guides/add-gke
Add GKE, Amazon ECS, and Azure App Service deployment guides
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‎content/actions/guides/deploying-to-amazon-elastic-container-service.md‎

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---
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title: Deploying to Amazon Elastic Container Service
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intro: You can deploy to Amazon Elastic Container Service (ECS) as part of your continuous deployment (CD) workflows.
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product: '{% data reusables.gated-features.actions %}'
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versions:
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free-pro-team: '*'
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enterprise-server: '>=2.22'
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---
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{% data reusables.actions.enterprise-beta %}
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{% data reusables.actions.enterprise-github-hosted-runners %}
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### Introduction
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This guide explains how to use {% data variables.product.prodname_actions %} to build a containerized application, push it to [Amazon Elastic Container Registry (ECR)](https://aws.amazon.com/ecr/), and deploy it to [Amazon Elastic Container Service (ECS)](https://aws.amazon.com/ecs/).
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On every new release in your {% data variables.product.company_short %} repository, the {% data variables.product.prodname_actions %} workflow builds and pushes a new container image to Amazon ECR, and then deploys a new task definition to Amazon ECS.
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### Prerequisites
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Before creating your {% data variables.product.prodname_actions %} workflow, you will first need to complete the following setup steps for Amazon ECR and ECS:
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1. Create an Amazon ECR repository to store your images.
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For example, using [the AWS CLI](https://aws.amazon.com/cli/):
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{% raw %}```bash{:copy}
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aws ecr create-repository \
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--repository-name MY_ECR_REPOSITORY \
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--region MY_AWS_REGION
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```{% endraw %}
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Ensure that you use the same Amazon ECR repository name (represented here by `MY_ECR_REPOSITORY`) for the `ECR_REPOSITORY` variable in the workflow below.
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Ensure that you use the same AWS region value for the `AWS_REGION` (represented here by `MY_AWS_REGION`) variable in the workflow below.
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2. Create an Amazon ECS task definition, cluster, and service.
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For details, follow the [Getting started wizard on the Amazon ECS console](https://us-east-2.console.aws.amazon.com/ecs/home?region=us-east-2#/firstRun), or the [Getting started guide](https://docs.aws.amazon.com/AmazonECS/latest/developerguide/getting-started-fargate.html) in the Amazon ECS documentation.
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Ensure that you note the names you set for the Amazon ECS service and cluster, and use them for the `ECS_SERVICE` and `ECS_CLUSTER` variables in the workflow below.
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3. Store your Amazon ECS task definition as a JSON file in your {% data variables.product.company_short %} repository.
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The format of the file should be the same as the output generated by:
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{% raw %}```bash{:copy}
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aws ecs register-task-definition --generate-cli-skeleton
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```{% endraw %}
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Ensure that you set the `ECS_TASK_DEFINITION` variable in the workflow below as the path to the JSON file.
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Ensure that you set the `CONTAINER_NAME` variable in the workflow below as the container name in the `containerDefinitions` section of the task definition.
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4. Create {% data variables.product.prodname_actions %} secrets named `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` to store the values for your Amazon IAM access key.
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For more information on creating secrets for {% data variables.product.prodname_actions %}, see "[Encrypted secrets](/actions/reference/encrypted-secrets#creating-encrypted-secrets-for-a-repository)."
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See the documentation for each action used below for the recommended IAM policies for the IAM user, and methods for handling the access key credentials.
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### Creating the workflow
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Once you've completed the prerequisites, you can proceed with creating the workflow.
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The following example workflow demonstrates how to build a container image and push it to Amazon ECR. It then updates the task definition with the new image ID, and deploys the task definition to Amazon ECS.
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Ensure that you provide your own values for all the variables in the `env` key of the workflow.
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{% raw %}
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```yaml{:copy}
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name: Deploy to Amazon ECS
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on:
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release:
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types: [ created ]
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env:
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AWS_REGION: MY_AWS_REGION # set this to your preferred AWS region, e.g. us-west-1
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ECR_REPOSITORY: MY_ECR_REPOSITORY # set this to your Amazon ECR repository name
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ECS_SERVICE: MY_ECS_SERVICE # set this to your Amazon ECS service name
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ECS_CLUSTER: MY_ECS_CLUSTER # set this to your Amazon ECS cluster name
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ECS_TASK_DEFINITION: MY_ECS_TASK_DEFINITION # set this to the path to your Amazon ECS task definition
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# file, e.g. .aws/task-definition.json
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CONTAINER_NAME: MY_CONTAINER_NAME # set this to the name of the container in the
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# containerDefinitions section of your task definition
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defaults:
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run:
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shell: bash
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jobs:
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deploy:
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name: Deploy
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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@v2
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- name: Configure AWS credentials
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uses: aws-actions/configure-aws-credentials@v1
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with:
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aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
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aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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aws-region: $AWS_REGION
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- name: Login to Amazon ECR
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id: login-ecr
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uses: aws-actions/amazon-ecr-login@v1
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- name: Build, tag, and push image to Amazon ECR
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id: build-image
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env:
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ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
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IMAGE_TAG: ${{ github.sha }}
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run: |
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# Build a docker container and
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# push it to ECR so that it can
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# be deployed to ECS.
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docker build -t $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG .
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docker push $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG
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echo "image=$ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG" >> $GITHUB_ENV
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- name: Fill in the new image ID in the Amazon ECS task definition
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id: task-def
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uses: aws-actions/amazon-ecs-render-task-definition@v1
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with:
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task-definition: $ECS_TASK_DEFINITION
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container-name: $CONTAINER_NAME
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image: ${{ steps.build-image.outputs.image }}
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- name: Deploy Amazon ECS task definition
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uses: aws-actions/amazon-ecs-deploy-task-definition@v1
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with:
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task-definition: ${{ steps.task-def.outputs.task-definition }}
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service: $ECS_SERVICE
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cluster: $ECS_CLUSTER
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wait-for-service-stability: true
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```
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{% endraw %}
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### Additional resources
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For more information on the services used in these examples, see the following documentation:
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* "[Security best practices in IAM](https://docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html)" in the Amazon AWS documentation.
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* Official AWS "[Configure AWS Credentials](https://github.com/aws-actions/configure-aws-credentials)" action.
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* Official AWS [Amazon ECR "Login"](https://github.com/aws-actions/amazon-ecr-login) action.
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* Official AWS [Amazon ECS "Render Task Definition"](https://github.com/aws-actions/amazon-ecs-render-task-definition) action.
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* Official AWS [Amazon ECS "Deploy Task Definition"](https://github.com/aws-actions/amazon-ecs-deploy-task-definition) action.

‎content/actions/guides/deploying-to-azure-app-service.md‎

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---
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title: Deploying to Azure App Service
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intro: You can deploy to Azure App Service as part of your continuous deployment (CD) workflows.
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product: '{% data reusables.gated-features.actions %}'
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versions:
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free-pro-team: '*'
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enterprise-server: '>=2.22'
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---
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{% data reusables.actions.enterprise-beta %}
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{% data reusables.actions.enterprise-github-hosted-runners %}
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### Introduction
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This guide explains how to use {% data variables.product.prodname_actions %} to build, test, and deploy an application to [Azure App Service](https://azure.microsoft.com/en-us/services/app-service/).
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Azure App Service can run web apps in several languages, but this guide demonstrates deploying an existing Node.js project.
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### Prerequisites
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Before creating your {% data variables.product.prodname_actions %} workflow, you will first need to complete the following setup steps:
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1. Create an Azure App Service plan.
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For example, you can use the Azure CLI to create a new App Service plan:
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```bash{:copy}
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az appservice plan create \
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--resource-group MY_RESOURCE_GROUP \
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--name MY_APP_SERVICE_PLAN \
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--is-linux
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```
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In the command above, replace `MY_RESOURCE_GROUP` with your pre-existing Azure Resource Group, and `MY_APP_SERVICE_PLAN` with a new name for the App Service plan.
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See the Azure documentation for more information on using the [Azure CLI](https://docs.microsoft.com/en-us/cli/azure/):
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* For authentication, see "[Sign in with Azure CLI](https://docs.microsoft.com/en-us/cli/azure/authenticate-azure-cli)".
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* If you need to create a new resource group, see "[az group](https://docs.microsoft.com/en-us/cli/azure/group?view=azure-cli-latest#az_group_create)."
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2. Create a web app.
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For example, you can use the Azure CLI to create an Azure App Service web app with a node runtime:
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```bash{:copy}
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az webapp create \
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--name MY_WEBAPP_NAME \
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--plan MY_APP_SERVICE_PLAN \
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--resource-group MY_RESOURCE_GROUP \
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--runtime "node|10.14"
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```
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In the command above, replace the parameters with your own values, where `MY_WEBAPP_NAME` is a new name for the web app.
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3. Configure an Azure publish profile and create an `AZURE_WEBAPP_PUBLISH_PROFILE` secret.
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Generate your Azure deployment credentials using a publish profile. For more information, see "[Generate deployment credentials](https://docs.microsoft.com/en-us/azure/app-service/deploy-github-actions?tabs=applevel#generate-deployment-credentials)" in the Azure documentation.
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In your {% data variables.product.prodname_dotcom %} repository, create a secret named `AZURE_WEBAPP_PUBLISH_PROFILE` that contains the contents of the publish profile. For more information on creating secrets, see "[Encrypted secrets](/actions/reference/encrypted-secrets#creating-encrypted-secrets-for-a-repository)."
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### Creating the workflow
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Once you've completed the prerequisites, you can proceed with creating the workflow.
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The following example workflow demonstrates how to build, test, and deploy the Node.js project to Azure App Service.
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Ensure that you set `AZURE_WEBAPP_NAME` in the workflow `env` key to the name of the web app you created.
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{% raw %}
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```yaml{:copy}
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on:
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release:
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types: [created]
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env:
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AZURE_WEBAPP_NAME: MY_WEBAPP_NAME # set this to your application's name
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AZURE_WEBAPP_PACKAGE_PATH: '.' # set this to the path to your web app project, defaults to the repository root
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NODE_VERSION: '10.x' # set this to the node version to use
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jobs:
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build-and-deploy:
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name: Build and Deploy
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v2
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- name: Use Node.js ${{ env.NODE_VERSION }}
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uses: actions/setup-node@v1
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with:
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node-version: ${{ env.NODE_VERSION }}
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- name: npm install, build, and test
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run: |
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# Build and test the project, then
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# deploy to Azure Web App.
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npm install
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npm run build --if-present
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npm run test --if-present
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- name: 'Deploy to Azure WebApp'
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uses: azure/webapps-deploy@v2
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with:
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app-name: ${{ env.AZURE_WEBAPP_NAME }}
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publish-profile: ${{ secrets.AZURE_WEBAPP_PUBLISH_PROFILE }}
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package: ${{ env.AZURE_WEBAPP_PACKAGE_PATH }}
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```
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{% endraw %}
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### Additional resources
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The following resources may also be useful:
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* For the original starter workflow, see [`azure.yml`](https://github.com/actions/starter-workflows/blob/master/ci/azure.yml) in the {% data variables.product.prodname_actions %} `starter-workflows` repository.
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* The action used to deploy the web app is the official Azure [`Azure/webapps-deploy`](https://github.com/Azure/webapps-deploy) action.
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* The "[Create a Node.js web app in Azure](https://docs.microsoft.com/en-us/azure/app-service/quickstart-nodejs)" quickstart in the Azure web app documentation demonstrates using VS Code with the [Azure App Service extension](https://marketplace.visualstudio.com/items?itemName=ms-azuretools.vscode-azureappservice).

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