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119 changes: 119 additions & 0 deletions .github/workflows/alibabacloud.yml
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# This workflow will build and push a new container image to Alibaba Cloud Container Registry (ACR),
# and then will deploy it to Alibaba Cloud Container Service for Kubernetes (ACK), when a release is created.
#
# To use this workflow, you will need to complete the following set-up steps:
#
# 1. Create an ACR repository to store your container images.
# You can use ACR EE instance for more security and better performance.
# For instructions see https://www.alibabacloud.com/help/doc-detail/142168.htm
#
# 2. Create an ACK cluster to run your containerized application.
# You can use ACK Pro cluster for more security and better performance.
# For instructions see https://www.alibabacloud.com/help/doc-detail/95108.htm
#
# 3. Store your AccessKey pair in GitHub Actions secrets named `ACCESS_KEY_ID` and `ACCESS_KEY_SECRET`.
# For instructions on setting up secrets see: https://developer.github.com/actions/managing-workflows/storing-secrets/
#
# 4. Change the values for the REGION_ID, REGISTRY, NAMESPACE, IMAGE, ACK_CLUSTER_ID, and ACK_DEPLOYMENT_NAME.
#

name: Build and Deploy to ACK

on:
release:
types: [created]

# Environment variables available to all jobs and steps in this workflow.
env:
REGION_ID: cn-hangzhou
REGISTRY: registry.cn-hangzhou.aliyuncs.com
NAMESPACE: namespace
IMAGE: repo
TAG: ${{ github.sha }}
ACK_CLUSTER_ID: clusterID
ACK_DEPLOYMENT_NAME: nginx-deployment

ACR_EE_REGISTRY: myregistry.cn-hangzhou.cr.aliyuncs.com
ACR_EE_INSTANCE_ID: instanceID
ACR_EE_NAMESPACE: namespace
ACR_EE_IMAGE: repo
ACR_EE_TAG: ${{ github.sha }}

jobs:
build:
runs-on: ubuntu-latest
environment: production

steps:
- name: Checkout
uses: actions/checkout@v2

# 1.1 Login to ACR
- name: Login to ACR with the AccessKey pair
uses: aliyun/acr-login@v1
with:
region-id: "${{ env.REGION_ID }}"
access-key-id: "${{ secrets.ACCESS_KEY_ID }}"
access-key-secret: "${{ secrets.ACCESS_KEY_SECRET }}"

# 1.2 Buid and push image to ACR
- name: Build and push image to ACR
run: |
docker build --tag "$REGISTRY/$NAMESPACE/$IMAGE:$TAG" .
docker push "$REGISTRY/$NAMESPACE/$IMAGE:$TAG"

# 1.3 Scan image in ACR
- name: Scan image in ACR
uses: aliyun/acr-scan@v1
with:
region-id: "${{ env.REGION_ID }}"
access-key-id: "${{ secrets.ACCESS_KEY_ID }}"
access-key-secret: "${{ secrets.ACCESS_KEY_SECRET }}"
repository: "${{ env.NAMESPACE }}/${{ env.IMAGE }}"
tag: "${{ env.TAG }}"

# 2.1 (Optional) Login to ACR EE
- uses: actions/checkout@v2
- name: Login to ACR EE with the AccessKey pair
uses: aliyun/acr-login@v1
with:
login-server: "https://${{ env.ACR_EE_REGISTRY }}"
region-id: "${{ env.REGION_ID }}"
access-key-id: "${{ secrets.ACCESS_KEY_ID }}"
access-key-secret: "${{ secrets.ACCESS_KEY_SECRET }}"
instance-id: "${{ env.ACR_EE_INSTANCE_ID }}"

# 2.2 (Optional) Build and push image ACR EE
- name: Build and push image to ACR EE
run: |
docker build -t "$ACR_EE_REGISTRY/$ACR_EE_NAMESPACE/$ACR_EE_IMAGE:$TAG" .
docker push "$ACR_EE_REGISTRY/$ACR_EE_NAMESPACE/$ACR_EE_IMAGE:$TAG"
# 2.3 (Optional) Scan image in ACR EE
- name: Scan image in ACR EE
uses: aliyun/acr-scan@v1
with:
region-id: "${{ env.REGION_ID }}"
access-key-id: "${{ secrets.ACCESS_KEY_ID }}"
access-key-secret: "${{ secrets.ACCESS_KEY_SECRET }}"
instance-id: "${{ env.ACR_EE_INSTANCE_ID }}"
repository: "${{ env.ACR_EE_NAMESPACE}}/${{ env.ACR_EE_IMAGE }}"
tag: "${{ env.ACR_EE_TAG }}"

# 3.1 Set ACK context
- name: Set K8s context
uses: aliyun/ack-set-context@v1
with:
access-key-id: "${{ secrets.ACCESS_KEY_ID }}"
access-key-secret: "${{ secrets.ACCESS_KEY_SECRET }}"
cluster-id: "${{ env.ACK_CLUSTER_ID }}"

# 3.2 Deploy the image to the ACK cluster
- name: Set up Kustomize
run: |-
curl -s "https://raw.githubusercontent.com/kubernetes-sigs/kustomize/master/hack/install_kustomize.sh" | bash /dev/stdin 3.8.6
- name: Deploy
run: |-
./kustomize edit set image REGISTRY/NAMESPACE/IMAGE:TAG=$REGISTRY/$NAMESPACE/$IMAGE:$TAG
./kustomize build . | kubectl apply -f -
kubectl rollout status deployment/$ACK_DEPLOYMENT_NAME
kubectl get services -o wide
81 changes: 81 additions & 0 deletions .github/workflows/aws.yml
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# This workflow will build and push a new container image to Amazon ECR,
# and then will deploy a new task definition to Amazon ECS, when a release is created
#
# To use this workflow, you will need to complete the following set-up steps:
#
# 1. Create an ECR repository to store your images.
# For example: `aws ecr create-repository --repository-name my-ecr-repo --region us-east-2`.
# Replace the value of `ECR_REPOSITORY` in the workflow below with your repository's name.
# Replace the value of `aws-region` in the workflow below with your repository's region.
#
# 2. Create an ECS task definition, an ECS cluster, and an ECS service.
# For example, follow the Getting Started guide on the ECS console:
# https://us-east-2.console.aws.amazon.com/ecs/home?region=us-east-2#/firstRun
# Replace the values for `service` and `cluster` in the workflow below with your service and cluster names.
#
# 3. Store your ECS task definition as a JSON file in your repository.
# The format should follow the output of `aws ecs register-task-definition --generate-cli-skeleton`.
# Replace the value of `task-definition` in the workflow below with your JSON file's name.
# Replace the value of `container-name` in the workflow below with the name of the container
# in the `containerDefinitions` section of the task definition.
#
# 4. Store an IAM user access key in GitHub Actions secrets named `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY`.
# See the documentation for each action used below for the recommended IAM policies for this IAM user,
# and best practices on handling the access key credentials.

on:
release:
types: [created]

name: Deploy to Amazon ECS

jobs:
deploy:
name: Deploy
runs-on: ubuntu-latest
environment: production

steps:
- name: Checkout
uses: actions/checkout@v2

- name: Configure AWS credentials
uses: aws-actions/configure-aws-credentials@v1
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: us-east-2

- name: Login to Amazon ECR
id: login-ecr
uses: aws-actions/amazon-ecr-login@v1

- name: Build, tag, and push image to Amazon ECR
id: build-image
env:
ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
ECR_REPOSITORY: my-ecr-repo
IMAGE_TAG: ${{ github.sha }}
run: |
# Build a docker container and
# push it to ECR so that it can
# be deployed to ECS.
docker build -t $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG .
docker push $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG
echo "::set-output name=image::$ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG"

- name: Fill in the new image ID in the Amazon ECS task definition
id: task-def
uses: aws-actions/amazon-ecs-render-task-definition@v1
with:
task-definition: task-definition.json
container-name: sample-app
image: ${{ steps.build-image.outputs.image }}

- name: Deploy Amazon ECS task definition
uses: aws-actions/amazon-ecs-deploy-task-definition@v1
with:
task-definition: ${{ steps.task-def.outputs.task-definition }}
service: sample-app-service
cluster: default
wait-for-service-stability: true
50 changes: 50 additions & 0 deletions .github/workflows/azure.yml
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# This workflow will build and push a node.js application to an Azure Web App when a release is created.
#
# This workflow assumes you have already created the target Azure App Service web app.
# For instructions see https://docs.microsoft.com/azure/app-service/app-service-plan-manage#create-an-app-service-plan
#
# To configure this workflow:
#
# 1. For Linux apps, add an app setting called WEBSITE_WEBDEPLOY_USE_SCM and set it to true in your app **before downloading the file**.
# For more instructions see: https://docs.microsoft.com/azure/app-service/configure-common#configure-app-settings
#
# 2. Set up a secret in your repository named AZURE_WEBAPP_PUBLISH_PROFILE with the value of your Azure publish profile.
# For instructions on obtaining the publish profile see: https://docs.microsoft.com/azure/app-service/deploy-github-actions#configure-the-github-secret
#
# 3. Change the values for the AZURE_WEBAPP_NAME, AZURE_WEBAPP_PACKAGE_PATH and NODE_VERSION environment variables (below).
#
# For more information on GitHub Actions for Azure, refer to https://github.com/Azure/Actions
# For more samples to get started with GitHub Action workflows to deploy to Azure, refer to https://github.com/Azure/actions-workflow-samples
on:
release:
types: [created]

env:
AZURE_WEBAPP_NAME: your-app-name # set this to your application's name
AZURE_WEBAPP_PACKAGE_PATH: '.' # set this to the path to your web app project, defaults to the repository root
NODE_VERSION: '10.x' # set this to the node version to use

jobs:
build-and-deploy:
name: Build and Deploy
runs-on: ubuntu-latest
environment: production
steps:
- uses: actions/checkout@v2
- name: Use Node.js ${{ env.NODE_VERSION }}
uses: actions/setup-node@v2
with:
node-version: ${{ env.NODE_VERSION }}
- name: npm install, build, and test
run: |
# Build and test the project, then
# deploy to Azure Web App.
npm install
npm run build --if-present
npm run test --if-present
- name: 'Deploy to Azure WebApp'
uses: azure/webapps-deploy@v2
with:
app-name: ${{ env.AZURE_WEBAPP_NAME }}
publish-profile: ${{ secrets.AZURE_WEBAPP_PUBLISH_PROFILE }}
package: ${{ env.AZURE_WEBAPP_PACKAGE_PATH }}
23 changes: 23 additions & 0 deletions .github/workflows/c-cpp.yml
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name: C/C++ CI

on:
push:
branches: [ master ]
pull_request:
branches: [ master ]

jobs:
build:

runs-on: ubuntu-latest

steps:
- uses: actions/checkout@v2
- name: configure
run: ./configure
- name: make
run: make
- name: make check
run: make check
- name: make distcheck
run: make distcheck
46 changes: 46 additions & 0 deletions .github/workflows/cmake.yml
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name: CMake

on: [push]

env:
# Customize the CMake build type here (Release, Debug, RelWithDebInfo, etc.)
BUILD_TYPE: Release

jobs:
build:
# The CMake configure and build commands are platform agnostic and should work equally
# well on Windows or Mac. You can convert this to a matrix build if you need
# cross-platform coverage.
# See: https://docs.github.com/en/free-pro-team@latest/actions/learn-github-actions/managing-complex-workflows#using-a-build-matrix
runs-on: ubuntu-latest

steps:
- uses: actions/checkout@v2

- name: Create Build Environment
# Some projects don't allow in-source building, so create a separate build directory
# We'll use this as our working directory for all subsequent commands
run: cmake -E make_directory ${{github.workspace}}/build

- name: Configure CMake
# Use a bash shell so we can use the same syntax for environment variable
# access regardless of the host operating system
shell: bash
working-directory: ${{github.workspace}}/build
# Note the current convention is to use the -S and -B options here to specify source
# and build directories, but this is only available with CMake 3.13 and higher.
# The CMake binaries on the Github Actions machines are (as of this writing) 3.12
run: cmake $GITHUB_WORKSPACE -DCMAKE_BUILD_TYPE=$BUILD_TYPE

- name: Build
working-directory: ${{github.workspace}}/build
shell: bash
# Execute the build. You can specify a specific target with "--target <NAME>"
run: cmake --build . --config $BUILD_TYPE

- name: Test
working-directory: ${{github.workspace}}/build
shell: bash
# Execute tests defined by the CMake configuration.
# See https://cmake.org/cmake/help/latest/manual/ctest.1.html for more detail
run: ctest -C $BUILD_TYPE
23 changes: 23 additions & 0 deletions .github/workflows/erlang.yml
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name: Erlang CI

on:
push:
branches: [ master ]
pull_request:
branches: [ master ]

jobs:

build:

runs-on: ubuntu-latest

container:
image: erlang:22.0.7

steps:
- uses: actions/checkout@v2
- name: Compile
run: rebar3 compile
- name: Run tests
run: rebar3 do eunit, ct
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