build-push-action VS starter-workflows

Starting with version 4, docker/build-push-action builds images using the OCI format by default. OCI (Open Container Initiative) is the modern standard that is supported by AWS ECR. However, AWS Lambda does not support OCI image manifests. Lambda only accepts the older Docker v2 schema: application/vnd.docker.distribution.manifest.v2+json

docker/build-push-action

Does build-push-action solve this? I haven’t used their multi-arch configs but I was under the impression that it was pretty smooth.

https://github.com/docker/build-push-action

To publish images to Docker Hub, I use the docker/build-push-action@v6, where I specify:

Docker Build and Publish:

## Local Cache This method leverages local storage for caching Docker layers. The downside is that old cache entries aren’t deleted automatically, so the cache size might increase over time. A temporary fix involves moving and cleaning the cache after each build. ```yaml //".github/workflows/build.yml" name: Docker Build on: push: jobs: docker: runs-on: ubuntu-latest steps: - name: Set up Docker Buildx uses: docker/setup-buildx-action@v3 // highlight-start - name: Cache Docker layers uses: actions/cache@v4 with: path: /tmp/.buildx-cache key: ${{ runner.os }}-buildx-${{ github.sha }} restore-keys: | ${{ runner.os }}-buildx- // highlight-end - name: Login to Docker Hub uses: docker/login-action@v3 with: username: ${{ vars.DOCKERHUB_USERNAME }} password: ${{ secrets.DOCKERHUB_TOKEN }} // highlight-start - name: Build and push uses: docker/build-push-action@v6 with: push: true tags: user/app:latest cache-from: type=local,src=/tmp/.buildx-cache cache-to: type=local,dest=/tmp/.buildx-cache-new,mode=max // highlight-end - # Temp fix # https://github.com/docker/build-push-action/issues/252 # https://github.com/moby/buildkit/issues/1896 name: Move cache run: | rm -rf /tmp/.buildx-cache mv /tmp/.buildx-cache-new /tmp/.buildx-cache

Configuring the GitHub Actions Workflow We set up a GitHub Actions workflow to automate the integration and deployment process. The integration workflow is triggered on every pull request while the deployment workflow was triggered upon the completion of the build and push workflow for docker images gotten from the marketplace. It used the appleboy/ssh-action to execute the deployment script on the server.

We use the docker/build-push-action to build the application image. In addition to setting the correct tag, the image build step must also provide a label matching your service name. Because the image should be pushed to your container registry, we set push: true, and because we want ludicrous build speed we instruct the build step to utilize the GitHub Actions cache.

name: Lint and Dockerize the app on: push: branches: [master] pull_request: branches: [master] env: # Use docker.io for Docker Hub if empty REGISTRY: docker.io # github.repository as / IMAGE_NAME: ${{ github.repository }} jobs: build: runs-on: ubuntu-latest permissions: contents: read packages: write steps: - name: Checkout repository uses: actions/checkout@v2 - name: Set up Google Cloud uses: google-github-actions/[email protected] with: project_id: ${{ secrets.GCP_PROJECT_ID }} service_account_key: ${{ secrets.GCP_SA_KEY }} # Login against a Docker registry except on PR # https://github.com/docker/login-action - name: Log into registry ${{ env.REGISTRY }} # if: github.event_name != 'pull_request' uses: docker/login-action@v1 with: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} # Extract metadata (tags, labels) for Docker # https://github.com/docker/metadata-action #- name: Extract Docker metadata # id: meta # uses: docker/metadata-action@98669ae865ea3cffbcbaa878cf57c20bbf1c6c38 # with: # images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} # Build and push Docker image with Buildx (don't push on PR) # https://github.com/docker/build-push-action - name: Build and push Docker image uses: docker/build-push-action@v2 with: context: ./ tags: ${{ secrets.DOCKER_USERNAME }}/magga:latest push: true file: ./Dockerfile - name: Image digest run: echo

3. CI/CD Pipelines & Automated Tests

For this project, I used GitHub Actions as my CI/CD tool due to its seamless integration with GitHub repositories and support for AWS.

GitHub Actions for CI/CD pipelines

If your code lives on GitHub (which it probably does), GitHub Actions should be your go-to for CI/CD.

My base target is used for development use, but my production target is used for production use. I'm using a GitHub Actions workflow to checkout my code, installing dependencies without development dependencies, and building my application. When that's done, I build the Docker image and send it to my container registry.

CI/CD: GitHub Actions, GitLab CI, CircleCI, ArgoCD

In this post, I will share WebRTC.ventures' best practices in automating the deployment of AI-powered voice assistants for Amazon Connect, moving beyond manual, click-by-click setups to a robust, scalable Infrastructure as Code (IaC) approach. We’ll explore how to manage both static and dynamic resources, leverage tools like Terraform and AWS Serverless Application Model (SAM), and even set up an automated deployment pipeline using Github Actions to deploy your conversational IVR solutions efficiently.

Github Actions (Popular)

The Python Pulumi code is deployed with GitHub Actions. This leverages static credentials for AWS embedded as repository secrets. I have implemented two workflows:

When Microsoft announced the App Center shutdown last year, they recommended an array of alternative tools from elsewhere in their developer toolkit and beyond to replace its capabilities. Users seeking an alternative to App Center's hosted build automation, or App Store deployment, capabilities can look to Azure DevOps Pipelines or GitHub Actions. For cloud-based on-device testing, they recommend external tool BrowserStack. And for internal and test distribution, they simply steer users towards either TestFlight or Google Play Console.