Module 3 · Project 2: Containerise, Deploy to the Cloud and Automate with CI/CD

OBJECTIVE: package the Project 1 service in Docker, run the full app (API + front end + vector database + cache) with one command, deploy it to the cloud, and set up GitHub Actions so every merge is tested and deployed automatically. WHAT WE COVER (in project order): • Docker: images, containers, Dockerfile, layers, .dockerignore, small and safe images • Docker Compose: running several services together • Container registries • Deploying to a platform (Render or Railway) and to Google Cloud Run • Secrets, health checks, logs and rollbacks in the cloud • CI with GitHub Actions: tests and checks on every pull request • CD: build and deploy automatically on merge • Kubernetes basics (when you outgrow simple hosting) AFTER THIS MODULE YOU CAN: • Run any AI app the same way on any machine with Docker • Deploy it to the cloud with secrets, health checks and rollbacks • Set up a CI/CD pipeline that tests and deploys automatically TOOLS: Docker, Docker Compose, GitHub Actions, Render/Railway, Google Cloud (Cloud Run, Artifact Registry, Secret Manager), kubectl (glimpse).