Lab: Building Container Images
Take a working but naïve Dockerfile and progressively improve it into a production-grade image. Each section introduces one technique, applied to a real Python Flask app, so you can see the impact directly.
Launch the lab
{{< labspace-launch image="dockersamples/labspace-building-images" >}}
What you'll learn
By the end of this Labspace, you will have completed the following:
- Read an image's layer history and understand the layer cleanup pitfall
- Restructure a Dockerfile for fast, cache-efficient incremental builds
- Write a
.dockerignorefile and run containers as a non-root user - Use multi-stage builds to run tests as a build gate and dramatically reduce image size
- Choose the right base image for production, including Docker Hardened Images
- Inject secrets safely at build time using
--mount=type=secret
Modules
| # | Module | Description |
|---|---|---|
| 1 | Welcome & Your First Build | Explore the sample app and build the initial image |
| 2 | Understanding Image Layers | Inspect layers with docker history and see the layer cleanup pitfall |
| 3 | Dockerfile Best Practices | Fix cache ordering, add .dockerignore, and switch to a non-root user |
| 4 | Multi-Stage Builds | Run tests as a build gate and use a slim base for the production stage |
| 5 | Choosing a Base Image | Compare slim, Alpine, and Docker Hardened Images |
| 6 | Build Secrets | Show why ARG leaks secrets and use --mount=type=secret safely |
| 7 | Wrap-up | Review the complete best-practices checklist and next steps |
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