CI
Continuous Integration can build and test Docker images automatically whenever code changes are pushed.
Lesson 22
CI/CD with Docker
This page explains how Docker becomes a repeatable artifact in automation pipelines instead of only a tool you run manually on your laptop.
CD
Continuous Delivery or Deployment can tag, push, and roll out images without repeating the same manual steps each time.
Main value
Docker makes automation more consistent because the same image can move from build to test to deployment.
Simple pipeline flow
Code push
Build image
Run checks
Push image
Deploy image
Why Docker fits pipelines
One image
Same artifact in each stage
Less environment mismatch
What CI usually does with Docker
- Builds the image from the Dockerfile.
- Runs linting, tests, or basic verification.
- Confirms the image can be created correctly.
- May fail the pipeline if the container build is broken.
What CD usually does with Docker
- Tags the image clearly.
- Pushes it to a registry.
- Promotes or deploys the same artifact later.
- Reduces manual deployment mistakes.
Example command sequence
docker build -t my-app:build-42 .
docker test my-app:build-42
docker tag my-app:build-42 registry/my-app:1.4.0
docker push registry/my-app:1.4.0
The exact tools differ between platforms, but the idea stays the same: build once, move forward with confidence.
Common beginner mistakes
- Testing one image but deploying a different one.
- Using unclear tags everywhere.
- Relying only on local manual checks.
- Skipping automated Docker builds in the pipeline.
CI/CD memory guide
Build once
Docker gives you a clear artifact.
Docker gives you a clear artifact.
Test the same artifact
This reduces mismatch between steps.
This reduces mismatch between steps.
Push the same artifact
Now the registry stores exactly what passed checks.
Now the registry stores exactly what passed checks.
Deploy the same artifact
That is one of Docker’s strongest workflow advantages.
That is one of Docker’s strongest workflow advantages.
Next page: Lesson 23 explains how logs and monitoring help you observe containers after deployment.