Case study — Docker explained: images, containers and volumes
Real-world implementation
Context
Continuous deployment pipeline for a SaaS platform serving 40 000 users
The challenge
The team's Docker images averaged 3.8 GB and took 18 minutes to build and push in CI. Deployment rollbacks required manual intervention, and the production image was identical to the development image — including build tools and source code.
Our approach
We converted each service to a multi-stage Dockerfile: a builder stage using the full Node/Python SDK, and a runner stage based on distroless. A named volume was added for the PostgreSQL data directory. Trivy scanning was integrated as a required CI check. Image tags were pinned to digests in all environment manifests.
Results
Image size dropped from 3.8 GB to 320 MB (−92 %). CI build time fell from 18 minutes to 4 minutes, thanks to layer caching and the smaller image. Zero critical CVEs in the runner stage. Rollbacks became automated via health-check-gated deployments.
Ready to build?
Tuplify Studio turns these concepts into working software.
Discuss your project