Docker: From Dev to Production
"Works on my machine" is solved. We standardize Dockerfiles, optimize layers, scan for vulnerabilities, and deploy with confidence across environments.
What we deliver with Docker
Dockerfile standards
Multi-stage builds, pinned base images, non-root users, and a shared template, so every service builds the same way and reviews stay short.
Image size and build speed
Layer ordering, build caches, and minimal runtime images that cut pull times and make deploys and rollbacks predictable.
Vulnerability scanning
Automated scans in the pipeline with a severity threshold and an owner, plus a policy for base image refreshes instead of annual patching.
Registry and tagging discipline
Immutable tags tied to commits, retention rules, and no reliance on latest in any environment that matters.
Local to production parity
Compose setups that mirror real dependencies, so developers catch configuration problems locally rather than during a release.
How we work with Docker
Containers are a packaging standard, and packaging standards only help if they are uniform. We publish one Dockerfile template per language, wire scanning into CI, and treat a base image bump as a routine change rather than a project.
The discipline that pays off most is tagging. Immutable, commit-linked tags plus a small retention policy mean an incident review can reconstruct exactly what ran, which is usually the first question asked.
Docker in production: where it breaks
The same handful of problems show up on almost every engagement. Naming them early is cheaper than discovering them at 2am.
Latest tags everywhere
The same deploy produces different behaviour a week apart. Pinned digests plus a scheduled refresh make builds reproducible.
Secrets baked into image layers
Deleting a file in a later layer does not remove it from history. Secrets belong in the runtime environment or a secret manager.
Fat images and slow rollouts
A 2GB image slows every scale event. Multi-stage builds and slim runtimes typically cut size by more than half.
When to use Docker
Teams standardising build and deploy before moving to Kubernetes.
Applications with environment-specific configuration drift.
Regulated deployments needing reproducible, signed artefacts.