Docker Development
Docker packages an application and its runtime dependencies into a portable image that runs identically across environments. We write Dockerfiles, configure Docker Compose for local development, optimize images for production, and establish the container practices a team can maintain.
Capabilities
What we do with Docker
New containerization
Dockerfile Authoring
Writing production-quality Dockerfiles for Node.js, Python, Java, and other runtimes. Multi-stage builds that keep production images small by separating the build environment from the runtime environment.
Dev environment
Docker Compose for Local Development
Docker Compose configurations that let a developer start the full application stack — application, database, cache, queues — with a single command, in an environment that matches production closely enough to trust.
Size · Layers · Cache
Image Optimization
Reducing image size through layer ordering, .dockerignore configuration, minimal base images (Alpine or distroless), and removing unnecessary build tools from the final image stage.
Non-root · Scanning
Security Hardening
Running containers as non-root users, removing unnecessary packages, scanning images with Trivy for known CVEs, and configuring read-only root filesystems where the application supports it.
Lift and containerize
Existing Application Containerization
Taking an application that currently runs on bare metal or a VM and containerizing it — assessing dependencies, handling configuration as environment variables, and addressing persistent storage requirements.
Build · Push · Deploy
CI/CD Image Build Pipeline
Automated image builds in CI, pushed to ECR or another registry on merge, with image tag strategy (commit SHA, semantic version, or both) and deployment trigger configuration.
Our approach
Layer order determines cache efficiency
Docker builds layers from top to bottom and caches each layer. If a line early in the Dockerfile changes, every subsequent layer is rebuilt. We order Dockerfile instructions so that the instructions that change most frequently — copying application code — come last, and the instructions that change rarely — installing system packages — come first. This keeps builds fast in CI.
Multi-stage builds for production images
A build environment needs compilers, package managers, and development headers. A production image does not. Multi-stage builds use one stage to compile and another to assemble the runtime image, copying only the build output into the final stage. The production image is smaller, has a reduced attack surface, and contains no unnecessary tooling.
Containers run as non-root
A container that runs as root is a container where a process escape gives the attacker root access to the host. We create a dedicated application user in the Dockerfile and switch to it before the CMD instruction. This is not optional for production workloads.
Scan images in CI
We integrate Trivy or a comparable scanner into the CI pipeline to catch known CVEs in base images and dependencies before images are pushed to a registry. An unscanned image is an unknown risk.
All engineering work is done by US-based engineers. We do not offshore any development or architecture work.
Part of our container practice
FAQ
Common questions
Virginia · United States
Need Docker expertise?
If you are containerizing an application for the first time or need to improve an existing container setup, reach out and we will assess the requirements.