The same environment everywhere
Development, testing and production rely on the same image, which eliminates most “it works on my machine” discrepancies.
Expertise · Docker
Docker Containerization: Reproducible, Containerized Applications
Docker makes application environments reproducible across development, testing and deployment. Our teams containerize the applications they build or take over, including AI services, for predictable production releases and documented operations.
Understanding the technology
Docker in your project.
Docker packages an application and its dependencies into an image, which then runs as a container. This makes it easier to reproduce the same environment across development, testing and deployment. Persistent data, secrets and communication between services still need to be organized around the container.
The benefits for your product
Why choose Docker?
Used in service of your applications, Docker brings concrete benefits throughout the software lifecycle.
Lightweight isolation
Containers share the host kernel. They start quickly and use fewer resources than a virtual machine, while still isolating processes and resources.
Portability
The same image runs on a developer workstation, a server, a public cloud or an orchestrator.
A foundation for scaling
Containers are easy to replicate behind a load balancer and can be orchestrated with Kubernetes when the need justifies it.
A pillar of continuous delivery
The images built in the CI/CD pipeline are the same ones that get deployed, which makes releases reproducible.
What we cover
The work we take on.
Images
Define dependencies, build steps and configurations.
Services
Organize communication, volumes and persistence needs.
Runtime
Manage secrets, permissions and container health checks.
Our Docker expertise
The Docker ecosystem we master.
Images & Dockerfile
Docker Engine, multi-stage builds, minimal and up-to-date base images, optimized instructions and vulnerability scanning.
Docker Compose
Multi-container environments for development (services, networks, volumes, variables) and simple single-host deployments, with health checks and restart policies.
Registries
Docker Hub, private registries (Docker Registry, Harbor, Artifactory), versioning and tagging strategies, image cleanup.
Networking & storage
Bridge, host or overlay networks, named volumes and mounts, database persistence, backup and restore.
Docker and AI
Containerizing AI services to take them to production.
An AI POC often runs on the machine of the person who wrote it. Containerizing it is one of the first steps toward turning it into a service: pinned dependencies, configuration and API keys kept out of the image, health checks, usable logs, and the same image tested and then deployed.
Our teams apply these practices both to services that call models (OpenAI, Claude, Gemini) and to document indexing pipelines. See our AI solutions for business.
In the field
From technology to real-world use.
When taking over an application that is hard to install, we document its dependencies, build the image and describe the associated services. A new developer should be able to start the project with a known procedure. The same artifacts can then be tested before deployment, with the configuration specific to each environment kept separate.
The choices that matter
The choices to examine before building.
An oversized or poorly maintained image increases dependencies and slows down updates. We review process permissions, volumes and health checks. Backing up a database is not just a matter of keeping the container, and a containerized application still requires an operations strategy.
From work to deliverables
Delivered work your team can take over.
The scope of the engagement specifies the components to build or take over and the acceptance criteria. We prepare what is needed to understand the changes, verify them and continue the work. Containerization can be a targeted workstream or part of the work of a dedicated team that builds and runs your product.
- Versioned configurations
- Documented delivery pipeline
- Monitoring and operating procedures
Frequently asked questions
Docker: your questions.
What is Docker and why use it?
Docker is a containerization platform that runs an application and its dependencies in an isolated, portable environment. It reduces compatibility issues between environments and simplifies deployments.
How does Docker fit into an application’s lifecycle?
It plays a role at every stage. Developers work in the same environment as production, the CI/CD pipeline builds and tests the image, and that same image is then deployed.
What is the difference between Docker and a virtual machine?
A container shares the host system’s kernel; it is lighter and starts faster. A virtual machine includes a full operating system and provides stronger isolation, which is useful for certain security contexts or legacy applications.
How can you reduce Docker image size?
Multi-stage builds, minimal base images, a .dockerignore file, grouped instructions and removal of temporary files. A smaller image downloads faster and exposes fewer dependencies.
Is Docker safe in production?
Yes, with good practices — non-root processes, minimal and up-to-date images, vulnerability scanning, secrets kept out of the image, network isolation and resource limits.
How do you manage persistent data with Docker?
With named volumes or mounts, and a tested backup and restore strategy. The container should remain replaceable; the data must survive its replacement.
When should you use Docker Compose rather than Kubernetes?
Docker Compose is suited to local development and simple applications on a single host. Kubernetes is justified for high availability, autoscaling and multiple services in production.
How do you monitor containerized applications?
With health checks, metrics collection (cAdvisor, Prometheus, Grafana), centralized logging and, if needed, an APM tool.
Can you containerize an AI POC to take it to production?
Yes. We pin the dependencies, move keys and configuration out of the image, add health checks and logs, then integrate the service into the delivery pipeline and monitoring.
Let’s talk about your technical context.
Tell us about the application, the issue to address and the known constraints. We will review the dependencies and the initial scope of work with your team.