Containerization has moved from an emerging trend to a baseline expectation in modern software delivery. If your team deploys applications to the cloud, understanding Docker and Kubernetes is no longer optional — it is a core competency. This primer covers the essential concepts and explains how the two technologies fit together.
What Containers Actually Solve
Traditional deployments rely on the host operating system’s libraries and configuration. That creates subtle differences between development, staging, and production environments — differences that surface as bugs at the worst possible time. A container packages an application together with its runtime, libraries, and configuration into a single image. That image runs identically whether it is on a developer laptop, a CI server, or a production cluster.
Docker: Building and Running Containers
Docker provides the tooling to build container images from a Dockerfile, a simple text file that describes each layer of the image. Best practices include using minimal base images like Alpine to reduce surface area, leveraging multi-stage builds to keep production images lean, and never baking secrets into image layers. Once built, images are pushed to a registry — Docker Hub, GitHub Container Registry, or a private registry — and can be pulled by any environment that runs the Docker runtime.
Kubernetes: Orchestrating at Scale
Running a single container is straightforward. Running hundreds of containers across multiple machines, keeping them healthy, scaling them up during traffic spikes, and rolling out updates without downtime — that is orchestration, and it is where Kubernetes comes in. Kubernetes groups containers into pods, manages networking between them with services, and uses deployments to handle rolling updates and rollbacks. Declarative YAML manifests describe the desired state, and the Kubernetes control plane works continuously to reconcile actual state with that declaration.
When Kubernetes Is Overkill
Kubernetes adds operational complexity. For small teams running a handful of services, managed container platforms like AWS ECS, Google Cloud Run, or Azure Container Apps can provide most of the benefits with far less overhead. Evaluate your team’s capacity honestly before committing to a full Kubernetes setup. Starting with a simpler platform and migrating later is a valid strategy.
Getting Started
Begin by containerizing one service. Write a Dockerfile, build the image, and run it locally. Then push it to a registry and deploy it to a managed container platform. Once you are comfortable with the container lifecycle, explore Kubernetes using a local cluster tool like Minikube or kind. Incremental adoption beats big-bang migrations every time.