Docker

A Python web application in a container is only as good as its process model. Running uvicorn main:app inside a Docker image works for development, but it leaves every CPU core beyond the first idle and provides no process supervision when a worker crashes. The production pattern pairs a process manager (Gunicorn) with an async…

Compiled languages produce a single artifact that either runs or does not. There is no interpreter, no virtual environment, no dependency resolution at startup. This property makes them ideal candidates for minimal container images: the build stage can be heavy, but the runtime stage needs only the binary and whatever shared libraries it dynamically links…

A Dev Container is not a production image with debugging tools bolted on. It is a separate artifact defined by a structured metadata file—devcontainer.json—that tells the editor how to build, start, and configure a containerized workspace . The distinction matters: production images should be minimal and hardened; development images should include compilers, debuggers, language servers,…

A CI pipeline for Docker images is not a single build step. It is a sequence of decisions: build the image without pushing, run the container to verify it starts, check a health endpoint, then rebuild with the same cache and push the tested artifact. GitHub Actions provides the primitives for this sequence through Docker’s…

The difference between a Docker CI pipeline that finishes in thirty seconds and one that takes four minutes is almost never the code. It is whether the layer cache survived from the previous run. GitHub-hosted runners are ephemeral: every job starts with an empty filesystem, and BuildKit’s local cache—the default mechanism that makes local builds…

The choice between DinD and DooD is a choice about where the Docker daemon lives and who controls it. Docker-in-Docker runs a nested daemon inside the CI job container, giving each job its own isolated Docker environment with its own image cache, network, and storage. Docker-outside-of-Docker mounts the host’s Docker socket into the job container,…

GitOps is a deployment model in which the desired state of the infrastructure is stored in a Git repository, and a controller continuously reconciles the running state with the committed state. The model has two implementations that are often confused: pull-based reconciliation, where an in-cluster agent watches Git and applies changes, and image-update automation, where…

Traefik is a reverse proxy that discovers Docker containers through the Docker socket and routes traffic to them based on labels attached to the container itself. The routing configuration is not a separate file that must be edited when a service is added; it is a set of traefik.http.routers.* and traefik.http.services.* labels on the container,…

Docker’s persistence model creates a specific backup problem: named volumes and bind mounts hold the data that matters, but the container’s writable layer is disposable, and the image is reproducible from a registry. A backup strategy that copies the entire /var/lib/docker directory is fragile and often inconsistent; a strategy that stops the stack and tars…

A packet that leaves a container and reaches the internet passes through at least four distinct processing stages, and each stage is implemented by a different kernel subsystem. The veth pair is the virtual cable between the container’s network namespace and the host’s. The Linux bridge is the switch that connects the host-side veth to…