Page 6 - Docker

A generic blue green deployment simply swaps two container versions. For Magento that is not enough, because indexers, cache, sessions and database migrations complicate the color switch. This article shows how blue green deployments for Magento in containers are built so the traffic switch actually happens without downtime and without inconsistent data.

Magento 2 needs a precisely tuned service stack. PHP-FPM, Nginx, MariaDB, Redis, Elasticsearch or OpenSearch, and a Node container for frontend builds: each of these services has specific configuration requirements that differ in Docker from a classic server installation. Knowing these differences is what lets you build a stable and performant Magento Docker stack.

Containerized databases behave differently from classic database installations: init directories, volume persistence and health check synchronization are concepts that need to be understood before the first production container goes live. Anyone who skips these fundamentals ends up fighting data loss, race conditions and non-reproducible development environments later on.

docker stack deploy turns a familiar compose file into a complete, highly available Swarm stack, including networks, volumes, secrets and configs in a single rollout. Knowing the differences between local compose and stack deployment helps you avoid the most common pitfalls when moving from development to production.

Anyone who compiles on production servers couples the build environment and the runtime environment in a way that leads to non-reproducible deployments. Docker release images with multi-stage builds cleanly separate these phases, deliver lean artifacts, and turn every deployment into a controllable, reversible operation.

A server change, a hosting provider switch, or consolidating multiple Docker hosts eventually requires moving a running database container from one machine to another. Depending on data volume, downtime tolerance, and network connectivity between hosts, logical dumps, raw volume copies via rsync, or a replication cutover each suit different scenarios, with their own pitfalls around consistency and integrity.

Running every container in the default bridge network means giving up name resolution, isolation between projects and the ability to cut containers off from the internet on purpose. A dedicated bridge network per project solves exactly these three problems with a few lines of configuration.

A container is not a virtual machine, it is an isolated process sharing the same kernel with the host. Container escape prevention means consistently hardening exactly that boundary: no unnecessary privileges, no mounted sockets, active seccomp and AppArmor profiles, and a current kernel, so a compromised container never becomes a stepping stone to the host.

A Docker image is not a black box. It is an ordered sequence of read-only layers that together form the container's filesystem. Anyone who understands how layers are built, why the build cache gets invalidated, and how registries distribute images efficiently writes Dockerfiles that build fast and produce small images.

Integration and end-to-end tests rarely fail because of the test logic itself, they fail because of the environment: the wrong database version, services that never started, race conditions during startup. Docker Compose solves exactly that, with declared dependencies, healthchecks and network isolation that make every test run reproducible.