Page 9 - Docker

Without a systematic Docker cleanup strategy, CI runners and production servers fill up within weeks with unused images, orphaned volumes, and stale build caches. The right automation concept prevents disk exhaustion without accidentally deleting important data.

An uncontrolled flood of latest tags and anonymous Docker Hub pulls puts every production environment at risk. Teams that run a private Docker registry, adopt meaningful image versions, and define retention policies create traceable, reproducible builds and significantly reduce the risk of outages.

Before a service runs in production with multiple replicas in Kubernetes or Docker Swarm, it is worth testing locally with deploy.replicas in Docker Compose. This way, port conflicts, shared volumes and load balancing behavior can be uncovered on the development machine, instead of noticing them only after a production rollout.

Bare metal, virtual machines and containers form a spectrum of isolation, overhead and deployment speed, not a simple either-or decision. This article explains when full hardware control is necessary, when hypervisor isolation makes sense for multi-tenancy, and when containers are the faster choice, along with the hybrid approach that most production hosting setups actually run to balance cost, security and operational effort.

Packaging a TypeScript project into a Docker image without a multi-stage build ships the entire TypeScript compiler, every devDependency and the source tree straight into production. A clean multi-stage build separates compilation, dependency pruning and runtime into three distinct stages, noticeably reducing image size, attack surface and deployment time.

Static code analysis and dependency checking are among the security features GitLab ships built in, and they can be wired into an existing .gitlab-ci.yml with just a few lines. The real work starts only afterwards: results need to be assessed, real vulnerabilities need to be prioritized, and false alarms need to be suppressed cleanly, without the security noise eroding developer trust in the tooling. This article covers integrating SAST and Dependency Scanning into an existing PHP or Node pipeline, and the practical handling of the findings that come out of it.

Every time a container is started with a published port, Docker silently rewrites the host's iptables rule set. This automation is convenient, but it regularly causes hard-to-trace conflicts once custom firewall rules or tools like firewalld enter the picture.

Containers share the host kernel, so they are not an automatic security win over classic servers. This article shows how minimal base images, non-root users, automated vulnerability scanning in the CI pipeline, secure secrets handling without image layer leaks, and a hardened runtime with a read-only filesystem and reduced Linux capabilities make Docker deployments for Magento and PHP projects noticeably safer.

A Varnish, Redis and OpenSearch sidecar with default configuration runs, but rarely delivers the performance a Magento shop needs under real load. This article shows how these three sidecars are deliberately fine-tuned as containers, from VCL rules through eviction policies to JVM heap sizing, instead of relying on factory defaults.

Remote development in PhpStorm is more than SFTP upload and hoping for the best. With the right SSH setup, a configured remote interpreter, port forwarding for Xdebug, and the JetBrains Remote Development mode, you can work on distant servers with the same IDE experience as locally.