Tag: Docker

1. Temporary Shell Containers for Maintenance and Diagnostics

   May 10, 2026

   Anyone who installs debugging tools on a production server creates a permanent attack surface for what is really a temporary task. Temporary shell containers offer an alternative: diagnostic tools only for the duration of the diagnosis, in the right network perspective, with no residue left on the host. With docker run --rm and namespace sharing, this takes seconds.

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2. Beobachtbarkeit in Container-Stacks: Metriken, Logs und Health | mironsoft.de

   May 10, 2026

   Ein Container-Stack ohne Beobachtbarkeit ist eine Blackbox: Man sieht, ob der Stack läuft, aber nicht warum er langsam ist, welcher Service fehlerhafte Antworten liefert oder wann ein Health Check still fehlschlägt. Strukturierte Logs, Prometheus-Metriken und richtig konfigurierte Health Checks machen jeden Container-Stack transparent und wartbar.

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3. Observability in Container Stacks: Metrics, Logs, and Health

   May 9, 2026

   A container stack without observability is a black box: you can see whether it is running, but not why it is slow, which service is returning faulty responses, or when a health check silently fails. Structured logs, Prometheus metrics, and properly configured health checks make every container stack transparent and maintainable.

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4. Running Magento Cron and Message Queue Consumers in Containers

   May 7, 2026

   Magento cron and message queue consumers behave differently in containers than on a classic server with a host crontab. Without dedicated containers, clear locking and clean signal handling, you get duplicate jobs, hanging consumers and lost messages. This article shows how Magento cron and consumers are reliably run as standalone, monitored containers.

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5. Setting Up Hot Reload for PHP and Node in Containers

   May 5, 2026

   Hot reload behaves differently in containers than on bare metal, because bind mounts, filesystem events and OPcache validation add extra layers between the editor and the running process. Understanding these layers makes PHP and Node changes appear just as fast as without containers, without rebuilding on every code change.

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6. Debugging DNS Issues in Docker Networks

   May 4, 2026

   Name resolution failure is one of the most common and, at the same time, one of the least understood errors in Docker setups. Anyone who knows how the embedded DNS server works and which tools expose the root cause can find DNS issues in Docker networks in minutes instead of hours.

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7. Distributed Tracing for Containerized Applications with OpenTelemetry

   May 4, 2026

   When a request travels through five containers and loses 800 milliseconds somewhere, metrics and logs alone only help so much. Distributed tracing with OpenTelemetry follows every request as a connected chain of spans across container boundaries and shows in Jaeger exactly which service, which database query or which external call is responsible for the latency.

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8. Distroless Images for PHP Applications

   Apr 28, 2026

   Distroless images contain neither a shell nor a package manager nor unnecessary system libraries, which drastically reduces the attack surface of a PHP container. With static-php-cli or FrankenPHP as a base, a complete PHP runtime can be compiled into a distroless image without needing the classic PHP-FPM distribution.

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9. Docker in GitLab CI: Runners, DinD, Caching and Artifacts

   Apr 25, 2026

   Docker in GitLab CI is powerful, but the configuration is full of pitfalls: the wrong runner type, insecure Docker-in-Docker, build caches that never hit, and artifacts that transfer unnecessary megabytes. Once you understand the mechanisms, you build pipelines that finish in three minutes instead of thirty.

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10. Docker Compose vs Kubernetes: What Actually Changes

    Apr 19, 2026

    Kubernetes gets marketed as the solution to problems many teams do not even have yet. Docker Compose handles local development and smaller production deployments elegantly. Kubernetes handles cluster scaling, self-healing and multi-tenant isolation. The difference is not about which technology is better, it is about the size of the problem.

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