🔥 Did you know Docker's default settings are designed for convenience, not necessarily production? A container can run without CPU or memory limits, while its logs keep growing if rotation isn't configured. t.co/RkEroQGfFu
Everything may look fine during development, but in production, these defaults can become serious operational problems. Here are 4 things to watch out for: 🧠 1. Memory limits: Without limits, one container can consume all available host memory, triggering the Linux OOM killer.
⚙️ 2. CPU limits: Containers get throttled when they hit CPU limits. Set them too tightly, and application performance suffers. 📜 3. Log management: Docker's default `json-file` logging driver doesn't rotate logs automatically. Over time, logs can fill up your disk.
🧹 4. Disk space: Old images, stopped containers, unused volumes and build cache can quietly consume valuable disk space. ✅ YOUR PRODUCTION CHECKLIST → Set memory limits based on peak usage. → Configure CPU limits carefully. → Enable log rotation.
→ Send application logs to stdout and stderr. → Ship logs to an external logging platform. → Monitor CPU, memory, restarts, OOM kills and disk usage. → Regularly clean up unused Docker resources. → Keep persistent data in volumes or external storage.
⚠️ COMMON MISTAKES → Setting memory limits based on average usage. → Collecting logs without monitoring them. → Storing important data inside a container's writable filesystem.
The tricky part? These problems may not show up during testing. They can surface weeks later during a traffic spike. Production readiness isn't just about getting your container running. It's about ensuring one poorly behaved container doesn't bring everything else down.
💬 Which of these Docker issues have you encountered? #Docker #DevOps #DataEngineering #SRE #CloudNative
