14 Docker Production
A focused guide to Docker Production, connecting core concepts with practical Docker and container operations.
Docker production covers the collection of practices — appropriate resource limits, health checks, logging configuration, security hardening, and resilient orchestration — that distinguish a genuinely production-ready containerized deployment from one that merely happens to work during local development or testing.
Why Production Requirements Differ Meaningfully From Development
A development environment optimizes for convenience and fast iteration; production needs to optimize for reliability, security, and observability under real, often unpredictable load, requiring deliberate additional configuration beyond what development needs.
services:
app:
build: .
volumes:
- .:/app
command: npm run dev
services:
app:
image: registry.example.com/myapp:1.0
deploy:
resources:
limits:
memory: 512M
restart_policy:
condition: on-failure
The production configuration explicitly constrains resources and defines restart behavior, concerns that simply don't matter in the more permissive development context.
Key Areas Requiring Specific Production Attention
Resource limits, health checks, structured logging, and security hardening each need deliberate configuration appropriate to running real workloads reliably.
services:
app:
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8080/health"]
interval: 30s
deploy:
resources:
limits:
cpus: '1.0'
memory: 512M
Why Treating Production Configuration as a Distinct, Deliberate Concern Matters
Simply taking a development configuration and running it in production, without these additional considerations, risks resource exhaustion, undetected failures, and security exposure that a properly configured production setup specifically guards against.
docker stats
Why Docker Production Matters
Recognizing production's distinct requirements, and deliberately configuring for them rather than reusing development defaults, is essential for an application to actually run reliably, securely, and observably once it's handling real traffic and real consequences for failure.