docker-setup_skill

Overview

This skill provides a practical Docker containerization guide focused on Java Spring Boot applications. It bundles a recommended multi-stage Dockerfile, a Docker Compose example for app+MySQL, and commonly used Docker commands. The content is aimed at making builds reproducible, images lean, and local deployments consistent.

How this skill works

The skill shows how to use a multi-stage Dockerfile: build the artifact with Maven in a build stage, then copy the produced JAR into a slim runtime image to keep final images small. It includes a Docker Compose file to orchestrate the application and a MySQL service with a persistent volume. Common CLI commands are provided for building images, running containers, inspecting logs, and entering containers for debugging.

When to use it

• Packaging a Spring Boot application for consistent runtime across environments
• Setting up a local development stack with application and database using Docker Compose
• Optimizing CI pipelines by building artifacts in a separate build stage
• Reducing final image size and attack surface for production deployments
• Quickly reproducing bugs by running the exact image used in CI or production

Best practices

• Use multi-stage builds: compile in a full image (Maven) and copy the artifact into a minimal JRE image
• Expose only required ports and avoid running as root inside the container
• Externalize configuration via environment variables or mounted config files; use secrets for credentials
• Mount persistent volumes for stateful services like databases to avoid data loss
• Add healthchecks and graceful shutdown support so orchestration tools can manage restarts properly
• Keep images small by using slim base images and cleaning build caches

Example use cases

• Local development: spin up app + MySQL with docker-compose and iterate quickly
• CI pipeline: build artifact in a builder stage, run lightweight tests in the runtime image
• Production deployment: publish the optimized runtime image to a registry and deploy to orchestrators
• Debugging: run container locally, use docker logs and docker exec to inspect runtime issues
• Migration: containerize database-dependent apps to standardize environments across teams