docker / getting-started

Multi-stage Builds

This outline describes the core concepts and practical applications of multi-stage builds. Multi-stage builds are a powerful feature introduced in Docker 17.04, offering a streamlined approach to crafting efficient Docker images.

Why Multi-Stage Builds?

The key benefit of multi-stage builds lies in their ability to separate build-time dependencies from runtime dependencies, resulting in leaner, more optimized images. The traditional method of including all dependencies in a single stage often leads to bulky images, consuming unnecessary storage and network resources.

A Simple Example

Let’s illustrate the benefits of multi-stage builds using a straightforward example.

# Stage 1: Build the application
          FROM golang:1.18 AS builder
          
          WORKDIR /app
          
          COPY . .
          
          RUN go build -o main
          
          # Stage 2: Create a minimal runtime image
          FROM alpine:latest
          
          WORKDIR /app
          
          COPY --from=builder /app/main .
          
          CMD ["/app/main"]

In this example, the first stage (builder) is used to build the Go application. It’s a heavy image with all the necessary build tools. The second stage (runtime) utilizes a lean Alpine Linux base image, copying only the compiled binary from the builder stage. This final image is significantly smaller, making it efficient for deployment and execution.

Benefits of Multi-Stage Builds

  • Reduced Image Size: Only the essential components needed for runtime are included in the final image.
  • Improved Security: Minimizing dependencies reduces the attack surface, enhancing image security.
  • Faster Builds: Building separate stages can lead to faster image build times, particularly when complex builds are involved.
  • Clean Separation: Clearly distinguishes between build-time and runtime requirements.

Key Concepts

  • Stages: Each FROM instruction defines a new stage in the Dockerfile.
  • Stage Naming: Assign names to stages using the AS keyword for easy reference.
  • Copying Artifacts: Use the COPY --from=stage_name instruction to copy artifacts between stages.

Best Practices

  • Clean Separation: Design Dockerfiles with a distinct separation of build and runtime stages.
  • Minimize Dependencies: Include only the essential runtime components in the final image.
  • Optimize Layers: Minimize the number of layers by grouping commands that modify the same file.
  • Clear Naming: Choose descriptive stage names for easy understanding.

Additional Resources