Multi-Stage Builds for Optimized Container Images in Platform Engineering

Containerization has become an essential tool for building, deploying, and running applications. One of the most popular containerization tools is Docker, which allows developers to create lightweight, portable, and self-contained environments for their applications. However, as the size of container images grows, so does the time and resources required to build and deploy them. This is where multi-stage builds come in.

Multi-stage builds are a feature of Docker that allows developers to create optimized container images by using multiple build stages. Each stage can have its own set of instructions and dependencies, and only the necessary files and libraries are copied to the final image. This results in smaller, more efficient container images that are faster to build and deploy.

Here's an example of a multi-stage Dockerfile for a Node.js application:

# Stage 1: Build
FROM node:14 as build

WORKDIR /app

COPY package*.json ./

RUN npm ci

COPY . .

RUN npm run build

# Stage 2: Runtime
FROM node:14-alpine as runtime

WORKDIR /app

COPY --from=build /app/dist ./dist

COPY package*.json ./

RUN npm ci --only=production

CMD ["npm", "start"]

In this example, the first stage (build) is responsible for building the application. It uses the node:14 base image and sets the working directory to /app. It then copies the package.json and package-lock.json files to the container and installs the dependencies using npm ci. Next, it copies the rest of the application code and runs the build command using npm run build.

The second stage (runtime) is responsible for running the application. It uses the node:14-alpine base image, which is a smaller and more lightweight version of Node.js. It sets the working directory to /app and copies the built files from the first stage using the --from=build flag. It then copies the package.json and package-lock.json files again and installs only the production dependencies using npm ci --only=production. Finally, it sets the command to start the application using npm start.

By using multi-stage builds, we can separate the build and runtime environments, which allows us to optimize the final container image. In this example, the first stage installs all the development dependencies, which are not needed at runtime. These dependencies are not copied to the final image, resulting in a smaller and more efficient container.

Another benefit of multi-stage builds is that they allow us to use different base images for different stages. In the example above, we used the node:14 base image for the build stage and the node:14-alpine base image for the runtime stage. This allows us to take advantage of the smaller size and faster performance of the Alpine Linux distribution for the runtime environment, while still using the full-featured Node.js distribution for the build environment.

Here are some best practices for using multi-stage builds:

1. Use a minimal base image for the runtime stage to reduce the size of the final container image.

2. Install only the necessary dependencies for each stage.

3. Use the --from=<stage> flag to copy only the necessary files from one stage to another.

4. Use the .dockerignore file to exclude unnecessary files from the build context.

5. Use the --no-cache flag when building the final image to ensure that all dependencies are reinstalled.

In conclusion, multi-stage builds are a powerful feature of Docker that allow developers to create optimized container images for their applications. By separating the build and runtime environments and using different base images for each stage, developers can reduce the size and improve the performance of their container images. By following best practices and using multi-stage builds effectively, platform engineers can build and deploy applications more efficiently and reliably.