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Comparing Multi-Stage Builds vs. Single-Stage Builds

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Platform Engineers
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3 min read

In the context of Docker image creation, build processes play a crucial role in ensuring the efficient and reliable deployment of applications. Two common approaches to building Docker images are multi-stage builds and single-stage builds. This blog post delves into the technical differences between these two methods, highlighting their distinct characteristics and use cases.

Single-Stage Builds

A single-stage build involves creating a Docker image in a single step. This approach is straightforward and easy to implement. The Dockerfile for a single-stage build typically includes all the necessary instructions to build and package the application.

# Use an official Python runtime as a parent image
FROM python:3.9-slim

# Set the working directory to /app
WORKDIR /app

# Copy the current directory contents into the container at /app
COPY . /app

# Install any needed packages specified in requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Make port 80 available to the world outside this container
EXPOSE 80

# Define environment variable
ENV NAME World

# Run app.py when the container launches
CMD ["python", "app.py"]

In this example, the Dockerfile uses a single stage to build and package a Python application. The resulting image includes all the dependencies and the application code.

Multi-Stage Builds

Multi-stage builds, on the other hand, involve creating multiple intermediate images during the build process. Each stage serves a specific purpose, such as building the application, creating a runtime environment, or copying artifacts. This approach allows for more flexibility and control over the final image.

# Stage 1: Build
FROM python:3.9-slim as build
WORKDIR /app
COPY . /app
RUN pip install --no-cache-dir -r requirements.txt
RUN python setup.py build

# Stage 2: Runtime
FROM python:3.9-slim
WORKDIR /app
COPY --from=build /app/. .
CMD ["python", "app.py"]

In this multi-stage build example, there are two stages: build and runtime. The build stage is responsible for building the application, while the runtime stage creates the final image by copying the artifacts from the build stage.

Key Differences

  1. Image Size: Multi-stage builds typically result in smaller final images since each stage can be optimized for its specific task. In contrast, single-stage builds often include unnecessary dependencies and files, leading to larger images.

  2. Build Complexity: Multi-stage builds offer more flexibility and control over the build process, allowing for more complex build scenarios. Single-stage builds are generally simpler and easier to implement.

  3. Layer Caching: Multi-stage builds can take advantage of layer caching more effectively, as each stage can cache its layers independently. This can significantly speed up the build process.

  4. Artifact Management: Multi-stage builds provide a clear separation of concerns, making it easier to manage artifacts and dependencies between stages.

Use Cases

  1. Complex Builds: Multi-stage builds are ideal for complex build scenarios involving multiple dependencies, compilation steps, or artifact management. They offer more control and flexibility, making them suitable for large-scale applications.

  2. Small Images: When image size is a concern, multi-stage builds can help minimize the final image size by separating build and runtime dependencies.

  3. Simple Applications: Single-stage builds are suitable for simple applications with minimal dependencies, where the build process is straightforward and easy to implement.

Conclusion

In conclusion, both multi-stage builds and single-stage builds have their strengths and weaknesses. Multi-stage builds offer more flexibility, control, and optimization opportunities, making them suitable for complex build scenarios and large-scale applications. Single-stage builds, on the other hand, are simpler and easier to implement, making them ideal for small applications with minimal dependencies. By understanding the technical differences between these two approaches, developers can choose the most appropriate method for their specific use case.

Platform Engineering