Why Multi-stage builds for smaller images in MLOps? - Purpose & Use Cases

The Big Idea

Discover how to shrink your container images without losing power or speed!

The Scenario

Imagine you are building a software container that needs many tools and files to compile your code, but only a few of those files are needed to actually run the program.

You try to include everything in one big container image.

The Problem

This big container becomes slow to download and uses lots of storage.

It also has unnecessary tools that can cause security risks.

Every time you update, you waste time rebuilding and pushing a huge image.

The Solution

Multi-stage builds let you use one container to build your program and another smaller container to run it.

This way, only the needed files go into the final image, making it much smaller and faster.

Before vs After

✗ Before

FROM build-image
RUN build commands
COPY all files
RUN setup runtime

✓ After

FROM build-image AS builder
RUN build commands
FROM runtime-image
COPY --from=builder /app /app

What It Enables

It enables fast, secure, and efficient container images that are easy to share and deploy.

Real Life Example

A data scientist builds a large ML model with many tools, but the final container only includes the model and minimal runtime to serve predictions quickly.

Key Takeaways

Manual container builds often include unnecessary files and tools.

Multi-stage builds separate build and runtime environments.

This results in smaller, faster, and safer container images.