Docker Multi-Stage Builds | Shrink Images from 2GB to 134MB

🎯 Why Docker Image Size Matters

Every DevOps engineer runs into this problem:

You build a Docker image.
It works… but it’s HUGE.
2GB+ images slow down your CI/CD pipeline, eat storage, and burn through deployment time.

In production, bloated images = wasted money and frustrated teams.

The fix? Docker multi-stage builds.

With a few tweaks to your Dockerfile, you can shrink images from gigabytes to megabytes — without losing functionality.

▶️ What You’ll Learn in This Video

In this step-by-step hands-on demo, I break down: https://youtu.be/HBoOJgwA4Co

📌 Docker Image Basics

• Why images get so large

• How caching and layers work

📌 Hands-On Setup

• Build a Flask app in a single-stage Dockerfile → ends up 2.29 GB

• Run the container and check its size

📌 Optimization with Multi-Stage Builds

• Create a slim production-ready Dockerfile

• Copy only the essentials into the final stage

• Compare with the bloated build

📌 Debugging Layers

• Use docker images to see size difference

• Use docker history to inspect layers

📌 Best Practices

• Always separate build and runtime

• Use .dockerignore to avoid copying junk

• Tag optimized images for CI/CD pipelines

👉 Watch the full video here: [YouTube Link]
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🛠 Takeaway Example Command

❓ How do you inspect the size of each layer in your Docker image?

✅ Answer:

docker history <image-id>

💡 This shows you exactly which steps in your Dockerfile are making your image huge.

💡 Why This Guide Stands Out

• Real-world focus → I don’t just tell you to “use alpine.” I show a 2.29 GB bloated build and shrink it to 134 MB.

• Debug-driven → We actually inspect layers and caching, so you know why sizes change.

• Production-ready → By the end, you’ll know how to optimize Dockerfiles for real CI/CD pipelines.

This isn’t “Docker Hello World.” It’s production-grade image optimization.

👋 Final Note

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Every week I share real DevOps outages, interview prep, and hands-on labs you can reproduce — so you’ll never be caught off guard in production.

— Arbaz
📺 YouTube: Learn with DevOps Engineer
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