🚀 Why Did Our Deployment Slow Down?
The Problem: Slow Container Deployment
Imagine this: Your team is working on an important release. The container images are built, and deployment starts. But there's a problem—it takes forever to launch.
Suddenly, your cloud bills rise, CPU usage spikes, and customers complain about slow service availability. You check the logs and realize… the Docker image size is massive!
🔍 What Went Wrong?
When a container is launched, its content is loaded into RAM. A larger image means:
Slower builds
Increased resource consumption
Higher time to market
That’s where image optimization comes in. By following best practices like reducing unnecessary layers, we can:
✅ Decrease build time
✅ Launch containers faster
✅ Lower CPU & RAM usage
✅ Reduce storage consumption
👨💻 Understanding Docker Image Build
We use tools to build images from a Dockerfile. Older Docker versions used the inbuilt Docker build engine, while newer versions use BuildKit, a more efficient build tool.
Switching Between Build Engines:
DOCKER_BUILDKIT=0 → Use the older build engine
DOCKER_BUILDKIT=1 → Use the newer BuildKit tool
How Does an Image Build Work?
1️⃣ Docker starts a container from the base image (FROM).
2️⃣ It runs the next step in the container.
3️⃣ Once done, Docker commits the running container into an image.
4️⃣ The container is removed, and the new image is used as a base for the next step.
5️⃣ This cycle repeats: launch → run step → commit → remove → repeat.
Each step creates an intermediate container, which commits into an intermediate image. The number of instructions in the Dockerfile equals the number of intermediate layers. Each layer holds the delta changes but is linked to previous layers, forming a chain.
🧐 How Does This Impact Image Size?
Older Docker builds retain metadata of all intermediate layers, increasing the final image size. Newer BuildKit builds discard unnecessary metadata, reducing image size.
Check Your Image History:
docker history <image_id>
With BuildKit, metadata about intermediate layers appears as <missing>, reducing storage and launch time.
🔹 Optimizing Image Layers
Reducing unnecessary layers optimizes image build performance.
✅ Efficient Approach:
RUN yum install -y python36 && pip3 install flask
❌ Inefficient Approach:
RUN yum install -y python36
RUN pip3 install flask
By minimizing layers, we:
Reduce build time
Optimize storage
Improve container performance
🎯 Conclusion
Optimizing Docker images is crucial for efficient deployments. By leveraging BuildKit, reducing layers, and following best practices, teams can:
Improve deployment speed
Lower cloud costs
Enhance service availability
🚀 Start optimizing your Docker images today and experience faster deployments! 🔥