How to leverage Docker Cache to optimize build speeds

Taking advantage of Docker's cache can significantly speed up your builds by reusing layers from previous builds. Let's learn how to optimize a Dockerfile to take full advantage of Docker's layer caching mechanism.

Prerequisites

Before you start:

• You should have Docker installed. Get Docker If you haven't already.
• You should be familiar with Docker basics, creating Dockerfiles, and common Docker commands.

How Docker Build Cache Works

Docker images are built in layers, where each statement in the Dockerfile creates a new layer. For example, instructions like FROM, RUN, COPYand ADD each creates a new layer in the resulting image.

Docker uses a content-addressable storage mechanism to manage image layers. Each layer is identified by a unique hash that Docker calculates based on the contents of the layer. Docker compares these hashes to determine whether it can reuse a layer from the cache.

Building a Docker image | Image by author

When Docker creates an image, it reviews each statement in the Dockerfile and performs a cache lookup to see if it can reuse a previously created layer.

Reuse or build from scratch | Image by the author

The decision to use caching is based on several factors:

• base image: If the base image (FROM instruction) has changed, Docker will invalidate the cache for all subsequent layers.
• Instructions: Docker checks the exact content of each instruction. If the instruction is the same as one executed previously, the cache can be used.
• Files and directories: for instructions involving files, such as COPY and ADDDocker checks the content of the files. If the files have not changed, the cache can be used.
• Build context:Docker also considers the build context (the files and directories sent to the Docker daemon) when deciding to use the cache.

Understanding cache invalidation

Certain changes can invalidate the cache, causing Docker to rebuild the layer from scratch:

• Modification in the Dockerfile:If an instruction in the Dockerfile changes, Docker invalidates the cache for that instruction and all subsequent instructions.
• Changes in source files: If the files or directories involved in the `COPY` or `ADD` instructions change, Docker invalidates the cache for these layers and subsequent layers.

In summary, here's what you need to know about the Docker build cache:

• Docker builds images layer by layer. If a layer hasn't changed, Docker can reuse the cached version of that layer.
• If one layer changes, all subsequent layers are rebuilt. Therefore, placing instructions that do not change frequently (such as the base image, dependency installations, initialization scripts) much earlier in the Dockerfile can help maximize cache accesses.

Best practices for leveraging Docker build cache

To take advantage of Docker's build cache, you can structure your Dockerfile in a way that maximizes cache accesses. Here are some tips:

• Ordering instructions by change frequency: Place instructions that change less frequently at the top of the Dockerfile. And place instructions that change frequently, such as COPY either ADD from the application code to the end of the Dockerfile.
• Separate dependencies from application code: Separates instructions that install dependencies from those that copy the source code. This way dependencies are only reinstalled if they change.

Next, let's take a couple of examples.

Examples: Dockerfiles that leverage the build cache

1. Below is an example Dockerfile to set up a PostgreSQL instance with some initial configuration scripts. The example focuses on optimizing layer caching:

# Use the official PostgreSQL image as a base
FROM postgres:latest

# Environment variables for PostgreSQL
ENV POSTGRES_DB=mydatabase
ENV POSTGRES_USER=myuser
ENV POSTGRES_PASSWORD=mypassword

# Set the working directory
WORKDIR /docker-entrypoint-initdb.d

# Copy the initialization SQL scripts
COPY init.sql /docker-entrypoint-initdb.d/

# Expose PostgreSQL port
EXPOSE 5432

The base image layer does not usually change frequently. Environment variables are unlikely to change frequently, so setting them early helps reuse the cache for later layers. Note that we copy the initialization scripts before the application code. This is because copying files that don't change frequently before those that do helps take advantage of the cache.

2. Here is another example of a Dockerfile to containerize a Python application:

# Use the official lightweight Python 3.11-slim image
FROM python:3.11-slim

# Set the working directory
WORKDIR /app

# Install dependencies
COPY requirements.txt requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Copy the contents of the current directory into the container
COPY . .

# Expose the port on which the app runs
EXPOSE 5000

# Run the application
CMD ("python3", "app.py")

Copying the rest of the application code after installing dependencies ensures that changes to the application code do not invalidate the dependency layer cache. This maximizes reuse of cached layers, resulting in faster builds.

By understanding and leveraging Docker's caching mechanism, you can structure your Dockerfiles for faster builds and more efficient image creation.

Additional Resources

Learn more about caching at the following links:

twitter.com/balawc27″ rel=”noopener”>Bala Priya C. is a developer and technical writer from India. He enjoys working at the intersection of mathematics, programming, data science, and content creation. His areas of interest and expertise include DevOps, data science, and natural language processing. He likes to read, write, code and drink coffee! Currently, he is working to learn and share his knowledge with the developer community by creating tutorials, how-to guides, opinion pieces, and more. Bala also creates engaging resource descriptions and coding tutorials.