Comment tirer parti du cache Docker pour optimiser les vitesses de construction

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Leveraging Docker cache can significantly speed up your builds by reusing layers from previous builds. Let’s learn how to optimize a Dockerfile to make the most of Docker’s layer caching mechanism.

Prerequisites

Before you begin:

• You should have Docker installed. Get Docker if you haven’t already.
• You should be familiar with basic Docker concepts, creating Dockerfiles, and common Docker commands.

How Docker Build Cache Works

Docker images are built in layers, where each instruction in the Dockerfile creates a new layer. For example, instructions like FROM, RUN, COPY, and ADD each create 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 computes based on the layer’s content. Docker compares these hashes to determine if it can reuse a layer from the cache.

Building a Docker Image | Image by Author

When Docker builds an image, it goes through each instruction in the Dockerfile and checks the cache to see if it can reuse a previously created layer.

To Reuse or Build from Scratch | Image by Author

The decision to use the cache depends 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 previously executed, the cache can be used.
• Files and Directories: For instructions involving files, like COPY and ADD, Docker checks the content of the files. If the files haven’t 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, forcing Docker to rebuild the layer from scratch:

• Changes 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 `COPY` or `ADD` instructions change, Docker invalidates the cache for those layers and subsequent layers.

To summarize, here’s what you need to know about 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 a layer changes, all subsequent layers are rebuilt. Therefore, placing instructions that don’t change often (such as the base image, dependency installations, initialization scripts) earlier in the Dockerfile can help maximize cache hits.

Best Practices for Leveraging Docker Build Cache

To take advantage of Docker build cache, you can structure your Dockerfile to maximize cache hits. Here are some tips:

• Order Instructions by Frequency of Change: Place instructions that change less frequently higher up in the Dockerfile. Place instructions that change frequently, such as COPY or ADD of application code, towards the end of the Dockerfile.
• Separate Dependencies from Application Code: Separate instructions that install dependencies from those that copy source code. This way, dependencies are only reinstalled if they change.

Next, let’s look at some examples.

Examples: Dockerfiles Leveraging Build Cache

1. Here’s an example Dockerfile for setting 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 doesn’t change frequently. Environment variables are unlikely to change often, so defining them early allows for cache reuse in subsequent layers. Note that we copy the initialization scripts before the application code. Copying files that don’t change frequently before those that do helps leverage the cache.

2. Here’s another example Dockerfile for containerizing 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 the reuse of cached layers, leading to 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 by clicking the following links:

Bala Priya C is an Indian developer and technical writer. She enjoys working at the intersection of mathematics, programming, data science, and content creation. Her areas of interest and expertise include DevOps, data science, and natural language processing. She loves reading, writing, coding, and drinking coffee! Currently, she is focused on learning and sharing her knowledge with the developer community by creating tutorials, how-to guides, opinion pieces, and more. Bala also creates engaging resource roundups and coding tutorials.