4.3.1 Build Cache Strategy

A build cache strategy is the deliberate structuring of a Dockerfile's instruction order specifically to maximize how often Docker's layer cache can be reused across successive builds, reducing average build time across a project's typical development and deployment workflow.

The Core Principle

Instructions whose results change infrequently should appear earlier in the Dockerfile, and instructions whose results change frequently should appear later, since changing an instruction invalidates the cache for everything that follows it.

FROM python:3.12-slim
RUN apt-get update && apt-get install -y libpq5
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
CMD ["python", "app.py"]

System dependencies (rarely change) come before Python dependencies (occasionally change), which come before application source (frequently changes) — each layer is invalidated only as often as its actual content changes.

Measuring Cache Effectiveness

Comparing build times for a typical, small source code change against a typical dependency change reveals how effectively the current instruction ordering is preserving cache benefits.

echo "// small change" >> app.py
time docker build -t myapp .

A well-structured cache strategy should make this kind of build noticeably fast, since only the final COPY and nothing before it needs to be redone.

Using BuildKit's Cache Mount for Package Manager Caches

Beyond instruction ordering, BuildKit's cache mounts let a package manager's own download cache persist across separate builds, even when the underlying layer itself is rebuilt.

RUN --mount=type=cache,target=/root/.cache/pip pip install -r requirements.txt

This can speed up dependency installation even when the installation layer itself must be rebuilt, since the downloaded package files remain cached separately.

Why a Deliberate Cache Strategy Matters

A Dockerfile whose instruction order has been deliberately considered for caching can make the difference between every build taking the same fixed time regardless of what changed, and the vast majority of typical builds completing in a fraction of that time because most layers are reused — a difference that compounds significantly across a project's full development lifecycle.