BuildKit’s history and metadata are surprisingly dynamic, often containing far more than just the steps you explicitly wrote in your Dockerfile.
Let’s see it in action. Imagine a simple Dockerfile:
FROM alpine:latest
COPY . /app
RUN echo "Hello, BuildKit" > /app/hello.txt
CMD ["cat", "/app/hello.txt"]
When you build this with BuildKit, you can inspect its internal state. The buildx imagetools inspect command is your window into this. For an image built with docker buildx build --tag my-alpine-app ., you’d run:
docker buildx imagetools inspect my-alpine-app:latest
This command doesn’t just show you the final image manifest; it reveals the build process itself. You’ll see a breakdown of layers, but more importantly, the buildkit.v0.image.v1 annotation within the manifest. This annotation contains a JSON object that details the build’s history. It includes information about the builder used, the source code context, and a step-by-step breakdown of the build process, including intermediate build steps that aren’t directly exposed in a standard docker history output.
The magic here is that BuildKit treats the build process as a directed acyclic graph (DAG) of build operations. Each instruction in your Dockerfile (like FROM, COPY, RUN) translates into one or more nodes in this graph. BuildKit optimizes this graph, potentially parallelizing operations and caching intermediate results. The metadata stored in the image annotation is essentially a serialized representation of this DAG, allowing for reproducibility and detailed inspection of how an image was constructed.
The buildkit.v0.image.v1 annotation is structured to capture this DAG. It has fields like frontend, which tells you which build system was used (e.g., dockerfile.v0), and build.source, which describes the source of the build. The most interesting part is the build.actions field, which is an array of objects. Each object represents a build step and contains fields like description (the command or instruction), content (the digest of the resulting layer), and digest (the digest of the action itself). This granular view means you can trace the origin of any layer back to its specific build instruction and even its parent layers in the build graph.
Consider a COPY instruction. BuildKit doesn’t just copy files; it calculates a content-addressable hash of the files being copied. If you were to build again with the exact same files in your build context, the COPY operation would be a cache hit, and the metadata would reflect that an existing layer was reused. This is crucial for understanding why builds are fast and reproducible. The metadata captures not just what happened, but how it happened and why a particular caching strategy was applied.
Furthermore, BuildKit’s history can include steps that weren’t explicitly written by you. For example, if you use multi-stage builds, the metadata will show the intermediate stages and their respective layers. Even the FROM instruction itself is recorded as an action, pointing to the base image’s digest. This allows for a complete lineage of the image, from its genesis as a minimal base image to its final state.
What most users don’t realize is that the buildkit.v0.image.v1 annotation is mutable and can be extended by custom build frontends or plugins. This means that beyond the standard Dockerfile instructions, additional metadata about security scanning, code provenance, or even test results can be embedded directly into the image’s build history. This is not merely an inspection tool; it’s a mechanism for attaching verifiable build artifacts to the image itself.
The next step in exploring BuildKit’s capabilities is understanding how to leverage this rich metadata for advanced caching strategies and reproducible builds beyond simple layer caching.