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Multistage BuildEdit

Multistage builds are a practical approach to structuring software deployment that separates the heavy lifting of building and testing code from the lean, production-ready artifact that actually runs in production. In modern development, where teams aim to move fast while controlling costs and risk, multistage builds help keep artifacts small, reproducible, and easier to secure. They are especially prevalent in containerized environments, where the final runtime image is kept minimal by excluding build tools, caches, and tests that were indispensable during development.

The technique emerged from the needs of teams to speed up deployments and reduce infrastructure costs without sacrificing developer productivity. By harnessing the capabilities of platforms like Docker and the scripting support of a Dockerfile, organizations can compile and verify software in one stage and then copy only the necessary artifacts into a separate, lighter runtime stage. This aligns with a straightforward, efficiency-minded approach to software delivery: you pay for what you run, not for the entire build environment.

Multistage builds are now a standard pattern in contemporary software engineering, reflecting a broader preference for modular, maintainable systems where build-time and run-time concerns are cleanly separated. They support better reproducibility, smaller attack surfaces, and clearer ownership of the components that actually ship to customers. In practice, teams often describe the approach as a pragmatic balance between rapid iteration and disciplined production readiness.

Origins and concept

The core idea traces back to the era when developers experimented with large monolithic images that included compilers, test libraries, and documentation alongside the application binaries. As containerization gained traction, the ability to express multiple build stages within a single configuration file became a natural evolution. The approach was popularized in part by Docker through enhanced support in Dockerfiles, allowing a single artifact to be produced from several distinct stages. This made it easier to automate the transition from a feature branch to a production-ready image while keeping the runtime footprint small. See how the concept relates to container images and the broader practice of containerization.

How multistage builds work

  • A build file declares multiple stages, each starting from its own base image and performing distinct tasks (compilation, testing, packaging, etc.). Each stage is given a name, such as "builder" or "runtime". The syntax for this is typically expressed in a Dockerfile.
  • The final runtime image strategically copies only the artifacts produced in the build stage, using a directive like COPY --from to pull files from a previous stage.
  • Build-time dependencies (compilers, dep management tools, test suites) live in the earlier stages and are omitted from the final image, reducing size and risk.
  • Build-time variables (ARG) and runtime configuration (ENV) help separate concerns between what is built and what runs in production. Secrets should be handled carefully, ideally using BuildKit secret mounts rather than baking them into layers.
  • The approach supports several common patterns, from producing a statically linked binary in a language like Go to packaging a compiled application with minimal runtime libraries in a small base image like Alpine Linux or even the bare Scratch image.

Example (simplified illustration): - Stage 1: FROM golang:1.20 AS builder - Copy source files - Run go build to produce a static binary - Stage 2: FROM alpine:3.19 - Create a non-root user - Copy the binary from the builder stage using COPY --from=builder - Define ENTRYPOINT to run the application

This structure keeps the final image lean and focused on runtime needs, while the build stage retains all the tools required for compilation and testing.

Benefits

  • Smaller final images: By excluding compilers, test utilities, and caches, the runtime image is significantly smaller, improving distribution, startup time, and resource usage.
  • Reduced attack surface: The final image contains only what is necessary to run the application, limiting potential entry points for attackers.
  • Clear separation of concerns: Build, test, and packaging live in their own stages, making audits, updates, and maintenance more straightforward.
  • Better reproducibility and updates: Dependencies can be pinned at the build stage, and the final image can be swapped or updated without re-architecting the runtime configuration.
  • Cost efficiency: Smaller images translate to lower storage and bandwidth costs, which matters in large-scale deployments and cloud environments.

Patterns and best practices

  • Always separate build-time from run-time: Use one or more build stages to compile and test, and a clean runtime stage for execution.
  • Use minimal runtime base images: Favor small images like Alpine Linux or the ultra-lightweight Scratch image to minimize the runtime footprint.
  • Copy carefully with --from: Name each build stage and copy only the necessary artifacts into the final stage.
  • Run as a non-root user in the final image: This reduces privilege escalation risk in production.
  • Pin base images and dependencies: Use explicit versions to improve reproducibility and reduce drift.
  • Manage secrets properly: Avoid embedding secrets in final images; leverage BuildKit secret mounting or other secret management approaches during the build.
  • Leverage BuildKit capabilities: BuildKit enhances caching, parallel builds, and secret management, improving security and efficiency.
  • Consider SBOM and licensing implications: Maintain transparency about components and licenses used in the final runtime image.
  • Validate through automated pipelines: Integrate multistage builds into CI/CD pipelines to ensure consistent builds and rapid feedback.

Security considerations and debates

  • Security vs complexity: Proponents argue multistage builds reduce the exposure of runtime environments by removing build tools and caches. Critics warn that orchestrating multiple stages can introduce complexity and potential misconfigurations if teams don’t follow disciplined practices.
  • Secrets and credentials: The temptation to bake credentials into a build is a common pitfall. The recommended approach is to avoid including secrets in any layer that makes it into the final image, and to use build-time secret mechanisms where possible.
  • Supply chain risk: Relying on external base images means trusting upstream maintainers. The best practice is to pin versions, verify signatures where available, and consider using SBOMs to keep a clear manifest of components.
  • Reproducibility vs flexibility: Multistage builds often improve reproducibility by isolating build steps, but controversy can arise around the determinism of base images and external dependencies. Advocates emphasize standardized, reproducible workflows and the ability to recreate a production artifact from source.
  • Operational efficiency: From a performance and cost perspective, multistage builds can be a strong investment for teams scaling deployments. The argument centers on delivering fewer, more secure artifacts faster and with lower operational overhead.

See also