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A monorepo is a single source-code repository that contains multiple projects. Those projects may share code and tooling, but they do not have to form one application or ship in one release. It is an organizational choice: keep multiple projects together, rather than give each project its own repository.
What does a monorepo contain?
The word combines “monolithic” and “repository,” though a monorepo does not necessarily contain one monolithic application. It can hold related or unrelated projects, such as libraries, services, and applications. Teams may manage dependencies and developer tools in common, while maintaining separate project boundaries inside the repository.
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The defining feature is the repository boundary: multiple projects live in one source-control repository. It does not determine whether projects are deployed together, released together, or owned by the same team.
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Coordinate changes across projects
When a change affects several projects, contributors can update them in one place and at one repository revision. That can avoid the coordination overhead of making and tracking corresponding changes across several repositories. Babel, for example, describes easier coordination across its modules and cross-module testing as benefits of its monorepo approach. These are observations about Babel’s project, not the result of a controlled comparison. Babel’s monorepo documentation
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Reuse code and manage dependencies
Shared source code can be easier to discover and reuse when it sits alongside its consumers. A shared repository can also make it simpler to align dependency versions or change a library and its users together. The 2018 literature review identifies simplified dependencies, code reuse, and coordinated refactoring among benefits reported in the literature. The review of monorepo literature
Keep workflows consistent
A common repository can support shared conventions for building, testing, linting, and releasing projects. Google Cloud cites code reuse, dependency management, and consistent developer workflows among the benefits of its monorepo. Its documentation also notes that some Google Cloud services use another Git repository for open-source software, illustrating that a monorepo can coexist with separate repositories. Google Cloud’s account of its monorepo
What are the trade-offs?
- Navigation and code health: A repository with many projects can feel large or intimidating, and keeping its code healthy takes active maintenance. Babel lists a larger, more intimidating codebase among its project-specific costs. Babel’s monorepo documentation
- Build and test workload: A shared repository does not automatically make builds faster or tests more selective. Without tooling that understands project dependencies, a change may trigger more work than necessary.
- Tooling investment: Large repositories can require substantial effort to establish ownership, dependency boundaries, build and test automation, and repository workflows. The literature review also identifies complexity, migration, and build, deployment, and testing concerns among reported challenges. The 2018 literature review
- Versioning boundaries: Keeping code together can make coordinated changes easier, but teams may value the version information and independent dependency and release boundaries that separate repositories provide. The literature review reports loss of version information as a challenge.
How do large monorepos avoid building everything?
They rely on explicit project boundaries and tooling that can determine which targets depend on a change. In the workflow described by Bazel’s FAQ, teams own parts of a large source tree, publish components as build targets, and specify dependencies so Bazel can predict which programs and tests a change affects. The repository itself does not provide that prediction; the build system uses the dependency information. Bazel’s FAQ
Target size involves a trade-off. A single broad target is simpler to describe but may require rebuilding a whole project after a change. Fine-grained targets can help caching and scheduling, but their dependency declarations take more work to create and maintain. Bazel’s dependency guidance
Bazel is one possible tool, not a requirement for a monorepo. Its FAQ says it is aimed especially at large codebases, mixed compiled languages, multiple deployment platforms, and extensive tests; it may offer little benefit when a workflow consists of a few long, sequential steps. Bazel’s FAQ
How does a monorepo compare with separate repositories?
Neither arrangement is universally better. A monorepo tends to suit teams that frequently coordinate changes across projects and can support shared tooling. Separate repositories can suit projects with strong independent versioning, release, or ownership boundaries. The practical choice depends on how the team works, not on repository size alone.
- Cross-project changes: How often do changes span projects, and how costly is it to coordinate them across repositories?
- Dependencies and releases: Do projects benefit from consuming internal code at a shared revision, or do they need independently versioned dependencies and release schedules?
- Build and test performance: Can the tooling identify affected projects, or would a shared repository mean running too much work for each change?
- Ownership and navigation: Can the team keep responsibilities clear and the codebase understandable as it grows?
- Migration and maintenance: Is the current coordination pain significant enough to justify moving repositories and maintaining the supporting tools?
The 2018 review by Gleison Brito, Ricardo Terra, and Marco Tulio Valente synthesized 21 grey-literature sources and two academic papers. It found no consensus that one repository strategy works best for every team; its findings describe that literature, not a current controlled comparison. Read the review
Is Google’s monorepo a model to copy?
Google Cloud describes a repository containing millions of source files and billions of lines of code, with a history of hundreds of millions of changelists and tens of thousands of new changelists on each workday. Those figures are reported by Google Cloud, and the cited page does not state when they were published. They illustrate the scale of one organization’s approach, not a target or a prescription for other teams. Google Cloud’s monorepo account
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