The repository structure that works for a two-person startup almost never works for a fifty-person engineering team. What starts as a simple, clean codebase eventually develops friction points as more people and services are added. The conversation about whether to use a single Monorepo or split work across multiple repositories usually starts here, when dependency management gets complicated, practices drift between teams, and CI builds start taking way too long. It’s a constant tension between giving teams the independence to move fast and maintaining the shared context needed for services to actually work together.

The Evolving Challenge of Code Structure

In practice, the pain shows up in pull requests. A simple bug fix in a shared library requires five separate PRs in five different service repositories. Or a developer on the web team can’t test their changes locally because the API team just refactored a core model, and nobody realized the dependency was there.

These aren’t theoretical problems, they are daily slowdowns that block releases and frustrate engineers. The core challenge is finding a structure that minimizes this kind of coordination overhead without creating new bottlenecks.

Understanding the Core Architectures: Monorepo and Multiple Repositories

The debate comes down to two primary models for organizing code. Each one optimizes for a different set of priorities and introduces its own specific set of problems when not managed correctly.

The Monorepo Approach: Consolidating Related Code

A monorepo is a single repository containing multiple distinct projects with well-defined relationships. Think of a frontend application, its backend API, and a shared component library all living in the same git repository. The main advantage is the ability to make atomic changes across all of them in a single commit. When an API contract changes, you can update the API server and its clients in the same PR, ensuring they are always in sync.

This is incredibly useful for tightly coupled projects and for enforcing consistency with shared tooling like linters and test frameworks. The problems start to appear with scale. As the repository grows, git clone and git status can become slow. Build systems have to be smart enough to only test and deploy what has actually changed, which requires specialized tooling. Access control also becomes a concern, since giving a contractor access to one project might mean giving them access to the entire codebase.

The Multiple Repository Approach

The alternative is to give each service, application, or library its own repository. This model makes it clear who is responsible for each part. The team that owns the payments service owns the payments-api repository. This independence allows teams to develop, test, and deploy on their own schedule. The repositories are smaller, builds are faster (for that one service), and access control is straightforward.

The trade-off is coordination. Managing dependencies across dozens of repositories is a serious operational burden. A change to a common utility library can trigger a cascade of updates, PRs, and deployments across the organization. Without strong discipline, you end up with "version soup," where different services are running different versions of the same internal library, making bugs hard to track down. Enforcing consistent practices for testing, security, and deployment also requires a lot of effort because there’s no single source of truth.

Key Factors When Choosing a Repository Strategy

The right choice depends entirely on your context. The answer comes from looking at how your code, teams, and processes actually work, not from following a trend. Four factors tend to matter most.

Interdependencies and Coupling

This is probably the most important question to ask: how often do components need to change together? If your frontend and backend are almost always deployed in lockstep, separating them into different repositories creates constant, unnecessary work. You’ll spend more time coordinating PRs and managing versions than you will writing code. The overhead of coordinating changes across repository boundaries is a direct tax on developer productivity. If your services are truly independent and interact through stable, versioned APIs, then multiple repositories might work just fine.

Team Structure and Collaboration Patterns

How are your teams organized? A small, co-located team can easily manage the communication overhead of a monorepo. When everyone is in the same planning meetings, it’s easy to coordinate breaking changes. For large, distributed organizations with teams in different time zones, the clear ownership lines of multiple repositories can reduce communication friction. The question is whether you want to optimize for clear boundaries and asynchronous work (multi-repo) or for seamless cross-team refactoring and shared context (monorepo).

Build, Test, and Deployment Workflows

Your CI/CD pipeline will look very different depending on the model you choose. A monorepo requires an intelligent build system that can identify the subset of the codebase affected by a change and only run the relevant tests and deployments. Without this, CI times will eventually become a major bottleneck. In a multi-repo world, the challenge is different. You need standardized build and deployment pipelines that can be applied across all repositories, and you need a strategy for orchestrating releases that involve changes to multiple services. For example, how do you safely roll out a change that requires both an API and a web app to be updated at the same time?

Tooling Ecosystem and Infrastructure

Monorepos are much more viable today thanks to mature tools like Bazel, Nx, and Turborepo. These tools solve the core problems of task scheduling and remote caching, making it possible to manage huge codebases without crippling build times. Adopting a monorepo without committing to investing in this tooling is a recipe for failure. For multiple repositories, the tooling focus is on dependency management and discovery. You’ll need a private package registry (like Artifactory or GitHub Packages) to host internal libraries, and tools like Dependabot become essential for keeping dependencies up to date. Security scanning and access control also have to be configured and managed for each repository.

A Framework for Evaluation

Instead of looking for a universally correct answer, evaluate your specific situation. The best strategy is the one that causes the least amount of friction for your teams day-to-day.

Assessing Your Current State and Future Needs

Start by analyzing your codebase’s real-world interconnectedness. Look at recent PRs and feature development cycles. How many of them required changes in more than one service or library? If the number is high, that’s a strong signal that the coordination overhead of a multi-repo setup is already costing you. Next, consider your team structure. Are you organized into small, autonomous product teams, or is there a lot of cross-team collaboration? Finally, be honest about the operational overhead. Do you have the platform engineering resources to build out and maintain the specialized tooling a monorepo requires, or the standardization processes a multi-repo setup demands?

What to consider for a monorepo to work well

If you decide a monorepo is the right fit, success depends on a few key practices:

Invest in tooling from day one

You need robust build, test, and code navigation tools. Don’t assume you can just put everything in one folder and figure it out later. Use path-based filtering in your CI so that a change to the documentation doesn’t trigger the backend service’s entire test suite.

Define clear responsibilities

Use `CODEOWNERS` files to define which teams are responsible for which parts of the codebase. This ensures that PRs are routed to the right people and prevents code from becoming orphaned.

Make it easy to find code and manage versions

Make it easy for developers to find and use shared libraries. For internal libraries, you’ll need a clear strategy for versioning within the monorepo to manage breaking changes.

What to consider when managing multiple repositories

If you’re managing multiple repositories, discipline and standardization are critical:

Standardize everything you can

Create templates or "starter kits" for new services that include standardized build scripts, Dockerfiles, linting configurations, and CI/CD pipelines. This prevents configuration drift and makes it easier for developers to move between projects.

Be disciplined about versioning

Use semantic versioning for all shared libraries and APIs. Automate dependency updates as much as possible to avoid falling behind on security patches and bug fixes.

Define clear boundaries and API contracts

When services live in separate repositories, their APIs are the only formal contract between them. These APIs need to be well-documented, stable, and backward-compatible to prevent changes in one service from breaking another.

Re-evaluating Your Strategy: When and How

Your choice is not permanent. You should periodically re-evaluate whether your repository strategy is still serving you well. The primary signal that something is wrong is recurring, painful friction. Are cross-cutting changes taking weeks to roll out across multiple repositories? Are teams constantly blocked waiting for another team to release a new version of a library? Are monorepo build times so slow that developers are avoiding running tests?

When you identify these pain points, consider incremental adjustments before a large-scale migration. If you have a few services in separate repositories that are always changing together, try merging just those into a single monorepo. See if that reduces friction. The goal is to continuously adjust your code organization to match how your teams and systems actually work, not to chase an architectural ideal.