Monorepos offer massive advantages from centralized codebases and shared dependencies to simplified refactoring. But they also come with a challenge that frustrates many teams: painfully slow CI/CD pipelines. As your monorepo grows, even a small change in one module can trigger builds and tests across unrelated parts of the codebase, slowing down feedback loops and killing developer momentum.
If you’re struggling with sluggish CI/CD in a monorepo, you’re not alone. The good news is that there are proven strategies to drastically improve build speed without sacrificing test coverage or deployment safety.
Learn to break down the root of the problem and what your team can do about it with this guide.
Best Practices to Solve Slow CI/CD Builds in Monorepos:
Optimize Builds with Intelligent Change Detection
The single most powerful way to speed up monorepo builds is to build only what changed. Tools like Nx, Bazel, or Turborepo provide smart change detection, so your CI can run only the tests and builds that are affected by a code change.
These tools analyze your dependency graph and execute tasks only for impacted projects. For example, if you change a UI component used in just one frontend app, your backend services shouldn’t rebuild or test at all.
For custom setups, consider writing scripts that detect file changes (e.g., with git diff) and trigger builds conditionally using CI logic. It’s not as robust as a full monorepo toolchain, but still significantly faster than a blanket build approach.
Use Build Caching to Reuse Work
Build caching stores the results of previous builds and reuses them when the inputs haven’t changed. This saves time when you’re making incremental changes or testing the same commits across branches.
Modern tools like Nx Cloud, Bazel Remote Cache, and GitHub Actions Cache integrate seamlessly with monorepos. They track inputs like source code, config files, and environment variables. If nothing has changed, cached outputs like compiled code or test results are used instead of rebuilding from scratch.
You can combine local and remote caches to speed up both individual developer machines and centralized CI pipelines.
Parallelize Everything You Can
CI/CD runtimes often support parallel execution, but monorepo pipelines don’t always make full use of it. Wherever possible:
- Split tasks into independent jobs (e.g., frontend, backend, libs)
- Run tests in parallel by project or file type
- Use matrix builds in GitHub Actions or pipelines in GitLab CI
Parallelism makes a massive difference in larger codebases. Even shaving off 10 minutes per build compounds into hours saved per week when multiple developers are pushing daily.
Just ensure that your tasks are properly scoped to avoid race conditions because each job should have isolated artifacts and environments.
Adopt Incremental Testing Strategies
Running all tests for every commit is overkill in a monorepo. Instead, implement test selection based on affected code. If you touch only a utility function, you shouldn’t need to rerun e2e tests for your entire stack.
Use dependency mapping tools or frameworks that support test impact analysis. For example:
- Jest with –onlyChanged
- Nx test runner with dependency-aware configuration
- Custom test discovery scripts
The goal is to balance speed and confidence: run only what’s necessary but ensure it’s enough to catch regressions.
Modularize the Repository
Even in a monorepo, your architecture matters. Keep boundaries clean between modules, services, and packages. This makes change detection and selective builds easier, and helps teams work in parallel without stepping on each other’s toes.
Use folder conventions (apps/, libs/, tools/) and standardized naming to group components logically. Tools like Lerna, Yarn Workspaces, or Nx help enforce boundaries, manage shared dependencies, and prevent cross-module coupling.
Over time, this modularity enables you to scale without the entire repo slowing down every commit.
Monitor and Continuously Improve Your CI
CI performance isn’t a “set it and forget it” operation. Build times can slowly creep up as projects grow, tests accumulate, and team habits evolve. Regularly review metrics like:
- Average pipeline duration per branch
- Time spent per job (build, test, deploy)
- Cache hit/miss rates
- Flaky or long-running tests
Many CI tools offer dashboards, or you can integrate monitoring with Prometheus, Datadog, or similar platforms. Use alerts to catch regressions in pipeline performance early and fix them before developer frustration builds up.
Why Monorepos Slow Down CI/CD?
Monorepos consolidate multiple services, libraries, and tools into one codebase. This creates opportunities for consistency and reuse, but also causes the CI/CD system to treat every change as potentially impactful across the entire repo. Without careful optimization, that leads to:
- Long build and test times
- High compute costs
- Developer frustration from slow feedback loops
The root issue is usually a lack of granularity. If your CI/CD pipeline doesn’t know exactly what changed or which components depend on it, it defaults to building and testing everything, whether it needs to or not.
Conclusion
Monorepos don’t have to mean slow CI/CD. With techniques like smart change detection, build caching, parallel jobs, and modular architecture, you can regain fast feedback loops and keep development flowing.
Optimizing your pipelines is a performance upgrade and a productivity investment. If you’re managing large codebases and looking for expert help to streamline your CI/CD infrastructure, TRIOTECH SYSTEMS can support your DevOps journey.
