How to Solve Slow CI/CD Builds in Monorepos: Tips for Faster Development

A monorepo gets your whole team a single source of truth, one repository, shared tooling, atomic commits across services. It does not automatically get you fast builds. Left unmanaged, a growing monorepo’s CI/CD pipeline degrades the same way slowly, then all at once: a 3-minute build becomes 15 minutes becomes 45, until a “quick fix” PR means a coffee break waiting for CI, every single time. This guide covers why monorepo builds actually get slow, the real tools and techniques that fix it in 2026, and the mistakes that make the problem worse instead of better.

Why Monorepo Builds Get Slow

The core problem is simple to state and easy to ignore until it hurts: without deliberate configuration, most CI systems rebuild and retest everything on every commit, regardless of what actually changed. Touch one file in a shared utility package, and a naive pipeline rebuilds and retests every service that could theoretically depend on it, often every service in the repo, even when the actual change affects almost nothing.

This gets worse as the monorepo grows. More packages means more theoretical dependencies to account for. More contributors means more commits triggering full rebuilds. Without a system tracking what actually changed and what’s actually affected, the pipeline’s runtime scales with the size of the whole repository, not the size of the change someone just made.

The Two Mechanisms That Actually Fix This

Dependency graphs and affected-only builds. Modern monorepo tools model which packages depend on which others, so a change only triggers rebuilds and tests for packages actually affected by it, not the entire repository. Nx uses this to compute exactly which projects are “affected” by a given change; Turborepo works similarly at the package level, and Bazel and Buck2 go further, modeling dependencies at the individual source-file level for more precise (if more complex to configure) rebuild scoping.

Remote caching. Local incremental builds help the one engineer running them. Remote caching helps the entire team: if another engineer already built and tested a specific combination of code, that cached result gets reused instead of rebuilt from scratch, sometimes even across different machines and CI runs entirely. This is often the single highest-leverage change a slow monorepo can make, a real 2026 benchmark shows Turborepo reducing build times by up to 70% in large JavaScript/TypeScript projects specifically through this combination of caching and selective task orchestration. It’s worth noting the direct cost angle too: every minute of redundant CI compute is billed the same as a minute of useful work, which is exactly the kind of waste FinOps cloud cost optimization work is built to surface.

Choosing the Right Tool for 2026

The practical 2026 consensus: start with Turborepo if your primary problem is “CI is slow because every package rebuilds” and you want the smallest process change. Move to Nx when you need more sophisticated governance, code generation, or complex cross-project dependency rules. Reach for Bazel or Buck2 only once you’re operating at a scale where hermetic, fully reproducible builds across multiple languages genuinely justify the setup cost, for most teams, that threshold is further away than it feels when the current pipeline is just annoying.

Fixing Flaky Tests

Flaky tests, tests that pass and fail inconsistently with no code change, are a distinct problem from slow builds, but they compound each other badly: a team that doesn’t trust CI results starts re-running failed builds “just in case,” which multiplies build time on top of whatever’s already slow. Common causes include tests with hidden timing dependencies, shared state leaking between test runs, and tests unintentionally depending on execution order. Isolating and quarantining known-flaky tests (running them separately, not blocking the main pipeline) is usually more productive short-term than trying to fix every flaky test before addressing build speed at all.

A Practical Optimization Checklist

1. Measure before optimizing: Identify which specific jobs or steps actually consume the most CI time, optimizing a fast step while ignoring the slowest one wastes effort. This is the same continuous monitoring discipline that matters for any production system, applied to your build pipeline instead of your runtime infrastructure.
2. Adopt affected-only builds first: This is almost always the highest-leverage single change, and most modern monorepo tools support it directly.
3. Enable remote caching: Local caching alone only helps the individual developer; remote caching helps every CI run and every teammate.
4. Parallelize independent tasks: Tests and builds for genuinely unrelated packages should run concurrently, not sequentially, wherever your CI provider supports it.
5. Separate fast feedback from full validation: A quick lint-and-unit-test pass on every commit, with a fuller integration suite reserved for merge-to-main or scheduled runs, keeps day-to-day feedback fast without skipping thorough validation entirely.
6. Quarantine flaky tests rather than ignoring them: Isolate them from blocking the pipeline while tracking them for an actual fix, instead of letting the whole team develop a habit of re-running failed builds.
7. Revisit your package manager. pnpm’s workspace model is commonly paired with Turborepo and Nx specifically for its speed advantages in monorepo dependency installation.

The Bottom Line

Slow monorepo CI/CD is rarely a mystery once you look at the actual cause: most pipelines rebuild far more than the change in question actually requires. Affected-only builds and remote caching are the two mechanisms that fix this, and choosing between Turborepo, Nx, and Bazel comes down to how much governance and precision you need versus how much setup complexity you’re willing to take on. Fix the rebuild scope and caching first, that’s usually where most of the actual time savings are, before reaching for a heavier tool than the problem requires.

When This Needs Real Engineering Investment

Getting affected-only builds and remote caching configured correctly the first time, instead of after months of accumulated CI frustration, is real DevOps engineering work, closely related to the YAML pipeline fundamentals covered in our companion guide. Once your pipeline is fast and reliable, the same engineering discipline extends naturally into database maintenance and middleware vs. API gateway architecture, different layers of the same system, all needing the same “measure, then fix the actual bottleneck” approach. If your team’s CI/CD has become slow enough to actually cost real development velocity, that’s exactly the kind of AIOps and DevOps work we do, reach out if you want it fixed properly rather than incrementally patched.

Frequently Asked Questions

Why is my CI/CD pipeline so slow in a monorepo? 

Most commonly because the pipeline rebuilds and retests the entire repository on every commit instead of only the packages actually affected by the change, the problem compounds as the repo and team both grow.

What’s the difference between Turborepo and Nx? 

Turborepo is a lighter-weight task runner focused on caching and parallel execution for JavaScript/TypeScript projects. Nx is broader, modeling the full project dependency graph and adding governance, code generation, and more sophisticated affected-command logic, at the cost of a steeper setup.

Does remote caching actually make a meaningful difference? 

Yes, often the single biggest improvement available, real 2026 benchmarks show reductions of up to 70% in large JavaScript/TypeScript monorepos when combined with selective task orchestration, since previously-built results get reused across the team instead of rebuilt from scratch.

Should I switch to Bazel to fix slow builds? 

Usually not as a first step. Bazel’s hermetic, source-file-level dependency tracking is powerful but requires significant setup investment, most teams get substantial improvement from Turborepo or Nx first, and should only consider Bazel once operating at a scale that genuinely requires it.

How do I deal with flaky tests in CI? 

Isolate and quarantine known-flaky tests so they don’t block the main pipeline while you investigate the root cause, usually hidden timing dependencies or shared state between tests, rather than letting the team develop a habit of blindly re-running failed builds.

What’s an “affected” build? 

A build that only rebuilds and tests the specific packages impacted by a given change, determined by analyzing the monorepo’s dependency graph, instead of rebuilding the entire repository regardless of what actually changed.