When we first introduced Nx into our Angular monorepo(Part 1 - Tackling Common Bottlenecks in Angular), the immediate productivity boost was undeniable. Scaffolding apps, generating libraries, and enforcing module boundaries all felt like the right direction for our frontend architecture design. But as the codebase grew, we ran into a familiar wall: build times.
The usual tricks—affected commands, incremental builds, and parallel execution—helped (see Part 1), but they weren’t enough. That’s when caching and distributed execution became game changers.
In this article, I’ll break down how Nx caching actually works, how to configure it properly, when to extend it into distributed builds with Nx Cloud, and how these strategies fit into modern frontend architecture patterns and frontend architecture guidelines for large teams.
Why Caching Matters in Front-end Architecture
Before diving into Nx, let’s zoom out. In any frontend architecture design, caching is the art of avoiding repeated work. Whether it’s browser caching assets or server-side caching database queries, the principle is simple: don’t redo work you’ve already done.
In monorepos, caching applies to tasks like builds, tests, and linting. If nothing about the source has changed, why re-run the entire process? Nx takes this principle and bakes it directly into its execution engine.
How Nx Local Caching Works
Nx records the inputs and outputs of every task you run. Inputs include things like source files, configuration, and environment variables. Outputs are build artifacts like transpiled JS files, test results, or linting reports.
Flow of a Cached Build
1. Developer runs `nx build my-app`
2. Nx hashes inputs (source files, tsconfig, env)
3. Checks if hash exists in local cache
- Yes → returns result instantly
- No → runs build, stores result in cache
Example: Speeding up builds
The first build might take 3 minutes. The second build—if no files have changed—finishes in under a second because Nx just pulls from the local cache.
This is caching in action, and it aligns with solid frontend architecture guidelines: make builds reproducible and predictable.
Nx Cloud and Distributed Execution
Local caching is powerful, but in a team setting, it only goes so far. Imagine developer A runs tests on a branch, and developer B checks out the same branch later. With local cache only, B won’t benefit from A’s work.
This is where Nx Cloud comes in.
What Nx Cloud Adds
- Remote Caching: Cache results are stored in Nx Cloud, so builds/tests done by one dev or in CI can be reused by everyone.
- Distributed Execution: Tasks can be split across multiple machines/agents in CI, drastically reducing overall pipeline times.
- Analytics & Insights: Track task timings and identify slowest libraries or apps.
Example: Connecting to Nx Cloud
npx nx connect-to-nx-cloud
Once connected, every cached result becomes a shared resource for the entire team.
Real-world Scenario
We had a CI pipeline that built 15 Angular apps in sequence. Total runtime: ~45 minutes. After enabling Nx Cloud with distributed execution, we parallelized tasks across 4 agents. Total runtime dropped to ~7 minutes.
This wasn’t just a performance boost—it was a cultural shift. Developers trusted CI again, and release velocity skyrocketed.
Common Pitfalls with Caching
Like any powerful tool, caching has sharp edges if misused.
1. Environment Variables in Cache Keys
If your builds depend on environment variables (API_URL, NODE_ENV) but they aren’t included in the hash, Nx might serve stale results.
Fix: Define environment variables as runtime inputs in nx.json.
{
"tasksRunnerOptions": {
"default": {
"options": {
"runtimeCacheInputs": ["API_URL", "NODE_ENV"]
}
}
}
}
2. OS and Node Version Differences
Caches can differ between Windows, Linux, and Mac if paths or tooling differ.
Guideline: Standardize Node versions with .nvmrc and use consistent tooling across dev/CI environments.
3. Cache Invalidation
Sometimes you need a fresh build (e.g., dependency upgrades).
nx reset
This clears the cache.
Integrating Caching into CI/CD
Caching isn’t just a developer convenience—it’s part of modern frontend architecture design. In fact, CI/CD pipelines benefit the most from caching because repetitive builds are the norm there.
Example: GitHub Actions Workflow
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Use Node.js
uses: actions/setup-node@v2
with:
node-version: 18
- run: npm ci
- run: npx nx affected:build --parallel --max-parallel=4
With Nx Cloud, builds are cached across PRs and branches, so if a library is unchanged, it’s instantly pulled from cache.
Distributed Execution in Practice
Distributed execution isn’t just for giant enterprises. Even mid-sized teams benefit from splitting workloads.
Example: Testing at Scale
Without distribution:
- 1200 tests across 10 apps → 20 minutes total
With distribution (4 agents):
- Split tests evenly → 5–6 minutes total
That’s a 3x improvement with no code changes—just better use of infrastructure.
Caching as a Frontend Architecture Pattern
If we step back, caching isn’t just a build trick. It’s a frontend architecture pattern—one that applies to assets, state, and now builds.
- Browser caching: Don’t reload assets unnecessarily
- State caching: Don’t refetch data if it hasn’t changed (React Query, Apollo)
- Build caching: Don’t recompile code that hasn’t changed
Seen this way, Nx caching is simply the application of a timeless architectural principle: avoid wasted work.
Guidelines for Effective Nx Caching
Here are my go-to frontend architecture guidelines when setting up Nx caching:
- Always enable local caching – zero downside, massive upside.
- Use Nx Cloud early – don’t wait until CI is crawling.
- Define runtime inputs – avoid cache poisoning from env vars.
- Monitor cache hits/misses – treat cache hit ratio as a key performance metric.
- Educate your team – caching is only effective if everyone understands how it works.
Case Study: From Painful Builds to Lightning CI
When I joined one SaaS project, build times were the team’s number one frustration. Developers joked that they could grab coffee twice before CI finished.
Here’s what we did:
- Enabled local caching → dev builds sped up immediately
- Connected Nx Cloud → shared cache across devs/CI
- Introduced distributed execution → CI cut from 45 min → 7 min
- Set cache hit KPIs → regularly reviewed misses and fixed root causes
The transformation was night and day. Productivity went up, morale improved, and we shipped features faster.
Frequently Asked Questions (FAQs)
Q: Is Nx caching safe for production builds?
Yes. Nx caches build artifacts, not runtime state. If inputs are unchanged, outputs are identical.
Q: Can I use caching without Nx Cloud?
Absolutely. Local caching works out of the box. Nx Cloud just extends it team-wide.
Q: How does this tie into frontend architecture design?
Caching is a foundational principle in frontend architecture patterns. Nx brings that principle to build systems, aligning with broader frontend architecture guidelines.
Final Thoughts
Caching and distributed execution aren’t just performance hacks. They’re part of sustainable frontend architecture design for modern teams. They embody the timeless principle of avoiding wasted work and scaling efficiently.
- Frontend architecture patterns like caching apply across browser, state, and builds.
- Nx gives us a way to implement those patterns effectively in Angular monorepos.
- The best results come when caching is embraced not just in tooling, but in team culture.
In Part 3, we’ll tackle structuring large Angular monorepos for performance—because caching alone can’t save you if your workspace design is flawed.
