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MONOREPO MASTERY PROJECTS

Monorepo Mastery: Learn by Building

To truly understand monorepos, you need to build systems that exercise their core challenges: dependency management, task orchestration, caching, and change detection. The best way to understand why tools like Nx, Turborepo, and Bazel exist is to hit the same walls they were built to overcome.

Core Concept Analysis

A monorepo is a single repository containing multiple distinct projects (apps, libraries, services) that can depend on each other. It’s NOT a monolith—the projects remain independent but share a unified development environment.

Problems Monorepos Solve

Problem Polyrepo Pain Monorepo Solution
Dependency Hell Syncing versions across 10 repos is a nightmare All packages use the same version, fixed atomically
Code Sharing Creating a shared lib = new repo, CI setup, npm publish Just import from ../shared-lib, done
Breaking Changes “Did my change break another team’s code?” 🤷 You find out immediately in the same commit
Tooling Consistency Each repo has different linting, testing, build configs One eslint.config.js to rule them all
Refactoring Rename a function used in 5 repos? Good luck. Find & replace across entire codebase
Onboarding Clone 12 repos, configure each one Clone once, run npm install, done

Fundamental Building Blocks

  1. Workspaces - Package manager’s ability to link local packages (npm/pnpm/yarn workspaces)
  2. Dependency Graph - DAG (Directed Acyclic Graph) of how packages depend on each other
  3. Task Orchestration - Running builds/tests in correct order based on dependencies
  4. Caching - Never rebuild what hasn’t changed
  5. Affected Detection - Only run tasks for packages touched by your changes
  6. Remote Caching - Share cache across team/CI

Project 1: Multi-Package Workspace from Scratch

  • File: MONOREPO_MASTERY_PROJECTS.md
  • Main Programming Language: TypeScript
  • Alternative Programming Languages: JavaScript, Go, Rust
  • Coolness Level: Level 2: Practical but Forgettable
  • Business Potential: 2. The “Micro-SaaS / Pro Tool”
  • Difficulty: Level 1: Beginner (The Tinkerer)
  • Knowledge Area: Package Management / Build Systems
  • Software or Tool: npm/pnpm workspaces
  • Main Book: The Pragmatic Programmer by Andrew Hunt and David Thomas

What you’ll build: A monorepo with 3 packages (shared-utils, frontend-app, backend-api) where apps consume the shared library—without publishing to npm.

Why it teaches Monorepos: This is the absolute foundation. You’ll understand how workspaces link packages locally, how node_modules is structured in a monorepo, and why you can import { helper } from '@myorg/shared-utils' without publishing.

Core challenges you’ll face:

  • Configuring workspaces (understanding package.json workspaces field) → maps to workspace protocol
  • Cross-package imports (TypeScript path resolution, package.json exports) → maps to code sharing
  • Hoisting behavior (why some deps go to root, others don’t) → maps to dependency deduplication
  • Running scripts across packages (npm run build --workspaces) → maps to task execution

Key Concepts:

Difficulty: Beginner Time estimate: Weekend Prerequisites: Basic npm/node, TypeScript basics

Real world outcome:

# Your monorepo structure
my-monorepo/
├── package.json          # root with workspaces config
├── packages/
│   ├── shared-utils/     # @myorg/shared-utils
│   ├── frontend-app/     # imports from shared-utils
│   └── backend-api/      # imports from shared-utils

# Run from root
$ pnpm install
$ pnpm --filter frontend-app dev
# Frontend runs, using live code from shared-utils!

# Change shared-utils/src/index.ts
# Frontend hot-reloads with the change—no npm publish needed

Learning milestones:

  1. Workspace linking works → You understand the workspace protocol
  2. TypeScript resolves cross-package imports → You understand path mapping
  3. One pnpm install sets up everything → You understand dependency hoisting

Project 2: Shared Component Library with Versioning

  • File: MONOREPO_MASTERY_PROJECTS.md
  • Main Programming Language: TypeScript (React)
  • Alternative Programming Languages: Vue, Svelte, vanilla JS
  • Coolness Level: Level 3: Genuinely Clever
  • Business Potential: 2. The “Micro-SaaS / Pro Tool”
  • Difficulty: Level 2: Intermediate (The Developer)
  • Knowledge Area: Design Systems / Package Publishing
  • Software or Tool: Storybook, Changesets, npm
  • Main Book: Refactoring UI by Adam Wathan & Steve Schoger (design) + Clean Code by Robert C. Martin (architecture)

What you’ll build: A design system monorepo with a ui-components package, a tokens package (colors, spacing), and a docs app—with automated versioning using Changesets.

Why it teaches Monorepos: Real companies use monorepos for design systems because components, tokens, and documentation must stay in sync. You’ll learn why atomic changes matter and how semantic versioning works across packages.

Core challenges you’ll face:

  • Package interdependencies (tokens → components → docs) → maps to dependency graph
  • Semantic versioning across packages (bump tokens = bump components?) → maps to version management
  • Generating changelogs (what changed in this release?) → maps to release automation
  • Publishing workflow (build all, publish in order) → maps to topological sorting

Key Concepts:

  • Changesets Workflow: Changesets Documentation
  • Semantic Versioning: semver.org
  • Topological Sorting: Algorithms Chapter 4.2 - Robert Sedgewick
  • Component Library Patterns: Atomic Design by Brad Frost

Difficulty: Intermediate Time estimate: 1-2 weeks Prerequisites: React basics, Project 1 completed

Real world outcome:

# Make a breaking change to Button component
$ echo "export const Button = () => <button>New API</button>" > packages/ui/Button.tsx

# Add a changeset describing the change
$ pnpm changeset
# Prompts: Which packages? (ui-components)
# Prompts: Semver bump? (major - breaking change)
# Prompts: Summary? "Redesigned Button API"

# When ready to release
$ pnpm changeset version
# ui-components: 1.0.0 → 2.0.0
# CHANGELOG.md updated automatically

$ pnpm changeset publish
# Publishes to npm in correct dependency order

Learning milestones:

  1. Storybook shows components from multiple packages → You understand cross-package composition
  2. Changesets tracks what changed → You understand version management
  3. Publish works without manual ordering → You understand topological builds

Project 3: Build a Dependency Graph Analyzer

  • File: MONOREPO_MASTERY_PROJECTS.md
  • Main Programming Language: TypeScript
  • Alternative Programming Languages: Go, Rust, Python
  • Coolness Level: Level 3: Genuinely Clever
  • Business Potential: 3. The “Service & Support” Model
  • Difficulty: Level 3: Advanced (The Engineer)
  • Knowledge Area: Graph Algorithms / Static Analysis
  • Software or Tool: Graph visualization (D3.js, Graphviz)
  • Main Book: Algorithms by Robert Sedgewick and Kevin Wayne

What you’ll build: A CLI tool that scans a monorepo, builds a dependency graph, detects cycles, and visualizes which packages depend on which.

Why it teaches Monorepos: Every monorepo tool (Nx, Turborepo, Bazel) builds a dependency graph internally. Understanding how to construct and traverse this graph is fundamental to understanding how these tools work.

Core challenges you’ll face:

  • Parsing package.json files (finding all packages, their deps) → maps to workspace discovery
  • Building a DAG (nodes = packages, edges = dependencies) → maps to graph construction
  • Cycle detection (A→B→C→A is bad) → maps to topological validity
  • Topological sort (build order: deps before dependents) → maps to task scheduling
  • Visualization (generate a visual graph) → maps to developer experience

Key Concepts:

  • Directed Acyclic Graphs: Algorithms Chapter 4.2 - Robert Sedgewick
  • Topological Sorting: Introduction to Algorithms (CLRS) Chapter 22.4
  • Cycle Detection (DFS): Algorithms Chapter 4.2 - Robert Sedgewick
  • Graph Visualization: D3.js in Action Chapter 6 - Elijah Meeks

Difficulty: Intermediate-Advanced Time estimate: 1-2 weeks Prerequisites: Data structures (graphs), recursion

Real world outcome:

$ mono-graph analyze ./my-monorepo

📦 Found 8 packages in workspace

Dependency Graph:
  @myorg/tokens (0 deps)
  @myorg/utils (0 deps)
  @myorg/ui-components → @myorg/tokens, @myorg/utils
  @myorg/frontend-app → @myorg/ui-components, @myorg/utils
  @myorg/backend-api → @myorg/utils
  @myorg/e2e-tests → @myorg/frontend-app, @myorg/backend-api

Build Order (topological):
  1. @myorg/tokens, @myorg/utils (parallel - no deps)
  2. @myorg/ui-components, @myorg/backend-api (parallel)
  3. @myorg/frontend-app
  4. @myorg/e2e-tests

$ mono-graph visualize --output graph.svg
# Opens beautiful SVG showing package relationships

Learning milestones:

  1. Tool discovers all packages automatically → You understand workspace structure
  2. Topological sort produces valid build order → You understand DAG algorithms
  3. Cycle detection catches circular deps → You understand graph validation
  4. Visualization renders correctly → You understand the graph structure deeply

Project 4: Build an “Affected” Detector

  • File: MONOREPO_MASTERY_PROJECTS.md
  • Main Programming Language: TypeScript
  • Alternative Programming Languages: Go, Rust, Python
  • Coolness Level: Level 4: Hardcore Tech Flex
  • Business Potential: 3. The “Service & Support” Model
  • Difficulty: Level 3: Advanced (The Engineer)
  • Knowledge Area: Git / Graph Algorithms / CI Optimization
  • Software or Tool: Git, CI/CD (GitHub Actions)
  • Main Book: Pro Git by Scott Chacon (free online)

What you’ll build: A CLI that determines which packages are “affected” by changes in a git commit/branch, so you only build/test what matters.

Why it teaches Monorepos: This is the killer feature of Nx (nx affected) and Turborepo. In a 100-package monorepo, running all tests takes 2 hours. Running tests for just the 3 affected packages takes 2 minutes. Understanding this changes how you think about CI.

Core challenges you’ll face:

  • Git diff parsing (which files changed between commits?) → maps to change detection
  • File-to-package mapping (this file belongs to which package?) → maps to workspace structure
  • Reverse dependency lookup (if A changes, what depends on A?) → maps to impact analysis
  • Transitive closure (if A changes, and B→A, and C→B, then C is affected) → maps to graph traversal

Key Concepts:

  • Git Diff/Log: Pro Git Chapter 2.3 - Scott Chacon
  • Reverse Graph Traversal: Algorithms Chapter 4.2 - Robert Sedgewick
  • Transitive Closure: Introduction to Algorithms (CLRS) Chapter 25.2
  • CI Optimization: Nx Affected Documentation

Difficulty: Advanced Time estimate: 1-2 weeks Prerequisites: Project 3 completed, Git internals basics

Real world outcome:

# You're on a feature branch, changed packages/shared-utils/src/math.ts
$ git diff main --name-only
packages/shared-utils/src/math.ts

$ mono-affected --base=main

🔍 Analyzing changes from main...

Changed packages:
  • @myorg/shared-utils (directly modified)

Affected packages (via dependencies):
  • @myorg/frontend-app (depends on shared-utils)
  • @myorg/backend-api (depends on shared-utils)
  • @myorg/e2e-tests (depends on frontend-app, backend-api)

NOT affected (safe to skip):
  • @myorg/tokens
  • @myorg/docs
  • @myorg/mobile-app

Recommended CI command:
  pnpm --filter @myorg/shared-utils --filter @myorg/frontend-app \
       --filter @myorg/backend-api --filter @myorg/e2e-tests test

Learning milestones:

  1. Tool correctly identifies changed packages → You understand file-to-package mapping
  2. Transitive dependencies included → You understand graph traversal
  3. Integrated with git branches → You understand CI/CD patterns
  4. CI time reduced by 80%+ → You understand why this matters

Project 5: Build a Task Cache System

  • File: MONOREPO_MASTERY_PROJECTS.md
  • Main Programming Language: TypeScript
  • Alternative Programming Languages: Rust, Go
  • Coolness Level: Level 4: Hardcore Tech Flex
  • Business Potential: 3. The “Service & Support” Model
  • Difficulty: Level 4: Expert (The Systems Architect)
  • Knowledge Area: Hashing / Caching / Filesystems
  • Software or Tool: Content-addressable storage
  • Main Book: Designing Data-Intensive Applications by Martin Kleppmann

What you’ll build: A caching layer that hashes inputs (source files, dependencies, env vars) and skips tasks if the output already exists—like Turborepo’s cache.

Why it teaches Monorepos: Caching is why monorepo tools feel magical. Without it, every build rebuilds everything. With it, npm run build takes 200ms because nothing changed. Understanding content-addressable caching fundamentally changes how you think about builds.

Core challenges you’ll face:

  • Input hashing (hash source files + deps + config) → maps to cache keys
  • Output storage (where to store build artifacts?) → maps to content-addressable storage
  • Cache invalidation (when to bust the cache?) → maps to cache correctness
  • Cache restoration (copy cached outputs back to correct locations) → maps to artifact management

Key Concepts:

  • Content-Addressable Storage: Designing Data-Intensive Applications Chapter 3 - Martin Kleppmann
  • Merkle Trees/Hashing: Mastering Bitcoin Chapter 9 - Andreas Antonopoulos
  • Cache Invalidation: Turborepo Caching Documentation
  • Build Determinism: Bazel Hermeticity

Difficulty: Advanced Time estimate: 2-3 weeks Prerequisites: Project 3 & 4 completed, understanding of hashing

Real world outcome:

# First build - nothing cached
$ mono-cache run build

[cache] @myorg/tokens: MISS - building...
[cache] @myorg/utils: MISS - building...
[cache] @myorg/ui: MISS - building...
[cache] @myorg/app: MISS - building...
✓ Build completed in 45.2s

# Second build - nothing changed
$ mono-cache run build

[cache] @myorg/tokens: HIT (restored from abc123)
[cache] @myorg/utils: HIT (restored from def456)
[cache] @myorg/ui: HIT (restored from 789ghi)
[cache] @myorg/app: HIT (restored from jkl012)
✓ Build completed in 0.3s  # 150x faster!

# Modify one file
$ echo "// comment" >> packages/utils/src/index.ts
$ mono-cache run build

[cache] @myorg/tokens: HIT
[cache] @myorg/utils: MISS - building...  # Changed!
[cache] @myorg/ui: MISS - building...     # Depends on utils
[cache] @myorg/app: MISS - building...    # Depends on ui
✓ Build completed in 12.1s  # Only rebuilt what needed it

Learning milestones:

  1. Cache hits work correctly → You understand content hashing
  2. Changing a file invalidates correct packages → You understand cache keys
  3. Outputs are restored correctly → You understand artifact storage
  4. Transitive invalidation works → You understand graph + caching together

Project 6: Build a Parallel Task Runner

  • File: MONOREPO_MASTERY_PROJECTS.md
  • Main Programming Language: TypeScript (Node.js)
  • Alternative Programming Languages: Rust, Go
  • Coolness Level: Level 4: Hardcore Tech Flex
  • Business Potential: 4. The “Open Core” Infrastructure
  • Difficulty: Level 4: Expert (The Systems Architect)
  • Knowledge Area: Concurrency / Process Management / Task Scheduling
  • Software or Tool: Task orchestration (like Nx, Turborepo)
  • Main Book: Operating Systems: Three Easy Pieces by Remzi Arpaci-Dusseau

What you’ll build: A task runner that executes package scripts in parallel (respecting dependency order), streams output correctly, and handles failures gracefully.

Why it teaches Monorepos: Running npm run build across 50 packages sequentially takes forever. Running them in parallel (while respecting dependencies) is 10x faster. This is the core of Turborepo, Nx, and Lage.

Core challenges you’ll face:

  • Topological task scheduling (run deps first, then dependents) → maps to graph-based execution
  • Parallel execution with limits (max 8 concurrent tasks) → maps to concurrency control
  • Output streaming (interleaved output from parallel tasks) → maps to process management
  • Failure handling (if A fails, don’t run B that depends on A) → maps to error propagation
  • Task pipelines (build depends on lint, test depends on build) → maps to task dependencies

Key Concepts:

  • Process Management: Operating Systems: Three Easy Pieces Chapter 5
  • Concurrency Patterns: Node.js Design Patterns Chapter 4 - Mario Casciaro
  • Worker Pools: Rust Atomics and Locks Chapter 8 - Mara Bos (if using Rust)
  • DAG Execution: Turborepo Task Graph

Difficulty: Advanced-Expert Time estimate: 2-3 weeks Prerequisites: Projects 3, 4, 5 completed

Real world outcome:

$ mono-run build --concurrency=4

┌─────────────────────────────────────────────────────┐
│ Running: build across 8 packages (max 4 parallel)  │
└─────────────────────────────────────────────────────┘

[tokens]    ▓▓▓▓▓▓▓▓▓▓ ✓ 1.2s
[utils]     ▓▓▓▓▓▓▓▓▓▓ ✓ 0.8s
[icons]     ▓▓▓▓▓▓▓▓▓▓ ✓ 2.1s
[backend]   ▓▓▓▓▓▓▓▓▓▓ ✓ 3.4s
[ui]        ▓▓▓▓▓░░░░░ building... (depends on tokens, utils, icons)
[frontend]  ⏳ waiting (depends on ui)
[docs]      ⏳ waiting (depends on ui)
[e2e]       ⏳ waiting (depends on frontend, backend)

# Task execution timeline:
# t=0s:  [tokens] [utils] [icons] [backend] start (4 parallel)
# t=0.8s: utils done
# t=1.2s: tokens done
# t=2.1s: icons done → [ui] starts
# t=3.4s: backend done
# t=5.5s: ui done → [frontend] [docs] start (2 parallel)
# t=7.2s: frontend done, docs done → [e2e] starts
# t=9.8s: e2e done

✓ Build completed in 9.8s (sequential would be 24.3s)

Learning milestones:

  1. Tasks run in parallel correctly → You understand concurrency
  2. Dependency order respected → You understand topological execution
  3. Output streams are readable → You understand process I/O
  4. Failures handled gracefully → You understand error propagation

Project 7: Remote Cache Server

  • File: MONOREPO_MASTERY_PROJECTS.md
  • Main Programming Language: Go
  • Alternative Programming Languages: Rust, TypeScript
  • Coolness Level: Level 4: Hardcore Tech Flex
  • Business Potential: 4. The “Open Core” Infrastructure
  • Difficulty: Level 4: Expert (The Systems Architect)
  • Knowledge Area: Distributed Systems / HTTP APIs / Storage
  • Software or Tool: S3/R2 compatible storage, HTTP server
  • Main Book: Designing Data-Intensive Applications by Martin Kleppmann

What you’ll build: A server that stores and serves build cache artifacts, so your entire team and CI share the same cache—like Turborepo Remote Cache or Nx Cloud.

Why it teaches Monorepos: Local caching is good. Remote caching is transformative. When CI builds something, your local machine can use that cache. When your coworker builds, you get their cache. This is why companies pay for Nx Cloud.

Core challenges you’ll face:

  • Cache key → artifact mapping (HTTP API: PUT/GET by hash) → maps to content-addressable storage
  • Artifact storage (local disk, S3, R2) → maps to storage backends
  • Authentication (who can read/write cache?) → maps to security
  • Garbage collection (delete old artifacts) → maps to storage management
  • Cache statistics (hit rate, storage used) → maps to observability

Key Concepts:

  • HTTP API Design: Design and Build Great Web APIs by Mike Amundsen
  • Content-Addressable Storage: Designing Data-Intensive Applications Chapter 3
  • S3-Compatible APIs: MinIO Documentation
  • Authentication Patterns: Web Application Security by Andrew Hoffman

Difficulty: Expert Time estimate: 2-4 weeks Prerequisites: Project 5 completed, HTTP API experience

Real world outcome:

# Start your cache server
$ mono-cache-server --port 3000 --storage=./cache-data
Cache server listening on http://localhost:3000

# Configure your monorepo to use it
$ echo 'MONO_REMOTE_CACHE=http://localhost:3000' >> .env

# CI builds and populates cache
$ CI=true mono-run build
[cache] @myorg/ui: MISS → uploading to remote...
[cache] Uploaded abc123 (2.3 MB) to remote cache

# Your local machine pulls from remote
$ mono-run build
[cache] @myorg/ui: REMOTE HIT → downloading from remote...
[cache] Downloaded abc123 (2.3 MB) in 0.4s
✓ Build completed in 0.8s (remote cache hit!)

# Cache statistics
$ curl http://localhost:3000/stats
{
  "total_artifacts": 1247,
  "storage_used": "4.2 GB",
  "hit_rate": "89.3%",
  "cache_hits_today": 3420,
  "bandwidth_saved": "142 GB"
}

Learning milestones:

  1. Cache upload/download works → You understand content-addressable HTTP APIs
  2. Multiple clients share cache → You understand distributed caching
  3. Auth prevents unauthorized access → You understand security
  4. Old artifacts are cleaned up → You understand storage management

Project Comparison Table

Project Difficulty Time Depth of Understanding Fun Factor
1. Multi-Package Workspace Beginner Weekend ⭐⭐ Foundation ⭐⭐
2. Shared Component Library Intermediate 1-2 weeks ⭐⭐⭐ Versioning ⭐⭐⭐
3. Dependency Graph Analyzer Intermediate-Advanced 1-2 weeks ⭐⭐⭐⭐ Core Algorithms ⭐⭐⭐⭐
4. Affected Detector Advanced 1-2 weeks ⭐⭐⭐⭐ CI Optimization ⭐⭐⭐⭐
5. Task Cache System Advanced 2-3 weeks ⭐⭐⭐⭐⭐ Caching ⭐⭐⭐⭐
6. Parallel Task Runner Advanced-Expert 2-3 weeks ⭐⭐⭐⭐⭐ Concurrency ⭐⭐⭐⭐⭐
7. Remote Cache Server Expert 2-4 weeks ⭐⭐⭐⭐⭐ Distributed ⭐⭐⭐⭐

Recommendation: Your Learning Path

Based on a logical progression, here’s the recommended order:

If you’re new to monorepos:

  1. Start with Project 1 (Workspace basics) - Get comfortable with workspaces
  2. Then Project 2 (Component library) - Understand real-world usage
  3. Then Project 3 (Dependency graph) - Understand the core data structure

If you want to understand how tools like Nx/Turborepo work:

  1. Project 3 (Dependency graph) - The foundation
  2. Project 4 (Affected detection) - The CI killer feature
  3. Project 5 (Caching) - The speed multiplier
  4. Project 6 (Parallel runner) - The orchestration layer

If you want to build your own monorepo tool:

Complete all projects 1-7 in order.

Final Project: Mini-Turborepo

  • File: MONOREPO_MASTERY_PROJECTS.md
  • Main Programming Language: Rust
  • Alternative Programming Languages: Go, TypeScript
  • Coolness Level: Level 5: Pure Magic (Super Cool)
  • Business Potential: 5. The “Industry Disruptor”
  • Difficulty: Level 5: Master (The First-Principles Wizard)
  • Knowledge Area: Build Systems / Developer Tooling / Distributed Systems
  • Software or Tool: Monorepo build system (like Turborepo/Nx)
  • Main Book: Designing Data-Intensive Applications by Martin Kleppmann

What you’ll build: A complete monorepo build tool combining all previous projects: workspace discovery, dependency graph, affected detection, local caching, remote caching, and parallel task execution.

Why it teaches Monorepos: This is the culmination of everything. You’ll understand exactly why Turborepo and Nx make the architectural decisions they do, because you’ll face the same tradeoffs.

Core challenges you’ll face:

  • All previous challenges combined → maps to systems integration
  • Configuration system (turbo.json equivalent) → maps to developer experience
  • Plugin architecture (support different package managers) → maps to extensibility
  • Performance optimization (fast startup, low memory) → maps to systems programming
  • Error messages (helpful errors like Elm/Rust) → maps to developer experience

Key Concepts:

  • CLI Design: The Art of Unix Programming Chapter 10 - Eric Raymond
  • Configuration Parsing: Language Implementation Patterns Chapter 2 - Terence Parr
  • Performance Profiling: Systems Performance Chapter 6 - Brendan Gregg
  • Error Handling: Effective Rust Chapter 4 - David Drysdale

Difficulty: Master Time estimate: 2-3 months Prerequisites: All previous projects completed

Real world outcome:

# Your complete monorepo tool in action
$ mini-turbo run build --filter=@myorg/frontend

┌──────────────────────────────────────────────────────────┐
│  mini-turbo v0.1.0                                       │
│  Packages: 12 │ Affected: 4 │ Cached: 8                  │
└──────────────────────────────────────────────────────────┘

   Dependency Graph:
   @myorg/tokens ─┐
   @myorg/utils ──┼─→ @myorg/ui ─→ @myorg/frontend
   @myorg/icons ──┘

   ● @myorg/tokens   │ ████████████████████ │ CACHE HIT
   ● @myorg/utils    │ ████████████████████ │ CACHE HIT
   ● @myorg/icons    │ ████████████████████ │ CACHE HIT
   ◐ @myorg/ui       │ ████████░░░░░░░░░░░░ │ building...
   ○ @myorg/frontend │ ░░░░░░░░░░░░░░░░░░░░ │ waiting...

   Remote cache: ↓ 3 hits (12.4 MB saved)

✓ Build completed in 4.2s

# Compare to sequential without cache: 2m 34s
# You've built a 36x speedup tool!

Learning milestones:

  1. Tool works end-to-end → You understand the complete system
  2. Cache hits work locally and remotely → You understand distributed caching
  3. Parallel execution with correct ordering → You understand graph-based scheduling
  4. Affected detection works with git → You understand change detection
  5. Someone else can use your tool → You understand developer experience

Key Resources

Official Documentation

Deep Dives

Books

  • Algorithms by Sedgewick & Wayne - For graph algorithms (Projects 3, 4, 6)
  • Designing Data-Intensive Applications by Kleppmann - For caching and distributed systems (Projects 5, 7)
  • Operating Systems: Three Easy Pieces - For concurrency (Project 6)

Summary

Monorepos solve real problems: dependency hell, code sharing friction, breaking changes, and tooling inconsistency. But they introduce new challenges that require sophisticated tooling.

By building these projects, you’ll understand:

  1. Why workspaces exist (linking local packages)
  2. Why dependency graphs matter (build order, affected detection)
  3. Why caching is transformative (10-100x faster builds)
  4. Why parallel execution is complex (respecting dependencies)
  5. Why remote caching is valuable (team-wide benefits)

After completing these projects, tools like Nx, Turborepo, and Bazel won’t be magic—they’ll be obvious solutions to problems you’ve personally experienced.

Sources: