Monorepo (Nx) Configuration for Large Web Projects

Imagine you have 10 applications (Next.js, React, Vue) and 40 TypeScript libraries. After every push, CI takes 40 minutes, even though only one component changed. Sound familiar? We've encountered this dozens of times, so we configure Nx—a system that builds a dependency graph and runs only what's necessary. Learn more about the dependency graph at nx.dev. With over 7 years of experience in monorepo architecture, we guarantee that after configuration, waiting for builds will be a thing of the past. Order Nx configuration, and we'll tailor it to your stack. This Nx monorepo configuration includes Nx code generators, modular architecture enforcement, Nx Cloud CI integration, and workspace setup for Vite Nx, Next.js Nx, and NestJS Nx.

How Nx Solves Problems for Large Teams

Unlike Turborepo, which simply runs scripts, Nx builds a file-level dependency graph. If you change packages/ui/src/Button.tsx, Nx checks which applications use it and runs only their tests and builds. No manual scripts needed—it all works via affected:test and affected:build.

But the real value is architectural control. Using tags (e.g., scope:web, type:util) and the enforce-module-boundaries rule, you can forbid imports from apps/api to apps/web at the linter level. Violations appear red directly in the IDE. This is critical as the team grows and newcomers start pulling server utilities into the frontend. We implement such constraints in every project—it's the foundation of modular architecture. Additionally, Nx leverages incremental builds, computation caching with high cache hit ratio, and distributed task execution (DTE) to orchestrate tasks efficiently.

Why Nx Is Better Than Turborepo for Complex Projects

Turborepo is a great choice for small projects with a single stack. But when you have 5+ applications built on different frameworks, Nx wins. It provides ready-made plugins: @nx/next configures caching for Next.js, @nx/vite for Vite, @nx/nest for NestJS. No need to manually specify inputs and outputs. Nx code generators create components, tests, and Storybook stories from a unified template—standardizing development and speeding up onboarding.

Common Problems and Solutions

How We Configure Nx: The Process

1. Analysis: We study your code structure, current configs (webpack, vite, tsconfig). Collect metrics—number of modules, app types, dependencies.
2. Design: Define tags for modules, dependency rules, configure nx.json. Create an architectural diagram.
3. Implementation: Create the workspace, move projects into apps and packages, connect plugins. Set up generators for new features.
4. Generators: Write custom generators (e.g., nx generate @myorg/feature:component) for standardization.
5. CI/CD: Configure affected commands in GitHub Actions/GitLab CI, connect Nx Cloud if needed. CI runs in 5-15 minutes instead of 40.
6. Testing: Verify that linting, tests, and builds work with nx affected. Add e2e tests for key scenarios.
7. Deployment: Give the go-ahead for the merge request. Developer time savings of up to 80%.

Each stage is documented: you receive not just a configured repository, but a guide on how to work with it. We also train your team (2-hour session). Once we migrated a project with 12 applications in 8 days: CI dropped from 45 to 9 minutes—the team saved over 100 hours per month.

Deliverables

• Configured Nx workspace with nx.json, project.json for each project.
• Plugins for all frameworks in use (Next.js, React, Vue, Angular, NestJS, etc.).
• Generator for creating new features (component template + test + story).
• Typed tags and the enforce-module-boundaries rule.
• CI integration: via Nx Cloud or standalone cache.
• Documentation: how to run tests, builds, deployments.
• Team training: a 1-2 hour session on working with Nx.

This is more than just npx nx generate—we set standards that last for years. We guarantee support for one month after delivery. Get a consultation on Nx configuration—contact us today.

Timelines and Cost Estimates

A fresh setup for 6-10 projects takes 3-5 days. Migrating an existing monorepo from Turborepo or Lerna takes 1-2 weeks depending on custom configs. Setup costs typically range from $3,000 to $7,000, and clients often save $5,000–$10,000 per month in CI costs after migration. Pricing is determined individually—reach out for a project assessment.

Once we migrated a project with 12 applications in 8 days: CI dropped from 45 to 9 minutes, saving the team over 100 hours per month. Order configuration to achieve similar results.

Backend Development Services: Laravel, Node.js, Go, Django, PostgreSQL

On a production server at 3:14 AM, the Laravel Jobs queue stopped processing. 40,000 unprocessed jobs in Redis. Cause: worker crashed due to a memory leak in one of the Jobs (leak via a static variable in an Eloquent observer), supervisor didn't restart it because of misconfigured stopwaitsecs. This is not a hypothetical scenario — it's Tuesday. We analyzed such an incident on a project with 500 RPS load: diagnosis took 4 hours, fix — 20 minutes. So you don't lose money on downtime, we offer backend development services with a focus on production-grade reliability. We'll assess your project in 2 days.

Backend is what works when no one is watching. Or doesn't work. We guarantee you'll have the first option.

How do we ensure production-grade reliability from day one?

What we do correctly from day one

Service Layer over Fat Controllers. Controller receives HTTP request, validates it via Form Request, passes data to Service, returns response. Business logic in Service, not Controller. This sounds trivial, but most legacy projects have controllers with 500 lines and SQL queries inside.

Repository Pattern we use cautiously. If you just wrap Model::where(...) in a repository method — that's boilerplate without benefit. Repository is justified when: you need to abstract from the data source (DB + cache + external API) or when query logic is complex enough to isolate.

Jobs, Events, Listeners. Everything that can be async — make async. Sending email, PDF generation, external API sync, aggregate recalculation — into Queue. Laravel Horizon for queue monitoring in Redis: see throughput, failed jobs, processing time per queue.

How Octane handles high load

Laravel Octane with RoadRunner or Swoole keeps the app in memory between requests — removes bootstrap overhead (config loading, class autoloading) on each HTTP request. Gain: 3–8x on synthetic benchmarks, 2–4x on real applications. Important: no state between requests in static variables — that leads to exactly the incidents from the beginning. We use this in projects with >1000 RPS.

What to do about N+1 queries

N+1 is the most common cause of slow pages in Laravel apps. Standard story: page worked fine on dev with 10 records, on production with 10,000 — 8-second load.

Laravel Debugbar in dev environment shows the number of queries per page. More than 20 queries per page — signal for audit.

Model::preventLazyLoading(! app()->isProduction());

Telescope for profiling in staging: logs all queries, jobs, mail, notifications with time detail. Numbers: after implementing eager loading, page load time drops from 8s to 0.3s — 27 times faster.

PostgreSQL: indexes that are actually needed

PostgreSQL 14+ is the primary DB on all projects. We use PgBouncer + PostgreSQL combination. 10+ years experience, more than 50 backend projects, 5 years on the market.

How PostgreSQL helps avoid slow queries

Composite indexes for frequent WHERE + ORDER BY. If you have WHERE user_id = ? AND status = ? ORDER BY created_at DESC — you need (user_id, status, created_at DESC). A separate index on (user_id) doesn't help much with sorting.

Partial indexes. If 95% of queries go with WHERE status = 'active':

CREATE INDEX idx_orders_active ON orders (created_at DESC)
WHERE status = 'active';

The index is small, fast, covers the main load.

GIN indexes for JSONB and arrays. @> operator without GIN index — seq scan. With index — fast even on millions of rows.

GIN for full-text search. to_tsvector + GIN instead of LIKE '%query%'. LIKE without index is always seq scan. With pg_trgm extension and gin_trgm_ops — supports LIKE with index, useful for CRM search by partial match.

Connection pooling: why it's more important than it seems

Rails, Laravel, Django open a new connection to PostgreSQL for each PHP/Python process. With 100 workers — 100 connections. PostgreSQL starts degrading from 200–300 active connections — overhead on connection management becomes significant.

PgBouncer — connection pooler in front of PostgreSQL. Transaction pooling mode: connection to PostgreSQL is occupied only during a transaction, returned to pool between requests. 1000 application workers → 20–50 actual connections to PostgreSQL. This reduces latency by 40% and hosting costs by 30%.

Node.js with Fastify: when it's better than Laravel

Node.js is justified for:

• Realtime: WebSocket servers, Server-Sent Events, chat, live updates
• Streaming: large files, video, streaming data
• High I/O concurrency: many parallel requests to external APIs without heavy business logic
• Serverless: Lambda/Cloud Functions — Node.js starts faster than PHP

Fastify over Express: 2–3 times faster on benchmarks, built-in JSON Schema validation, better TypeScript support, plugin architecture.

Typical realtime architecture: Laravel — core business logic and REST API. Node.js + Socket.io or ws — WebSocket server. Laravel publishes events to Redis Pub/Sub, Node.js subscribes and broadcasts to clients. This separation allows scaling the WebSocket server independently of the main app.

Go: microservices and high load

Go we use for:

• High-load microservices (>10,000 RPS)
• Background workers with strict latency requirements
• DevOps tools and CLI
• gRPC services in microservice architecture

Goroutines — thousands of times cheaper than OS threads. 10,000 concurrent connections on Go is normal on one server.

But Go is not a silver bullet. Development is slower than Laravel: more boilerplate, no ORM at Eloquent level, error handling with if err != nil everywhere. Justified only when performance is a real requirement, not an assumption.

Django and Python backend

Django with DRF (Django REST Framework) — for tasks where Python is needed: ML pipelines, data processing, integrations with AI tools.

Celery for background tasks — similar to Laravel Queue but more complex to configure. Celery Beat for cron tasks.

Django ORM vs raw SQL: ORM is convenient for CRUD. For analytical queries with multiple JOINs, window functions, and CTEs — connection.execute() with raw SQL is more readable and predictable.

Redis: not just cache

Redis in our projects plays multiple roles:

Redis Cluster for horizontal scaling. Sentinel for automatic failover on standalone setups.

Deployment and infrastructure

Docker + docker-compose — standard for local development and production. Each service in a container: PHP-FPM/Octane, Nginx, PostgreSQL, Redis, Queue Worker, Scheduler.

CI/CD via GitHub Actions:

1. Run tests (PHPUnit / Pest, Vitest, Playwright)
2. Build Docker image
3. Push to Container Registry
4. Deploy: docker pull → docker-compose up -d on server, or Kubernetes rolling update

Zero-downtime deploy for Laravel: php artisan down --secret=TOKEN is not needed with proper configuration. Strategy: new container starts next to the old one, Nginx switches traffic after health check, old container stops.

Monitoring: Sentry for exception tracking with alerting in Slack/Telegram. Grafana + Prometheus (or Grafana Cloud) for metrics: CPU, memory, request rate, queue depth, database connection count. Alerts on: error rate > 1%, p99 latency > 2s, queue depth > 1000 jobs.

What's included in turnkey work

• Architecture design (API documentation, DB schema, service diagram)
• Implementation according to agreed specification with code review
• CI/CD, monitoring, alerting setup
• Load testing (k6, wrk) with report
• Handover of source code, access, deployment instructions
• Training of customer's team (2-3 sessions)
• Warranty support for 1 month after delivery

Timeline benchmarks

Pricing is calculated individually after analyzing load, integrations, and business logic. Contact us for a free audit of your current backend — get an optimization plan in 2 days. Request a consultation.