Prod Forge – reference project for running a NestJS service in production

DayTradingCentral – Free Trading Journal (Next.js, NestJS, Postgres)

Reqlog – live HTTP request dashboard for NestJS/Express/Fastify, zero config

NestJS is a bad TypeScript framework

I’m a Computer Engineering student from Brazil. I built this to showcase backend patterns that go beyond simple CRUDs: row-level multi-tenancy (Prisma), async processing (BullMQ&#x2F;Redis), and observability (OpenTelemetry). Looking for feedback on the architecture!

Show HN: Production-Ready NestJS Back End (Multi-Tenancy, Event-Driven)

Every time you spin up a new project with an AI agent, you&#x27;re burning tokens on the same problems. Auth. Connection pooling. CI pipeline. Docker setup.Database migrations. Backend wired to frontend. Problems that were solved on the last project, and the one before that.Boilerworks is a CLI that skips all of it. 26 production-ready templates across 10 stacks. Your agent starts on the actual problem, not the scaffolding.pip install boilerworks 
 boilerworks initWhat you get out of the box: multi-stage CI, Docker Compose, Terraform, structured logging, test infrastructure, auth scaffolding. Not stubs — working code.Stacks: Django, FastAPI, Go, Rails, Laravel, NestJS, Spring, Elixir, Rust, Svelte.No lock-in. Standard libraries throughout. The generated code doesn&#x27;t know Boilerworks exists.Repo: <a href="https:&#x2F;&#x2F;github.com&#x2F;ConflictHQ&#x2F;boilerworks" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;ConflictHQ&#x2F;boilerworks</a>
Docs: <a href="https:&#x2F;&#x2F;boilerworks.dev" rel="nofollow">https:&#x2F;&#x2F;boilerworks.dev</a>

Show HN: Boilerworks – don't pay tokens to re-solve auth and CI on every project

I recently ran an audit on our latest full-stack repo to figure out why &quot;spinning up a new project&quot; felt like such a heavy lift. I counted every file required just to reach a &quot;production-ready&quot; baseline—before writing a single line of unique feature code.The count was roughly 600 files.To be clear, I&#x27;m not talking about a `create-react-app` sandbox. I mean a compliant, scalable SaaS foundation: Next.js frontend, Node.js&#x2F;NestJS backend, mobile wrapper, CI&#x2F;CD pipelines, and enough security config to pass a SOC2 audit.It sounds ridiculous (and honestly, it feels ridiculous), but when I broke it down, I couldn&#x27;t find many files I was willing to delete.Here is where the bloat comes from:First, the &quot;Configuration Hell&quot; accounts for about 40-50 files alone. We aren&#x27;t just dealing with `package.json` anymore. It&#x27;s `tsconfig.json` (base), `tsconfig.build.json`, `tsconfig.spec.json`... multiplied across frontend, backend, and shared libraries. Then add `.eslintrc.js`, `.prettierrc`, `jest.config.js`, `vitest.config.ts`, `nodemon.json`, and the Docker-compose variants for dev, test, and prod.Then there’s the DevOps and Quality layer. We have roughly 20-30 files for GitHub Actions workflows (lint, test, build, deploy, semantic release), Husky hooks (pre-commit, commit-msg), and pull request templates.But the real multiplier is the separation of concerns. In a modern monorepo, a &quot;Hello World&quot; isn&#x27;t just `console.log`. It’s:
- A NestJS module (Controller, Service, Module, DTO, Entity, Unit Test, E2E Test).
- A Next.js slice (Page, Component, Type definition, API client wrapper).
- A shared library entry.We found that adding a single &quot;minimal&quot; API endpoint usually touches 5-7 files just to maintain architectural standards.The trade-off is painful. On one hand, this setup handles the things we used to forget: security headers, proper logging, consistent error handling, and type safety across boundaries. It prevents the &quot;spaghetti code&quot; distinct to startups that scale too fast.On the other hand, the cognitive load of managing a 600-file &quot;empty&quot; project is massive. Updating dependencies becomes a chore because a major version bump in one tool (like ESLint) cascades through forty config files.I’m curious how others are handling this &quot;starting line&quot; complexity.Are you accepting the boilerplate as the cost of doing business? Or have you found a way to strip this down without sacrificing the compliance&#x2F;safety guardrails that enterprise clients demand?It feels like we&#x27;ve over-engineered the entry point of software development, but I’m not sure what the alternative is for a serious project. We tried going &quot;lean&quot; initially, but spent weeks retrofitting auth and testing harnesses later—which was worse.Is there a middle ground I&#x27;m missing, or is ~600 files just the new normal?

Tell HN: A production-ready "Hello World" is now ~600 files

I built Easemonitor to keep track of service uptime, response times, SEO, vulnerability scans, etc.
It&#x27;s 100 % open‑source (GPL‑3), runs in Docker on a cheap VPS and includes:NestJS API + worker with BullMQ queues
NextJS frontend with SSR caching &amp; image optimization
Prometheus metrics, Loki logs, Grafana dashboards, Jaeger tracing
JWT rotation, WAF rules, CSP&#x2F;HSTS, CVE audit scripts
Webhook DLQ, queue dashboard, healthchecks, maintenance mode
You can try it on my demo <a href="https:&#x2F;&#x2F;easemonitor.com" rel="nofollow">https:&#x2F;&#x2F;easemonitor.com</a>Would love feedback, contributions, or ideas for features.

Show HN: Easemonitor – self‑hosted uptime and performance monitoring

California&#x27;s AB 1043 takes effect January 2027. If your app serves California users, you&#x27;ll need to request OS-level age signals from Apple&#x2F;Google and treat them as &quot;actual knowledge&quot; of a user&#x27;s age. Penalties are $7,500 per affected child for intentional violations.We started building A3 (<a href="https:&#x2F;&#x2F;www.a3api.io" rel="nofollow">https:&#x2F;&#x2F;www.a3api.io</a>) after realizing the law has a gap nobody was talking about: browsers have no OS age signal. If you have a web app, the law creates compliance obligations but the platform provides no mechanism. And on native, you&#x27;re left stitching together Apple&#x27;s Declared Age Range API and Google&#x27;s Play Age Signals yourself — two different APIs, two different response formats, two different integration paths.The standard industry answer is ID uploads and selfie scans. We didn&#x27;t want to build that. Those approaches tank conversion rates, create PII liability, and feel disproportionate to the problem. So we went a different direction: passive behavioral signal fusion.The idea is that children and adults interact with devices differently in measurable ways — motor control, scroll patterns, typing rhythm, form completion speed. Our browser SDK (&lt;5 KB) collects these signals from standard DOM events, computes aggregate scores on-device, and sends only anonymized ratios and averages. No raw coordinates, no keystroke logs, no text content ever leaves the browser. The API processes everything in memory and discards it immediately.On native, we normalize the Apple&#x2F;Google OS signals into a single response. On the web, the behavioral signals become the primary assessment. Either way you get the same response format: a verdict, age bracket, confidence score, evidence tags, and an HMAC-SHA256 signed receipt for your audit trail.To be upfront about limitations: behavioral signals are probabilistic, not deterministic. A confident 12-year-old and a hasty adult can look similar in a short session. We mitigate this with five signal categories (behavioral metrics, input complexity, device context, contextual signals, account longevity) that are weighted and cross-validated, and we apply coverage penalties when fewer categories are present. But this is age estimation, not identity verification — it&#x27;s designed for the &quot;commercially reasonable&quot; standard the statute actually requires, not the false certainty that ID checks imply.The stack is NestJS on AWS Lambda, with client SDKs for React&#x2F;Vue&#x2F;vanilla JS, SwiftUI, and Jetpack Compose. There&#x27;s a free tier (100 checks&#x2F;month) if you want to kick the tires, and a playground at <a href="https:&#x2F;&#x2F;www.a3api.io&#x2F;playground" rel="nofollow">https:&#x2F;&#x2F;www.a3api.io&#x2F;playground</a>.If you maintain an open source project, we have a program that gives you Pro-tier access (50k checks&#x2F;month) for free — the only requirement is a &quot;Powered by A3&quot; in your age gate UI or README. Details at <a href="https:&#x2F;&#x2F;www.a3api.io&#x2F;open-source" rel="nofollow">https:&#x2F;&#x2F;www.a3api.io&#x2F;open-source</a>.Docs: <a href="https:&#x2F;&#x2F;www.a3api.io&#x2F;docs" rel="nofollow">https:&#x2F;&#x2F;www.a3api.io&#x2F;docs</a>Happy to answer questions about the signal fusion approach, the legal nuances, or where we think this falls short.

Show HN: Complying with California's AB 1043 via signal fusion, not ID uploads

Hi HN,I kept finding myself writing scripts or manually running prompts to do things like PR reviews, documentation generation, or issue triage on my GitHub repositories.After doing this enough times, I decided to build a small platform to automate these workflows.I recently open sourced it:<a href="https:&#x2F;&#x2F;github.com&#x2F;Njuelle&#x2F;Codaholiq" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;Njuelle&#x2F;Codaholiq</a>Codaholiq lets you run AI-powered workflows triggered by GitHub events.You connect a repository and define automations that run when certain events occur, such as:- pull request opened
- push to a branch
- issue created
- cron schedule
- manual triggerEach automation defines:- a trigger
- an AI provider or model (Claude Code, Codex, Gemini, etc.)
- a prompt template
- optional conditions on the GitHub event payloadWhen the event happens, Codaholiq renders the prompt using variables from the event context and dispatches a GitHub Actions workflow that runs the AI task.The platform also tracks executions with:- real-time log streaming
- token usage and cost tracking
- execution historyOne design goal was self-hosting, so the entire platform can run locally or on your own infrastructure.The architecture is intentionally simple:- GitHub webhooks trigger automations
- jobs are queued using Redis and BullMQ
- the NestJS backend processes the queue and dispatches workflows to GitHub Actions
- AI models are called through providers
- logs and token usage are streamed back to the UIThe full platform can run with Docker using Postgres and Redis.Example automation:An automation could trigger when a pull request is opened. 
It sends the PR diff to an AI model asking for a code review, then runs the task through a GitHub Actions workflow.Some possible use cases:- automated PR reviews
- generating documentation from diffs
- code refactoring suggestions
- issue triage
- automatic changelog generationIt&#x27;s still early, but the core pieces are working.One thing I&#x27;m unsure about is whether this project makes more sense as:- a self-hosted automation tool
- or a hosted version that simplifies setup and managementI&#x27;m curious how teams here would prefer to run something like this.Any feedback is very welcome.

Show HN: Codaholiq, AI automations for GitHub repositories

Focido is now live on App Store and Google Play after months of beta testing and weekly updates.What is it?
A social to-do app where your goals live in a feed, and real humans (not AI) send nudges to help you follow through. We built it because solo trackers have ~20% completion rates, while social accountability apps like Strava get people moving consistently.Key features:Post tasks, get matched with motivatorsReal-time nudges, replies, and task visibilityNudge limits, cooldowns, anonymous tasks for privacyLeagues, leaderboards, and motivator ratingsCustom reminder windows so it fits your scheduleTech:
Flutter (iOS&#x2F;Android), NestJS&#x2F;Supabase backend, RevenueCat for IAP. Real-time with Supabase. MVP in ~4 months.Why we built it:
Most productivity apps fail at completion. Humans are better at creating the right kind of pressure (guilt + reciprocity). Early data shows 3x completion uplift vs solo apps.Links:
iOS: <a href="https:&#x2F;&#x2F;apps.apple.com&#x2F;us&#x2F;app&#x2F;focido&#x2F;id6757135734">https:&#x2F;&#x2F;apps.apple.com&#x2F;us&#x2F;app&#x2F;focido&#x2F;id6757135734</a>
Android: <a href="https:&#x2F;&#x2F;play.google.com&#x2F;store&#x2F;apps&#x2F;details?id=com.focido.app.focido">https:&#x2F;&#x2F;play.google.com&#x2F;store&#x2F;apps&#x2F;details?id=com.focido.app...</a>
Website: 
<a href="https:&#x2F;&#x2F;focido.com" rel="nofollow">https:&#x2F;&#x2F;focido.com</a>Open to questions about retention, matching, or the economics of human motivators. Curious what HN thinks of social accountability vs gamification.

Show HN: Focido – social to-do where real people nudge you to finish tasks

I got tired of this loop:add console.log → redeploy → reproduce → squintBuilt reqlog. One import, a dashboard opens at 
localhost:9000, you see everything in real time — 
payload, response, latency, replay button.NestJS:
@Module({ imports: [ReqlogModule.forRoot()] })Express:
app.use(require(&#x27;reqlog-express&#x27;)())That is the entire setup.github.com&#x2F;FirasLatrech&#x2F;reqlog

Show HN: Reqlog – live HTTP dashboard for Node.js and Go

Anthropic just launched Remote Control for Claude Code. It lets you control a coding session from your phone or browser. Cool idea, except it requires a $200&#x2F;mo Max plan, supports one session at a time, has no auto-approve rules or hook management, and kills your session if the terminal closes or you lose network for 10 minutes.I built ForkOff because I kept coming back from skiing and biking to find my Claude Code sessions dead. I wanted to approve tool calls from my phone while I was out, not babysit a terminal.ForkOff is the open-source alternative:- Free (MIT licensed)
- E2E encrypted — the relay server sees only opaque blobs
- Auto-approve rules — configure which tools are safe, which need manual approval
- Proper diff rendering on mobile, not raw terminal text
- Sessions survive terminal close
- Self-hostable relay, or --local flag for direct P2P (zero internet)
- Multi-session supportStack: React Native + Expo (mobile), NestJS (relay), Node.js CLI that hooks into Claude Code&#x27;s PreToolUse&#x2F;PostToolUse lifecycle via the SDK. X25519 key exchange, XSalsa20-Poly1305 encryption.iOS beta is live on TestFlight. Android coming soon.We are looking forward to feedback, code contributions, and more!TestFlight: <a href="https:&#x2F;&#x2F;testflight.apple.com&#x2F;join&#x2F;dhh5FrN7" rel="nofollow">https:&#x2F;&#x2F;testflight.apple.com&#x2F;join&#x2F;dhh5FrN7</a>
(Note: We are currently pending apple&#x27;s review on the open-source version of the app expect the release on the above link within 24 hours till then the app config will show that you require an update)GitHub (CLI): <a href="https:&#x2F;&#x2F;github.com&#x2F;Forkoff-app&#x2F;forkoff-cli" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;Forkoff-app&#x2F;forkoff-cli</a>
GitHub (Mobile): <a href="https:&#x2F;&#x2F;github.com&#x2F;Forkoff-app&#x2F;forkoff-react-native" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;Forkoff-app&#x2F;forkoff-react-native</a>
Website: <a href="https:&#x2F;&#x2F;forkoff.app" rel="nofollow">https:&#x2F;&#x2F;forkoff.app</a>

Show HN: ForkOff – Orchestrate Your Claude Agents, Anytime, Anywhere

Hi HN, I&#x27;m the author.I&#x27;ve spent years building Node.js backends (mostly Express and NestJS) and I’ve consistently found traditional ORMs like TypeORM too heavy, while Prisma’s subscription models didn&#x27;t quite fit my need for lightweight CDC (Change Data Capture). I wanted something universal that felt closer to the metal but still handled real-time events seamlessly.Over the past couple of days, I built Kinetic SQL. It&#x27;s a thin, highly flexible SQL wrapper for Node.js (supporting Postgres, MySQL, and SQLite).The CORE focus:
Framework Agnostic: Works beautifully with Express, Fastify, or Vanilla Node, with a dedicated seamless-integration module for NestJS included as a bonus.Real-time Subscriptions: Listen to table changes (INSERT&#x2F;UPDATE&#x2F;DELETE) natively and push to clients (perfect for live dashboards).Zero-Touch Interfaces: The CLI (npx k-sql gen) reads your schema and auto-generates absolute type safety. No more writing interfaces by hand.Native DB Functions: Call your database procedures directly as native JavaScript methods.To stress-test the real-time engine, I built a high-frequency stock market simulator (running on a free Vercel&#x2F;Render stack with a 0-second cold start):Live Demo: <a href="https:&#x2F;&#x2F;live-stock-simulator.vercel.app&#x2F;" rel="nofollow">https:&#x2F;&#x2F;live-stock-simulator.vercel.app&#x2F;</a>
NPM: <a href="https:&#x2F;&#x2F;www.npmjs.com&#x2F;package&#x2F;kinetic-sql" rel="nofollow">https:&#x2F;&#x2F;www.npmjs.com&#x2F;package&#x2F;kinetic-sql</a>I&#x27;d love to hear your thoughts on the API design. 
(P.S. MSSQL support is coming soon!)

Show HN: Kinetic SQL – A lightweight, real-time SQL Engine for Node.js

LeetCode wasn&#x27;t actually preparing me or anyone else for the pressure of a real technical interview.Most platforms just give you a text box and a compiler. I wanted something that actually simulates the back-and-forth of an interviewer pushing you on time complexity, asking follow-up questions, and pointing out edge cases you missed.&gt; The Stack:
I built the backend with nestjs, prisma, postgresql, Webrtc for real time back and forth conv and [socket.io](<a href="http:&#x2F;&#x2F;socket.io" rel="nofollow">http:&#x2F;&#x2F;socket.io</a>) events in panel like code run etc…. claude-haiku-4-5 for conv and anthropic.claude-sonnet-4-6 for interview scoring.&gt; Where it still falls short:
It’s not perfect. Sometimes the AI gets overly pedantic about syntax instead of focusing on the core algorithmic logic. I’m still tuning the prompts to make it behave more like a senior engineer and less like a strict compiler.I&#x27;m currently trying to stress-test the system. I’d love for you to try breaking the AI interviewer or tell me why this approach is flawed. Happy to answer any questions about the stack or the prompt engineering.

Show HN: I built an AI-powered technical interview prep tool

Hey HN,In 2024 my son was born, and during the long nights of frequent wake-ups, I started (and never finished...) building an Electron app. I very quickly found that the boilerplate required to wire up the main and renderer processes to be very cumbersome, and I&#x27;m sure like many others, started to build abstractions around it to make life easier.Having been heavily indoctrinated in the NestJS ecosystem through my workplace, I started to grow fond of DI, decorators, and the declarative style of working.My first attempt at abstraction was fairly mediocre, but I recently decided to have a second crack. I leaned more heavily into decorators so that I could give the library a clean syntax that was simple to use. I then packaged it up so that others can use it too.Electron IPC Bridge allows you to decorate your classes in the main process, and automatically configures the contracts in the preload. The accompanying vite plugin generates types from those contracts and ensures type-safety in the renderer. Change your contracts? The types update too. Easy!Before:<pre><code> &#x2F;&#x2F; Main
 ipcMain.handle(&quot;users.get_profile&quot;, async (_event, userId: string) =&gt; {
 return userService.getProfile(userId);
 });

 &#x2F;&#x2F; Preload
 &#x2F;&#x2F; Easy to make a mistake with the channel, or forget to register 
 contextBridge.exposeInMainWorld(&quot;api&quot;, {
 getProfile: (id: string) =&gt; ipcRenderer.invoke(&quot;users.get_profile&quot;, id),
 });

 &#x2F;&#x2F; Renderer 
 &#x2F;&#x2F; No type-safety 
 const profile = await window.api.getProfile(userId); 

</code></pre>
After:<pre><code> &#x2F;&#x2F; Main
 @IpcController()
 class UsersController {
 @IpcHandle()
 async getProfile(userId: string) {
 return userService.getProfile(userId);
 }
 }

 &#x2F;&#x2F; Preload
 setupPreload();

 &#x2F;&#x2F; Renderer
 &#x2F;&#x2F; 100% Type-safe, auto-generated contracts with IDE autocomplete
 const profile = await window.api.users.getProfile(userId);
</code></pre>
I&#x27;ve also tried to supply a few different DI library examples too to help people get started. I took my original unfinished app and managed to migrate it fairly painlessly! It&#x27;s also using Nest now instead of typedi.AI Disclosure:Core: About ~90% handwritten with some assistance and refactoring in placesVite plugin: Around 50&#x2F;50, leaning towards AI leading where my experience with Vite is lackingDocs: Mostly written by me, but AI planned site structure, and reviewed and edited what I wrote. It also wrote the troubleshooting page and generated some diagrams for me.This post was all me!

Show HN: Electron IPC Bridge- Auto-generated type-safety without the boilerplate

Hi HN,I built Locus, an open-source project management platform designed for engineering teams that want to use AI coding agents.The core idea: plan sprints and manage tasks in a cloud dashboard, but all code execution happens locally on your infrastructure. Your source code never leaves your machine.How it works:- locus plan: AI generates a sprint plan by analyzing your codebase. It uses multi-agent roles to break down directives into structured tasks with complexity estimates and risk assessments. You can reject and iterate on plans before approving.- locus run: An agent picks up tasks from the sprint, executes them sequentially on a single branch, auto-commits after each task, and opens a PR when the sprint is done. Supports both Claude and Codex as backends.- locus review: Review that understands your full codebase, not just diffs. Detects bugs, security issues, and performance problems. Posts review comments directly to GitHub PRs.- locus discuss: Have architectural discussions with AI that has full project context. Insights and decisions are automatically extracted and saved.- Telegram bot: Manage your agent remotely from your phone.- VSCode extension: Chat with AI in your editor with full repo context.The whole system is free, self-hostable, and works with your existing GitHub workflow. There&#x27;s a one-command installation script for Ubuntu&#x2F;Debian&#x2F;macOS.Tech stack: TypeScript monorepo with NestJS API, Next.js dashboard, and a Bun-bundled CLI.I&#x27;m a solo developer building this because I was frustrated with the disconnect between planning tools and actual code execution.Would love feedback on the approach and any features you&#x27;d want to see.

Show HN: Locus – AI agents that ship your code

Transcriptum is an audio and video transcription service powered by WhisperX: speaker diarization, word-level timestamps, 50+ languages, and optional AI analysis (summaries, Q&amp;A, topics, sentiment, action items, fact-checking) via multiple LLM providers (OpenAI, Gemini, DeepSeek).You can upload files or paste a YouTube URL; we download and transcribe. Export as TXT, SRT, VTT, DOCX. Built with NestJS, Next.js, Prisma&#x2F;PostgreSQL; subscriptions are handled with Polar.I built this to have accurate, private transcription without locking into a single vendor, and to combine transcription with analysis in one place. Would love feedback from anyone who transcribes meetings, podcasts, or long-form content.

Show HN: Transcriptum – fast video transcription with speaker labels and summary

Hey HN,I built ToMusic, an iOS app that turns text descriptions into full songs (lyrics, vocals, and instrumentals) in seconds.How it works: You describe what kind of song you want (genre, mood, tempo, vocal style) or paste your own lyrics, and the app generates a complete, original song. It also works for pure instrumentals like background music, beats, and soundtracks.It supports 150+ genres (Pop, Jazz, EDM, Classical, Hip Hop, Metal...), 30+ moods, and 5 different AI models each with different strengths: longer tracks up to 8 minutes, better song structure, faster generation, etc.Tech stack: Native iOS built with Swift&#x2F;SwiftUI. Backend runs on NestJS with multiple AI music generation models, behind NGINX as a reverse proxy handling SSL via Let&#x27;s Encrypt. Built-in player with synchronized lyrics and audio visualizations. Streaming playback so you don&#x27;t have to wait for the full track to finish generating.I built this for content creators who need custom music for videos, musicians looking for quick inspiration, and honestly anyone who&#x27;s ever had a melody in their head but couldn&#x27;t produce it. No musical training needed.Would love to hear your feedback. Happy to answer questions about the AI models, the generation pipeline, or the iOS development side.

Show HN: ToMusic – Turn text prompts into original songs with AI (iOS)

Hey HN,I&#x27;m a solo dev and I built Invocrea because I was tired of spending hours every month on invoicing. Most tools out there are bloated, expensive, or just ugly.<pre><code> Invocrea lets you create and send professional invoices in under 30 seconds. The stack is Next.js + NestJS + MongoDB.

 The feature I&#x27;m most excited about: AI-generated invoice templates. You describe the style you want, and it generates a custom template for you. No more generic-looking invoices.

 What it does:
 - Create invoices&#x2F;quotes with smart auto-completion
 - Track payments (paid, pending, overdue) in real-time
 - Automatic reminders for unpaid invoices
 - Professional PDF export with your branding
 - AI-powered template generation
 - Client management with full billing history

 It&#x27;s free to start. If you want to try a paid plan, use code AVSE78 for 30% off.

 Would love your feedback on the product and the AI template generation. What would you improve?</code></pre>

Show HN: I built an invoicing SaaS with AI-generated invoice templates


  [![Backers on Open Collective](https://opencollective.com/nest/backers/badge.svg)](https://opencollective.com/nest#backer)
  [![Sponsors on Open Collective](https://opencollective.com/nest/sponsors/badge.svg)](https://opencollective.com/nest#sponsor)

## Description

Nest is a framework for building efficient, scalable [Node.js](http://nodejs.org) server-side applications. It uses modern JavaScript, is built with  [TypeScript](http://www.typescriptlang.org) preserves compatibility with pure JavaScript and combines elements of OOP (Object Oriented Programming), FP (Functional Programming), and FRP (Functional Reactive Programming).

Under the hood, Nest makes use of [Express](https://expressjs.com/), but also, provides compatibility with a wide range of other libraries, like e.g. [Fastify](https://github.com/fastify/fastify), allowing for easy use of the myriad third-party plugins which are available.

## Installation

```js
$ npm install
```

## Getting Started

Setting up a new project is quite simple. With npm installed, you can create a new Nest project with the following commands in your OS terminal:

```js
$ npm i -g @nestjs/cli
$ nest new project-name
```

## Running the app

```js
# development
$ npm run start

# watch mode
$ npm run start:dev

# production mode
$ npm run start:prod
```

## Test

```js
# unit tests
$ npm run test

# e2e tests
$ npm run test:e2e

# test coverage
$ npm run test:cov
```

## Support

Nest is an MIT-licensed open source project. It can grow thanks to the sponsors and support by the amazing backers. If you'd like to join them, please [read more here](https://opencollective.com/nest).

## Stay in touch

- Website - [https://nestjs.com](https://nestjs.com/)
- Twitter - [@nestframework](https://twitter.com/nestframework)

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