AGENT SKILL

nestjs-performance

Fastify adapter, Scope management, and Compression. Use when optimizing NestJS performance with Fastify, request-scoped providers, or compression. (triggers: main.ts, FastifyAdapter, compression, SINGLETON, REQUEST scope)

License 许可
MIT
最近更新
2026-06-24
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★ 67
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24

01 前言 Front Matter

name
nestjs-performance
description
Fastify adapter, Scope management, and Compression. Use when optimizing NestJS performance with Fastify, request-scoped providers, or compression. (triggers: main.ts, FastifyAdapter, compression, SINGLETON, REQUEST scope)

02 资源文件 3

03 SKILL.md 正文

Performance Tuning

Priority: P1 (OPERATIONAL)

High-performance patterns and optimization techniques for NestJS applications.

  • Adapter: Use FastifyAdapter instead of Express (2x throughput).

  • Compression: Enable Gzip/Brotli compression.

    // main.ts
    app.use(compression());
    
  • Keep-Alive: Configure http.Agent keep-alive settings to reuse TCP connections for upstream services.

Scope & Dependency Injection

  • Default Scope: Adhere to SINGLETON scope (default).
  • Request Scope: AVOID REQUEST scope unless absolutely necessary.
    • Pro Tip: A single request-scoped service makes its entire injection chain request-scoped.
    • Solution: Use Durable Providers (durable: true) for multi-tenancy.
  • Lazy Loading: Use LazyModuleLoader for heavyweight modules (e.g., Admin panels).

Caching Strategy

  • Application Cache: Use @nestjs/cache-manager for computation results.
    • Deep Dive: See Caching & Redis for L1/L2 strategies and Invalidation patterns.
  • HTTP Cache: Set Cache-Control headers for client-side caching (CDN/Browser).
  • Distributed: In microservices, use Redis store, not memory store.

Queues & Async Processing

  • Offloading: Never block the HTTP request for long-running tasks (Emails, Reports, webhooks).
  • Tool: Use @nestjs/bull (BullMQ) or RabbitMQ (@nestjs/microservices).
    • Pattern: Producer (Controller) -> Queue -> Consumer (Processor).

Serialization

  • Warning: class-transformer is CPU expensive.
  • Optimization: For high-throughput READ endpoints, consider manual mapping or using fast-json-stringify (built-in fastify serialization) instead of interceptors.

Database Tuning

  • Projections: Always use select: [] to fetch only needed columns.
  • N+1: Prevent N+1 queries by using relations carefully or DataLoader for Graph/Field resolvers.
  • Connection Pooling: Configure pool size (e.g., pool: { min: 2, max: 10 }) in config to match DB limits.

Profiling & Scaling

  • API Overhead vs DB Execution: Use an "Execution Bucket" strategy to continuously benchmark Total Duration, DB Execution Time, and API Overhead.
    • Total Baseline: Excellent (< 50ms), Acceptable (< 200ms), Poor (> 500ms). Exception: Authentication routes (e.g. bcrypt/argon2) should take 300-500ms intentionally.
    • DB Execution Baseline: Excellent (< 5ms), Acceptable (< 30ms), Poor (> 100ms - implies missing index or N+1 problem).
    • API Overhead Baseline: Excellent (< 20ms), Poor (> 100ms - implies heavy synchronous processing or serialization blocking Node's event loop).
  • Offloading: Move CPU-heavy tasks (Image processing, Crypto) to worker_threads.
  • Clustering: For non-containerized environments, use ClusterModule to utilize all CPU cores. In K8s, prefer ReplicaSets.

Anti-Patterns

  • No REQUEST scope without evaluation: One REQUEST-scoped provider makes the entire chain request-scoped.
  • No CPU tasks in HTTP handler: Offload image/crypto work to worker_threads or BullMQ.
  • No unprojected queries: Always select: [] the needed columns to avoid serializing unused data.

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