Agent skill

NestJS Performance

Fastify adapter, Scope management, and Compression.

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Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/performance-hoangnguyen0403-agent-skills-standar-2

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Additional technical details for this skill

labels
nestjs performance fastify
triggers
{
    "files": [
        "main.ts"
    ],
    "keywords": [
        "FastifyAdapter",
        "compression",
        "SINGLETON",
        "REQUEST scope"
    ]
}

SKILL.md

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.

    typescript
    // 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

  • 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.

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