Agent skill
NestJS Performance
Fastify adapter, Scope management, and Compression.
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
Metadata
Additional technical details for this skill
- labels
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nestjs performance fastify
- triggers
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{ "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
FastifyAdapterinstead of Express (2x throughput). -
Compression: Enable Gzip/Brotli compression.
typescript// main.ts app.use(compression()); -
Keep-Alive: Configure
http.Agentkeep-alive settings to reuse TCP connections for upstream services.
Scope & Dependency Injection
- Default Scope: Adhere to
SINGLETONscope (default). - Request Scope: AVOID
REQUESTscope 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
LazyModuleLoaderfor heavyweight modules (e.g., Admin panels).
Caching Strategy
- Application Cache: Use
@nestjs/cache-managerfor computation results.- Deep Dive: See Caching & Redis for L1/L2 strategies and Invalidation patterns.
- HTTP Cache: Set
Cache-Controlheaders 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-transformeris 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
relationscarefully orDataLoaderfor 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
ClusterModuleto utilize all CPU cores. In K8s, prefer ReplicaSets.
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