Nestjs caching queues

Skill dkmqflx/claude-tools/.claude/skills/nestjs-caching-queues

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npx -y skills add dkmqflx/claude-tools --skill nestjs-caching-queues

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NestJS caching and background-job queue best practices. Use when adding caching or async job processing to NestJS — CacheModule, cache-manager, Redis, or BullMQ/Bull queues. Triggers on CacheModule, @InjectQueue, @Processor, cache TTL, or background jobs.

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SKILL.md

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NestJS Caching & Queues

Best practices for two related NestJS performance techniques: caching (@nestjs/cache-manager, backed by Keyv/Redis) and background-job queues (@nestjs/bullmq, backed by Redis). Caching avoids recomputing or re-fetching hot data; queues move slow or unreliable work off the request path so HTTP responses stay fast. Both are Redis-backed in production and share the same core concern: predictable behavior under load and failure.

Verified against the NestJS v10/v11 docs (techniques/caching, techniques/queues). Note the units gotcha: cache TTLs are in milliseconds since @nestjs/cache-manager v2 / cache-manager v5+.

When to Apply

Reference these rules when:

Registering CacheModule or injecting CACHE_MANAGER / using CacheInterceptor
Choosing a cache store (in-memory dev vs. Redis prod via @keyv/redis)
Setting or debugging cache TTLs and cache invalidation
Deciding whether work belongs inline or in a queue (email, image/video processing, external API calls)
Wiring BullModule, @InjectQueue, or a @Processor consumer
Configuring retries/backoff, or scaling workers as a separate deployment

Rules

Rule	Impact	Topic
`cache-module-setup`	HIGH	Register `CacheModule` globally; in-memory for dev, Redis for prod
`set-sensible-ttl`	HIGH	Always set a TTL (in ms); never leave caches unbounded
`cache-keys-explicit`	HIGH	Deterministic, namespaced keys; invalidate on writes
`offload-heavy-work-to-queues`	CRITICAL	Move slow/external work off the request path into a queue
`idempotent-processors`	CRITICAL	Processors must tolerate retries and duplicate deliveries
`retries-and-backoff`	HIGH	Configure `attempts` + exponential `backoff` for transient failures
`separate-worker-process`	MEDIUM	Run consumers as a separate process/deployment for scaling & isolation

How to Use

Caching first. Start with cache-module-setup, then apply set-sensible-ttl and cache-keys-explicit to every cached value — a cache without a TTL or an invalidation story is a correctness bug, not just a performance one.
Queues for anything slow or flaky. Apply offload-heavy-work-to-queues to decide what to enqueue, then idempotent-processors and retries-and-backoff to make the consumer safe to re-run. These two are CRITICAL: BullMQ retries and at-least-once delivery mean a non-idempotent processor will double-charge, double-send, or corrupt data.
Scale out. Apply separate-worker-process when CPU-bound jobs threaten the event loop or you need to scale producers and consumers independently.

Each rule file shows an Incorrect and Correct example. Prefer BullMQ (@nestjs/bullmq) for new projects; Bull (@nestjs/bull) is in maintenance mode.