elasticsearch-expert
Expert-level Elasticsearch, search, ELK stack, and full-text search
Expert-level Elasticsearch, search, ELK stack, and full-text search
Expert-level Redis for caching, pub/sub, data structures, and high-performance applications
SedonaDB spatial engine enabling GeoACSets.jl categorical geospatial operations with O(log n) indexing
Implement production-grade caching with cache keys/TTLs/consistency classes per query, SWR (stale-while-revalidate), explicit invalidation, HTTP cache headers, and comprehensive testing for stale reads and cache warmup. Use when adding caching to queries, implementing cache invalidation, configuring HTTP caching, or ensuring cache consistency and performance.
bmorphism's GitHub stars (2155 repos) and created repos - a curated index
Complete knowledge domain for Cloudflare Vectorize - globally distributed vector database for building semantic search, RAG (Retrieval Augmented Generation), and AI-powered applications. Use when: creating vector indexes, inserting embeddings, querying vectors, implementing semantic search, building RAG systems, configuring metadata filtering, working with Workers AI embeddings, integrating with OpenAI embeddings, or encountering metadata index timing errors, dimension mismatches, filter syntax issues, or insert vs upsert confusion. Keywords: vectorize, vector database, vector index, vector search, similarity search, semantic search, nearest neighbor, knn search, ann search, RAG, retrieval augmented generation, chat with data, document search, semantic Q&A, context retrieval, bge-base, @cf/baai/bge-base-en-v1.5, text-embedding-3-small, text-embedding-3-large, Workers AI embeddings, openai embeddings, insert vectors, upsert vectors, query vectors, delete vectors, metadata filtering, namespace filtering, topK
Implement or debug Redis caching strategies using the centralized Upstash Redis client. Use when adding cache layers, debugging cache issues, or optimizing cache invalidation.
Data persistence for CFN Loop - SQLite storage, Redis coordination, automatic memory persistence
Use when working with caching in any Elixir project that uses the elixir_cache library. TRIGGER on any of these scenarios: (1) Adding, modifying, or debugging any cache module (`use Cache`, `_cache` suffix modules, adapter selection); (2) Choosing between adapters (ETS vs Redis vs ConCache vs PersistentTerm vs Counter vs DETS vs Agent); (3) Redis operations — hash_get/hash_set/hash_scan, json_get/json_set, sadd/smembers, scan, command, pipeline, connection pools; (4) ETS operations — update_counter, match_pattern, tab2file, rehydration, read_concurrency; (5) Strategy adapters — MultiLayer (L1/L2 caching), HashRing (distributed/consistent hashing), RefreshAhead (proactive refresh); (6) Testing caches — Cache.CaseTemplate, SandboxRegistry, sandbox?, async test isolation, cache mocking; (7) Cache patterns — get_or_create, cache invalidation, cache warming, TTL management, compression_level; (8) Infrastructure — supervision tree setup with {Cache, [modules]}, runtime config, Poolboy pools; (9) Performance — thund
Caching patterns for the elixir_cache project. TRIGGER when: writing or modifying caching code involving Redis, ETS, elixir_cache, Cachex, or any of the _cache apps. Also trigger when working with RedisLock, Cache.Redis, Cache.ETS, or cache sandbox testing. DO NOT TRIGGER when: working with code that doesn't involve caching layers.
Redis best practices for caching, data structures, and in-memory data architecture
Create repository adapter with MongoDB schema following the ports & adapters pattern. Use when adding persistence for domain entities.
Speed up Magento by managing indexers correctly, configuring Varnish full-page cache, and using Redis for session and object caching
Qdrant vector database: collections, points, payload filtering, indexing, quantization, snapshots, and Docker/Kubernetes deployment. Use when managing Qdrant collections, performing vector searches with payload filters, configuring HNSW indexes or quantization, or deploying Qdrant clusters. Keywords: Qdrant, vector database, HNSW, quantization, semantic search.
Implement efficient caching strategies using Redis, Memcached, CDN, and cache invalidation patterns. Use when optimizing application performance, reducing database load, or improving response times.
World-class caching strategies - cache invalidation, Redis patterns, CDN caching, and the battle scars from cache bugs that served stale data for hoursUse when "cache, caching, redis, memcached, cdn, ttl, invalidation, stale, cache aside, write through, cache stampede, thundering herd, cache warming, etag, cache-control, caching, redis, memcached, cdn, performance, http-cache, ttl, invalidation" mentioned.
Manage redis cache manager operations. Auto-activating skill for Backend Development. Triggers on: redis cache manager, redis cache manager Part of the Backend Development skill category. Use when working with redis cache manager functionality. Trigger with phrases like "redis cache manager", "redis manager", "redis".
Create and compare multiple RediSearch index configurations to find the best one