- DoorDash Feature Store Redis Optimization
How DoorDash benchmarked key-value stores and tuned Redis with hashes, xxHash, protobuf, and Snappy to cut its ML feature store's cost, memory, CPU, and latency.
- 1M RPS Voucher System
Case study of issuing vouchers at 1M req/s by pre-distributing them into pod RAM, with the trade-offs and the comment Q&A on fraud, Redis HA, and history.
- Conclusions And QA
Conclusions, best-practice summary, implementation checklist, and community Q&A on a distributed in-memory cache for heavy-read APIs, covering Redis Pub/Sub sync, race conditions, warm-up, and Redis versus Memcached at scale.
- In Memory Cache Best Practices
Index and summary of a guide to distributed in-memory caching for heavy-read APIs, pointing to the architecture, optimization, and trade-off notes.
- Optimization Techniques
Techniques and lessons learned for tuning a local in-memory cache synchronized by Redis Pub/Sub, covering serialization, native HTTP, ETags, eviction, race conditions, and pod lifecycle.
- Overview And Architecture
Problem context and reference architecture for serving 1M+ requests per second on heavy-read APIs using local in-memory caches synchronized through Redis Pub/Sub.
- Tradeoffs And Comparison
Trade-offs, limitations, comparisons with Redis client-side caching, Memcached, and CDNs, and benchmark numbers for a local in-memory cache fed by Redis Pub/Sub.
- Redis
Guide to Redis, the in-memory data structure store used as a database, cache, and message broker, covering its use cases, data types, persistence, and best practices.
- Top K Problem Heavy Hitters
Compares solutions to the Top K heavy hitters problem at 10 billion views per day (Redis sorted sets, Count-Min Sketch, OLAP pipelines, batch jobs, SQL) and recommends a hybrid fast path plus slow path architecture.