5 Proven API Performance Hacks for High‑Concurrency Systems
This article presents five practical API performance optimization techniques for high‑concurrency environments, covering pagination with cursor queries, asynchronous logging, multi‑level caching, data compression, and connection‑pool tuning, along with key configuration tips and a golden rule to monitor before optimizing.
1️⃣ Pagination Optimization
Scenario: querying millions of records. Techniques: use cursor pagination instead of OFFSET, default 20 items per page, toggle totalCount.
2️⃣ Asynchronous Logging
Replace synchronous disk writes with buffering logs in memory and batch flushing, achieving a 3‑5× performance boost.
3️⃣ Multi‑Level Caching
First layer: local cache (Guava/Caffeine). Second layer: distributed cache (Redis). Key configurations: set appropriate TTL and protect against cache penetration.
4️⃣ Data Compression
Compress requests with gzip/deflate, enable HTTP/2, use MessagePack for large JSON, reducing payload size by over 60%.
5️⃣ Connection Pool Tuning
Key parameters: maxWaitMillis for timeout control, maxActive for maximum connections. Monitor active connections and waiting threads.
Golden rule: monitor before optimizing; APM tools are essential.
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