Optimizing Backend API Performance
summary
Describes concrete fixes: use HikariCP connection pooling to cut connect/close overhead, add @Cacheable for method results to eliminate repeated DB hits, switch logging to asynchronous (Logback/Log4j async appenders) to remove I/O blocking, and apply payload compression like gzip/brotli while balancing CPU cost. Explains pagination choices (offset vs cursor) with cursor preferred for large datasets, recommends monitoring with Prometheus and Grafana, and shows these measures measurably lower latency and DB load.
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chapters (10)
- 0:00Introduction and Speaker Background
- 1:26Importance of API Performance
- 2:57Common API Performance Bottlenecks
- 5:18Solutions for API Performance Issues
- 5:43Pagination Techniques
- 7:17Asynchronous Logging
- 8:09Caching Strategies
- 9:23Payload Compression
- 10:53Connection Pooling
- 12:08Key Takeaways and Conclusion
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