spring-boot-performance

What problem does it solve?

This guide helps developers address performance bottlenecks in Spring Boot applications by outlining best practices and practical patterns for scaling and optimization.

Core Features & Use Cases

• Pagination: Implement efficient data loading for large datasets using pagination and avoid loading entire tables into memory.
• Caching & Projections: Use caching to speed up frequently accessed data and apply projections to fetch only needed fields.
• N+1 Query Elimination: Use joins, fetch strategies, and entity graphs to minimize extra database calls.
• JPA & Hibernate Tuning: Optimize batch sizes, second-level cache, and query hints; configure connection pooling and pool sizing.
• Async & Batch Processing: Offload long-running tasks to separate threads and perform bulk operations efficiently.
• Monitoring & Indexing: Enable query monitoring, compression, and database indexing for common queries.

Quick Start

Apply the performance optimization patterns described here to your Spring Boot project to improve latency and throughput.