May 2026 summary for yhyang201/sglang focused on expanding observability and reliability for caching in hybrid deployments. Delivered System Observability Enhancements: exposed gauge metrics for SWA and Mamba cache usage (available, evictable, and used tokens), enabling visibility, performance tracking, and data-driven capacity planning. Commit: 9fb9a1cca6bf1ec7202b8a7b9a05755e2b6ba707 ([sgl] expose swa and mamba cache metrics (#24396)). No critical bugs fixed this month; effort centered on instrumentation and reliability. Impact includes faster troubleshooting, improved resource planning, and a solid foundation for cache-pressure alerting. Skills demonstrated include observability instrumentation, metrics design, caching strategies, and hybrid deployment considerations.

April 2026 monthly summary focused on delivering high-impact features, stability fixes, and performance optimizations across four sgLang repositories. The work emphasizes business value through increased throughput, reduced memory usage, and more reliable large-scale inference and training workflows.

March 2026 monthly summary: Delivered cross-repo performance optimizations and stability fixes in sgLang projects. Key outcomes include pinned memory enhancements to CPU-GPU data transfers (Tensor operations in yhyang201/sglang and sgl-project/sglang), and robust scheduler handling with fixes for tensor mismatch after pause and improved CUDA graph handling for models without layers. These changes reduce synchronization overhead, improve batch processing throughput, and enhance runtime resilience in model execution pipelines across three repositories.

February 2026 — Consolidated stability enhancements for kvcache-ai/sglang with a focused fix to memory management in SchedulerOutputProcessorMixin. No new features released this month; major effort centered on preventing memory growth and improving reliability in long-running scheduler tasks.