February 2026 monthly summary for vLLM-Ascend integration focused on delivering Key-Value (KV) event handling and aggregation within the Ascend connector. The work enhances event publishing reliability across multiple workers and integrates KV events into the scheduler without altering user-facing behavior. This lays groundwork for observable, KV-driven analytics and smoother orchestration within the vLLM framework.

December 2025: Delivered Python bindings for replica descriptor retrieval in Mooncake, enabling get_replica_desc and batch_get_replica_desc access from Python. This work included binding implementation, API documentation improvements, and naming corrections to improve developer usability and consistency. The changes enhance automation capabilities by allowing developers to programmatically retrieve replica descriptors for specified keys, aligning with our store's goal of a more accessible and scriptable API surface.

Month 2025-11 – Mooncake (kvcache-ai/Mooncake): Implemented improved storage usage monitoring, clarified memory metrics, and strengthened documentation and CI stability. Delivered a secondary storage usage monitor to track allocated file size and total file capacity, enabling more accurate capacity planning and alerting. Refactored memory metrics for clarity and maintainability, including adopting int64_t definitions for file capacity and switching to an RAII approach to update allocated_file_size. Fixed several bugs to ensure robust functionality and prepared the codebase for smoother shipping. Updated docs to reflect new metrics and usage guidance. Overall impact: improved observability, reliability, and developer productivity; reduced risk of storage overages; easier onboarding for future contributors. Technologies/skills demonstrated: C/C++, metrics instrumentation, explicit int64_t usage, RAII patterns, code refactoring, documentation, and CI improvements.