Speaker
Description
Joblens, a lightweight and observability collector designed to achieve fine-grained monitoring of cluster jobs. Leveraging eBPF-based kernel instrumentation, Joblens enables dynamic tracking of process creation and system calls with zero overhead and no need for kernel modifications. Its modular and highly configurable plugin system, built on an asynchronous double-buffer pipeline, exports metrics to multiple backends such as Elasticsearch and Prometheus while maintaining less than 5% CPU overhead. Additionally, Joblens incorporates a Lua script rule engine that dynamically registers monitoring policies, allowing automatic detection and tracking of specific jobs. Integrated into the Interacitve aNalysis worKbench(INK), Joblens provides users with real-time web-based monitoring of job execution status, significantly enhancing cluster observability and debuggability.
| Desired slot length | 20 |
|---|---|
| Speaker release | Yes |