ccfos/huatuo

What it solves

HUATUO addresses the difficulty of troubleshooting performance issues and system failures in complex cloud-native and AI-heavy infrastructure. It provides deep, kernel-level visibility into how hardware and operating systems behave, helping engineers identify the root causes of performance jitter, CPU spikes, and I/O bottlenecks that are often invisible to standard application-level monitoring.

How it works

The project uses eBPF (extended Berkeley Packet Filter) to perform non-intrusive, low-overhead monitoring directly within the Linux kernel. It hooks into kernel subsystems like memory management, CPU scheduling, and networking to capture runtime context automatically. When performance events (like page faults or scheduling delays) occur, it triggers snapshots to record the system state, which can then be analyzed through integrated dashboards like Prometheus and Grafana.

Who it’s for

It is designed for site reliability engineers (SREs), system administrators, and infrastructure engineers managing large-scale cloud-native environments, AI computing clusters, and bare-metal servers who need granular, hardware-aware observability.

Highlights

• Kernel-wide observability for CPU, memory, I/O, and specialized AI hardware (GPUs/NPUs) with less than 1% performance overhead.
• Event-driven AutoTracing that captures system state during performance spikes or jitter.
• Continuous profiling of OS and application performance, including locks and resource usage.
• Zero-instrumentation deployment, meaning it does not require modifying application code to collect deep system insights.
• Seamless integration with standard observability stacks like Prometheus, Grafana, and Elasticsearch.