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Kernel-wide Insight

Leveraging BPF to deliver full-stack observability and deep performance insights into memory, scheduling, networking, and block I/O, with 1% overhead.

Instant Observability

Event-driven context snapshot with instrumentation across kernel slow paths. Automatic reports for system-wide events, including scheduling, networking, and interrupts.

AutoTracing

Pinpoint performance degradation in cloud-native environments with tracing-based intelligence. Automated tracing for CPU idle drops, I/O latency, and Loadavg spikes.

Continuous Profiling

Continuous profiling of OS kernel and multi-language (e.g. Java, Python, Go, C/C++.) applications across CPU, memory, I/O, and Lock. Driving business innovation.

Heterogeneous Hardware

Encompassing core system components such as CPUs, memory, PCIe interconnects, network adapters, and storage, alongside specialized AI accelerators including GPUs and NPUs.

Ecosystem Integration

Integrate open‑source observability stacks. Support bare‑metal and cloud‑native deployments. Aware of K8s containers / labels / annotations. Support mainstream Linux distributions.

Best Practice

Blog

Tracing Interrupt Spikes with irqtracing

2026-10-10 ,

Detect CPU interrupt spikes and trace softirq sources and execution contexts with a dual-view flame …

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Profiling Go Heap Memory from Outside the Process

2026-10-09

Read Go runtime heap samples from outside the process to attribute memory use to allocation stacks.

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Capturing Memory Evidence Before OOM

2026-09-24

Investigate memory growth across runtimes with out-of-process snapshots of allocation stacks and …

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Investigating TCP Retransmissions with tcpshark

2026-09-11 ,

Analyze TCP retransmissions with eBPF tracing and kernel packet drop correlation.

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Ecosystem

Huatuo Ecosystem

Users

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Contributors

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