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.

Distributed Tracing

Network-centric, service‑oriented request tracing across distributed systems. Delivers end‑to‑end visibility of microservice, ensuring system stability in large‑scale environments.

Ecosystem Integration

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

Practice

Blog

RDMA: Memory Window

By HAO022 on 2026-04-09

Analyzing Memory Window user-space, kernel, and underlying hardware implementation, design …

Read more

RDMA: Queue Pairs

By HAO022 on 2026-04-08

Analyzing Queue Pairs user-space, kernel, and underlying hardware implementation, design …

Read more

RDMA: Memory Region

By HAO022 on 2026-04-07

Analyzing Memory Region user-space, kernel, and underlying hardware implementation, design …

Read more

Linux Kernel RAS

By 王洪磊 on 2026-03-26

The hardware error detection in the kernel, including RAS, MCE, AER, and others.

Read more

Users