open-telemetry/opentelemetry-ebpf-profiler
Opentelemetry Ebpf Profiler
The OpenTelemetry eBPF profiler is a system-wide performance monitoring agent that captures stack traces and resource usage across kernel and user-space runtimes. By utilizing kernel-level tracing, it provides continuous observability into application behavior without requiring manual code instrumentation or process restarts.
The tool distinguishes itself through its ability to perform mixed-language stack unwinding, which reconstructs call chains across native code and managed virtual machines. It handles environments lacking frame pointers or debug symbols by parsing binary metadata and exception frames to ensure accurate stack reconstruction. To maintain efficiency, the agent employs probabilistic event sampling and asynchronous telemetry transmission, reducing the resource footprint while ensuring reliable data delivery to observability backends.
The profiler supports comprehensive performance analysis by mapping raw memory addresses to human-readable function names and source locations. It integrates into production observability infrastructure by exporting standardized performance signals, enabling consistent monitoring and bottleneck identification across complex, polyglot software environments.
Features
- eBPF Profilers - Captures stack traces across kernel and user-space runtimes using low-overhead eBPF kernel tracing.
- Cross-Environment Unwinders - Reconstructs accurate call chains across native code and managed runtimes to debug complex performance issues in polyglot environments.
- Continuous Profilers - Provides continuous, always-on monitoring of resource usage and call stacks across kernel and application runtimes.
- eBPF-Based Tracing - Captures system-wide execution events and stack traces using kernel-level probes with minimal performance overhead.
- OpenTelemetry Exporters - Transmits performance data and stack traces to observability backends using standardized telemetry formats.
- Native Stack Unwinders - Reconstructs call chains across native and managed code by parsing binary metadata and exception frames to ensure accurate stack traces.
- Memory Symbol Resolution - Translates raw memory addresses into human-readable function names by mapping execution frames against local binary metadata.
- Call Tracing - Recovers sequences of function calls by traversing stack frames across native, interpreted, and dynamically compiled code.
- Runtime Introspection Tools - Interprets runtime-specific metadata to traverse call stacks across native code and managed virtual machines.
- Asynchronous Telemetry - Buffers and transmits performance signals asynchronously to ensure reliable data delivery without blocking the profiled application.
- Kernel Execution Path Tracing - Gains deep visibility into application behavior by capturing system-wide execution data through low-overhead kernel instrumentation.
- Execution Event Sampling - Captures a statistically representative subset of performance events to reduce resource consumption and network bandwidth.
- Monitoring and Observability - Integrates into production infrastructure by exporting standardized performance telemetry for centralized analysis.
- Telemetry Collectors - Transmits collected stack traces, metrics, and host metadata to remote backends using a stateless, push-based protocol.
- Observability Data Exporters - Transmits captured profiling signals to compatible observability platforms using standardized telemetry formats.
- Performance Monitoring Tools - Identifies resource bottlenecks by mapping raw execution frames to human-readable function names across diverse code environments.
- Kernel Stack Trace Capture - Captures stack traces and resource usage across kernel and application runtimes without requiring manual instrumentation.
