| title | OpenTelemetry eBPF Instrumentation | ||||||
|---|---|---|---|---|---|---|---|
| linkTitle | OBI | ||||||
| description | Learn how to use OpenTelemetry eBPF Instrumentation for automatic instrumentation. | ||||||
| weight | 3 | ||||||
| cascade |
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OpenTelemetry libraries provide telemetry collection for popular programming languages and frameworks. However, getting started with distributed tracing can be complex. In some compiled languages like Go or Rust, you must manually add tracepoints to the code.
OpenTelemetry eBPF Instrumentation (OBI) is an auto-instrumentation tool to easily get started with Application Observability. OBI uses eBPF to automatically inspect application executables and the OS networking layer, and capture trace spans related to web transactions and Rate Errors Duration (RED) metrics for Linux HTTP/S and gRPC services. All data capture occurs without any modifications to application code or configuration.
OBI offers the following features:
- Wide language support: Java (JDK 8+), .NET, Go, Python, Ruby, Node.js, C, C++, and Rust
- Lightweight: No code changes required, no libraries to install, no restarts needed
- Efficient instrumentation: Traces and metrics are captured by eBPF probes with minimal overhead
- Distributed tracing: Distributed trace spans are captured and reported to a collector
- Log enrichment: Enrich JSON logs with trace context for correlation
- Kubernetes-native: Provides configuration-free auto-instrumentation for Kubernetes applications
- Visibility into encrypted communications: Capture transactions over TLS/SSL without decryption
- Context propagation: Propagate trace context across services automatically
- Protocol support: HTTP/S, gRPC, gRPC-Web, JSON-RPC, MQTT, Memcached, and more
- Database instrumentation: PostgreSQL (including pgx driver), MySQL, MongoDB, Redis, Couchbase (N1QL/SQL++ and KV protocol)
- GenAI instrumentation: Trace and metrics for OpenAI, Anthropic Claude, Google AI Studio (Gemini), and AWS Bedrock API calls with automatic payload extraction
- Low cardinality metrics: Prometheus-compatible metrics with low cardinality for cost reduction
- Network observability: Capture network flows between services with host-level TCP RTT statistics
- Enhanced service discovery: Improved service name lookup with DNS resolution
- Collector integration: Run OBI as an OpenTelemetry Collector receiver component
OBI v0.8.0 expands protocol coverage, payload extraction, and deployment documentation:
- Generic Go tracing improvements: Added generic Go protocol support, including context propagation for generic requests
- Expanded protocol coverage: Added JSON-RPC support across all languages
- Deeper HTTP payload extraction: Added full HTTP body extraction, with bounded decompression for response bodies
- Broader GenAI coverage: Added Google AI Studio (Gemini) and AWS Bedrock payload extraction, and fixed Vertex AI Gemini support
- Named CIDR labels: Network metrics can now label configured CIDR ranges with human-readable names
- New example scenario: Added an Apache HTTP Server example alongside the existing NGINX walkthroughs
- Support documentation: Added a project support matrix for release artifacts and supported environments
For a complete list of changes and upgrade notes, see the release notes.
If you want to explore the upstream examples, see the NGINX walkthrough and the Apache walkthrough.
The following diagram shows the high-level OBI architecture and where eBPF instrumentation fits into the telemetry pipeline.
OBI supports Linux environments that meet the following requirements:
| Requirement | Supported |
|---|---|
| CPU architecture | amd64, arm64 |
| Linux kernel | 5.8+, or RHEL-family Linux 4.18+ with the required eBPF backports |
| Kernel features | BTF |
| Privileges | Root, or the Linux capabilities required by the enabled OBI features |
OBI publishes the following supported release artifacts:
| Artifact | Supported platforms |
|---|---|
obi binary archive |
Linux amd64, Linux arm64 |
k8s-cache binary archive |
Linux amd64, Linux arm64 |
otel/ebpf-instrument container image |
Linux amd64, Linux arm64 |
otel/ebpf-instrument-k8s-cache container image |
Linux amd64, Linux arm64 |
OBI can be deployed on standalone Linux hosts, in containers, and on Kubernetes when the environment meets the requirements above.
OBI does not support non-Linux operating systems, Linux architectures other than
amd64 and arm64, Linux environments without BTF, or kernel versions earlier
than Linux 5.8 outside the documented RHEL-family 4.18+ exception.
Feature-specific support details are documented in these guides:
- Distributed traces: context propagation support, runtime-specific requirements, and distributed tracing limitations
- Export data: protocol, database, messaging, GenAI, GPU, and Go library instrumentation support
OBI provides application and protocol observability without code changes, but it does not replace language-level instrumentation in every scenario. Use language agents or manual instrumentation when you need custom spans, application-specific attributes, business events, or other in-process telemetry that eBPF-based instrumentation cannot derive automatically.
OBI can automatically capture network and protocol activity, but it cannot always recover application-specific details that are not visible from eBPF observation points.
Some features also have additional caveats or narrower support than the core platform requirements. For details, refer to the feature-specific documentation for distributed traces and exported instrumentation.
For a comprehensive list of capabilities required by OBI, refer to Security, permissions and capabilities.
- Follow the setup documentation to get started with OBI either with Docker or Kubernetes.
- Learn about trace-log correlation to connect traces with application logs and enrich JSON logs with trace context.
- Discover how to run OBI as a Collector receiver for centralized telemetry processing.
- See the troubleshooting guide for help with common issues.