Opentelemetry integrator
Skill a5c-ai/babysitter/library/specializations/sdk-platform-development/skills/opentelemetry-integrator
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Integrate OpenTelemetry tracing and metrics into SDKs
SKILL.md
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OpenTelemetry Integrator Skill
Overview
This skill integrates OpenTelemetry observability into SDKs, providing distributed tracing, metrics collection, and context propagation for comprehensive API monitoring.
Capabilities
- Add tracing spans to SDK operations
- Export metrics (latency, errors, throughput)
- Configure context propagation (W3C Trace Context)
- Support multiple exporters (OTLP, Jaeger, Zipkin)
- Implement custom span attributes
- Configure sampling strategies
- Add semantic conventions for SDK operations
- Support baggage propagation
Target Processes
- Observability Integration
- Telemetry and Analytics Integration
- Logging and Diagnostics
Integration Points
- OpenTelemetry SDKs (all languages)
- Jaeger for distributed tracing
- Prometheus for metrics
- Grafana for visualization
- Cloud observability platforms
Input Requirements
- Tracing requirements
- Metrics to collect
- Exporter configurations
- Sampling strategy
- Semantic convention mappings
Output Artifacts
- OpenTelemetry instrumentation
- Custom span definitions
- Metrics collectors
- Exporter configurations
- Propagator setup
- Sampling configuration
Usage Example
skill:
name: opentelemetry-integrator
context:
tracing:
enabled: true
propagator: w3c-trace-context
sampling: parentBased
sampleRate: 0.1
metrics:
enabled: true
exportInterval: 30s
metrics:
- sdk.request.duration
- sdk.request.count
- sdk.error.count
exporters:
traces: otlp
metrics: prometheus
serviceName: "my-sdk"
Best Practices
- Follow OpenTelemetry semantic conventions
- Use appropriate sampling rates
- Propagate context across boundaries
- Include useful span attributes
- Avoid high-cardinality attributes
- Configure exporters for production