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2.2 KiB
name, description, license, metadata
| name | description | license | metadata | ||||
|---|---|---|---|---|---|---|---|
| opentelemetry | Instrument applications and infrastructure with OpenTelemetry for unified traces, metrics, and logs. Use when implementing distributed tracing, service-level troubleshooting, or vendor-neutral observability. | MIT |
|
OpenTelemetry
Adopt vendor-neutral telemetry with consistent instrumentation across services.
When to Use This Skill
Use this skill when:
- Debugging latency across microservices
- Standardizing observability data model and naming
- Sending telemetry to Prometheus, Grafana, Datadog, or OTLP backends
- Building SLO dashboards with trace-to-log correlation
Core Workflow
- Define semantic conventions for services, environments, and versions.
- Add SDK or auto-instrumentation in each service.
- Run an OpenTelemetry Collector to receive, transform, and export telemetry.
- Validate cardinality and sampling to control cost.
- Create golden signals dashboards and alerting from collected data.
Collector Starter Config
# otel-collector.yaml
receivers:
otlp:
protocols:
grpc:
http:
processors:
batch:
memory_limiter:
check_interval: 1s
limit_mib: 512
attributes:
actions:
- key: deployment.environment
value: production
action: upsert
exporters:
debug: {}
otlp:
endpoint: observability-backend:4317
tls:
insecure: true
service:
pipelines:
traces:
receivers: [otlp]
processors: [memory_limiter, batch, attributes]
exporters: [otlp, debug]
metrics:
receivers: [otlp]
processors: [memory_limiter, batch, attributes]
exporters: [otlp]
Best Practices
- Use tail-based sampling for high-volume production traces.
- Tag telemetry with
service.name,service.version, anddeployment.environment. - Drop noisy attributes early in the collector.
- Keep metric label cardinality low for stable query performance.
Related Skills
- prometheus-grafana - Dashboarding and alerting
- datadog - Managed observability backend
- alerting-oncall - On-call routing and escalation