Agent Skillsgrafana/skills › opentelemetry

opentelemetry

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指导为各类应用配置 OpenTelemetry,将指标、日志和链路追踪数据发送至 Grafana Cloud 或自托管后端。涵盖自动注入、认证、Alloy 采集及采样策略。

skills/grafana-core/opentelemetry/SKILL.md grafana/skills

Trigger Scenarios

配置 OpenTelemetry SDK 发送遥测数据到 Grafana 调试 spans 未显示问题 设置 OTLP 环境变量

Install

npx skills add grafana/skills --skill opentelemetry -g -y
More Options

Non-standard path

npx skills add https://github.com/grafana/skills/tree/main/skills/grafana-core/opentelemetry -g -y

Use without installing

npx skills use grafana/skills@opentelemetry

指定 Agent (Claude Code)

npx skills add grafana/skills --skill opentelemetry -a claude-code -g -y

安装 repo 全部 skill

npx skills add grafana/skills --all -g -y

预览 repo 内 skill

npx skills add grafana/skills --list

SKILL.md

Frontmatter
{
    "name": "opentelemetry",
    "license": "Apache-2.0",
    "description": "Instrument any app with OpenTelemetry and ship metrics \/ logs \/ traces to Grafana Cloud or self-hosted Mimir \/ Loki \/ Tempo \/ Pyroscope. Covers SDK auto-instrumentation for Go, Java (Grafana JVM agent), Python (`opentelemetry-instrument`), Node.js, .NET (`Grafana.OpenTelemetry`), Beyla eBPF for zero-code; Grafana Cloud OTLP gateway + Basic-auth (instanceID + API key, base64); env-var config (`OTEL_EXPORTER_OTLP_*`, `OTEL_RESOURCE_ATTRIBUTES`); Alloy \/ OTel-Collector pipelines; Kubernetes Operator inject-annotations; and head + tail sampling. Use when instrumenting a service, pointing OTLP at Grafana Cloud, switching from Jaeger \/ Datadog \/ New Relic, choosing head- vs tail-sampling, or debugging \"spans aren't showing in Explore\" — even when the user says \"auto-instrument my Java app\", \"send traces to Grafana\", \"what env vars do I set\", \"OTLP endpoint\", or \"Operator inject\" without naming OpenTelemetry."
}

OpenTelemetry with Grafana

Docs: https://grafana.com/docs/opentelemetry/

Vendor-neutral instrumentation pipeline. Apps speak OTLP → Alloy (or direct) → Grafana Cloud (Mimir / Loki / Tempo / Pyroscope).

Backends

Signal Backend
Metrics Grafana Mimir
Logs Grafana Loki
Traces Grafana Tempo
Profiles Grafana Pyroscope

Prerequisites

  • Grafana Cloud stack OR self-hosted Mimir / Loki / Tempo
  • Cloud OTLP endpoint: https://otlp-gateway-<region>.grafana.net/otlp
  • Basic-auth credentials: numeric instance ID + API token with MetricsPublisher + LogsPublisher + TracesPublisher
  • An app to instrument

Common Workflows

1. Authenticate to the Grafana Cloud OTLP endpoint

# 1. Build the auth header
INSTANCE_ID=123456
API_KEY="glc_eyJ..."
export OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp-gateway-prod-us-east-0.grafana.net/otlp
export OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf
export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Basic $(echo -n "${INSTANCE_ID}:${API_KEY}" | base64)"
export OTEL_RESOURCE_ATTRIBUTES="service.name=myapp,service.namespace=myteam,deployment.environment=prod"

# 2. Smoke-test creds with a curl POST against the OTLP traces endpoint (empty body)
curl -s -o /dev/null -w "%{http_code}\n" \
  -X POST -H "Content-Type: application/x-protobuf" \
  -H "Authorization: Basic $(echo -n "${INSTANCE_ID}:${API_KEY}" | base64)" \
  "$OTEL_EXPORTER_OTLP_ENDPOINT/v1/traces" --data-binary '\n'
# Expect 400 (malformed payload) — NOT 401 (auth) or 404 (wrong endpoint).

2. Auto-instrument a Java app + verify

# 1. Download the Grafana JVM agent (single jar)
curl -sLO https://github.com/grafana/grafana-opentelemetry-java/releases/latest/download/grafana-opentelemetry-java.jar

# 2. Run with the agent + env from step 1
java -javaagent:./grafana-opentelemetry-java.jar -jar myapp.jar

# 3. Generate traffic, then verify in Grafana → Explore → Tempo:
#    TraceQL: { resource.service.name = "myapp" }
#    Expect spans within ~30s. Also verify metrics:
#    PromQL: count by (service_name)({service_name="myapp"})

3. Auto-instrument a Python app

pip install "opentelemetry-distro[otlp]"
opentelemetry-bootstrap -a install

# Same env vars as step 1, then:
opentelemetry-instrument python app.py

# Verify the same way — Explore → Traces filter service.name=myapp.

4. Add Alloy as a buffering / sampling collector

# Application points at local Alloy (gRPC fastest)
export OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
export OTEL_EXPORTER_OTLP_PROTOCOL=grpc

# Alloy environment for forwarding to Cloud
export GRAFANA_CLOUD_OTLP_ENDPOINT=https://otlp-gateway-prod-us-east-0.grafana.net/otlp
export GRAFANA_CLOUD_INSTANCE_ID=$INSTANCE_ID
export GRAFANA_CLOUD_API_KEY=$API_KEY
alloy run /etc/alloy/config.alloy

# Verify Alloy received and forwarded
curl -s http://localhost:12345/metrics | grep otelcol_exporter_sent_spans

Full Alloy config + tail-sampling block + OTel Collector YAML + K8s Operator install: references/collector-config.md.

SDK-by-language details (Go full code, Node manual setup, .NET ASP.NET Core, all the env-var quirks): references/instrumentation.md.

5. Kubernetes — auto-inject via the Operator

apiVersion: opentelemetry.io/v1alpha1
kind: Instrumentation
metadata: { name: my-instrumentation }
spec:
  exporter: { endpoint: http://otelcol:4317 }
  propagators: [tracecontext, baggage]
  java:
    image: us-docker.pkg.dev/grafanalabs-global/docker-grafana-opentelemetry-java-prod/grafana-opentelemetry-java:2.3.0-beta.1
  nodejs: {}
  python: {}

Then annotate pods:

metadata:
  annotations:
    instrumentation.opentelemetry.io/inject-java: "true"
    # or: inject-nodejs, inject-python, inject-dotnet
# Verify the operator injected the agent
kubectl describe pod <pod> | grep -A2 'opentelemetry-auto-instrumentation'
# Then run the same Grafana Explore checks.

Sampling — when to pick which

# Head sampling (cheap, decided at start; may lose rare errors)
export OTEL_TRACES_SAMPLER=parentbased_traceidratio
export OTEL_TRACES_SAMPLER_ARG=0.1   # 10%

Tail sampling (decides after seeing the whole trace — keep errors + sample the rest) requires an Alloy / OTel-Collector tail_sampling processor; full block in references/collector-config.md.

Key environment variables

Variable Example
OTEL_EXPORTER_OTLP_ENDPOINT https://otlp-gateway-prod-us-east-0.grafana.net/otlp
OTEL_EXPORTER_OTLP_PROTOCOL grpc or http/protobuf
OTEL_EXPORTER_OTLP_HEADERS Authorization=Basic <base64>
OTEL_RESOURCE_ATTRIBUTES service.name=app,service.namespace=team,deployment.environment=prod
OTEL_SERVICE_NAME shorthand for service.name
OTEL_TRACES_SAMPLER / _ARG parentbased_traceidratio / 0.1

Troubleshooting

  • 401 from OTLP gateway → instance ID is not numeric, or API key missing publisher roles
  • 404 → endpoint URL wrong (must end with /otlp)
  • Spans missing → check OTEL_EXPORTER_OTLP_PROTOCOL matches transport (Cloud OTLP gateway = http/protobuf, Alloy local = grpc)
  • Node.js auto-instrumentation broken after bundling → bundlers like @vercel/ncc defeat the require hooks
  • Python under Gunicorn / uWSGI shows no spans → reinit OTel providers in a post-fork hook

Resources

Version History

  • b583762 Current 2026-07-06 00:35

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