Opentelemetry
Grafana LabsOfficialPublished by Grafana Labs
- Skill
- Tool integration
- Cloud and DevOps
- Apache-2.0
- Low risk
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a comprehensive guide for instrumenting applications using OpenTelemetry (OTel) and configuring them to export metrics, logs, traces, and profiles to Grafana Cloud or self-hosted Grafana backends (Mimir, Loki, Tempo, Pyroscope). It covers various implementation methods, including SDK auto-instrumentation for multiple languages, zero-code instrumentation via Beyla eBPF, and the use of Grafana Alloy or the OTel Collector for pipeline management. The documentation includes authentication procedures, environment variable configurations, Kubernetes operator integration, and troubleshooting common connectivity issues.
What it does
- Configures OTLP exporters to send telemetry to Grafana Cloud or self-hosted backends.
- Provides auto-instrumentation patterns for Java, Python, Go, Node.js, and .NET.
- Demonstrates zero-code instrumentation using Beyla eBPF.
- Explains how to set up Grafana Alloy as a collector for buffering and tail-sampling.
- Details Kubernetes auto-instrumentation using the OTel Operator.
- Offers troubleshooting steps for common OTLP gateway and connectivity errors.
When to use it
- When you need to instrument a service to send telemetry data to Grafana Cloud.
- When migrating from other monitoring tools like Jaeger, Datadog, or New Relic.
- When you need to configure head or tail sampling for trace data.
- When debugging missing spans or connectivity issues between your app and Grafana.
- When setting up automated instrumentation in a Kubernetes environment.
Advantages
- Vendor-neutral instrumentation approach using standard OTLP protocols.
- Supports both manual SDK integration and zero-code instrumentation.
- Provides clear guidance on authentication and environment variable setup.
- Includes robust troubleshooting paths for common configuration pitfalls.
Usage examples
- “How do I auto-instrument my Java application to send traces to Grafana?”
- The agent provides the command to download the Grafana JVM agent and the necessary environment variables to authenticate with the Grafana Cloud OTLP gateway.
- “What environment variables are required to connect to the Grafana Cloud OTLP endpoint?”
- The agent lists the specific variables including OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_EXPORTER_OTLP_PROTOCOL, and the base64-encoded authorization header.
- “How can I use the Kubernetes Operator to instrument my pods?”
- The agent provides the YAML configuration for an Instrumentation resource and the specific annotations required to inject auto-instrumentation into your pods.
- “My spans are not showing up in Grafana Explore, how do I debug this?”
- The agent guides you through verifying your OTLP endpoint URL, checking that the protocol matches the transport, and ensuring your API key has the correct publisher roles.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/grafana/opentelemetry/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip opentelemetry.zip -d .agents/skills
Documentation by Grafana Labs
OpenTelemetry with Grafana
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/otlpBasic-auth credentials: numeric instance ID + API token with
MetricsPublisher+LogsPublisher+TracesPublisherAn 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_spansFull 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_PROTOCOLmatches transport (Cloud OTLP gateway =http/protobuf, Alloy local =grpc)Node.js auto-instrumentation broken after bundling → bundlers like
@vercel/nccdefeat the require hooksPython under Gunicorn / uWSGI shows no spans → reinit OTel providers in a post-fork hook
Resources
Files
- ATTRIBUTION.mdAdded by AutoGineer846 B
- LICENSELicence file added by AutoGineer11.1 KiB
- SKILL.md6.7 KiB
- references/collector-config.md18.1 KiB
- references/instrumentation.md20.6 KiB
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs network access, Needs an API key, Needs a command-line tool, Needs Python
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Attribution and licence
- Published by
- Grafana Labs
- Publisher
- Grafana Labs (Official)
- Source
- grafana/skills · skills/grafana-core/opentelemetry · commit 8fb72a5
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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