opentelemetry

Implement OpenTelemetry instrumentation and OTLP pipelines for Grafana telemetry.

1|Updated May 21, 2026
One-click install
npx skills add https://github.com/1k-off/umbraco-observability-playground --skill opentelemetry-1k-off
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: opentelemetry
Source: https://github.com/1k-off/umbraco-observability-playground/tree/main/.agents/skills/opentelemetry
Command: npx skills add https://github.com/1k-off/umbraco-observability-playground --skill opentelemetry-1k-off

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

OpenTelemetry with a Grafana backend solves the problem of collecting consistent, correlated telemetry (metrics, logs, traces, and profiles) across multiple languages and infrastructure so you can observe real system behavior end to end.

Core Features & Use Cases

  • Instrument applications across languages: Use OTel SDKs and frameworks (Go, Java via agent, Node.js auto-instrumentation, Python distro, .NET SDK, plus optional code-less eBPF via Beyla) to generate telemetry with correct service metadata.
  • Configure OTLP delivery: Point applications at Grafana Cloud OTLP endpoints with Basic Auth, choose transport (gRPC or HTTP/protobuf), and set resource attributes like service.name and deployment.environment.
  • Run and tune a collector pipeline: Use Grafana Alloy or upstream OTel Collector to receive OTLP, enrich/drop attributes, batch for efficiency, and apply head or tail sampling (including keeping errors).
  • Kubernetes-friendly deployment: Support Grafana’s Kubernetes Monitoring Helm chart and OpenTelemetry Operator Instrumentation CRs for automated injection.

Quick Start

Configure your app to export OTLP to your Grafana endpoint using OTEL_EXPORTER_OTLP_ENDPOINT, then verify flow by checking traces arriving in Grafana Cloud after a request.

Frequently Asked Questions about opentelemetry

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I send OpenTelemetry traces and metrics to Grafana Cloud?

To send OpenTelemetry traces and metrics to Grafana Cloud, configure your application's OTLP exporter endpoint and use Basic Auth headers for authentication. You can choose between gRPC or HTTP/protobuf transport and set standard resource attributes like service.name before verifying data arrival in Grafana.

What is the best way to instrument a multi-language application for distributed tracing?

The best way to instrument applications for distributed tracing is using OpenTelemetry SDKs across Go, Java, Node.js, Python, and .NET. You can also use code-less eBPF instrumentation via Beyla to automatically generate telemetry with correct service metadata without modifying code.

Does Kubernetes Monitoring support automated OpenTelemetry instrumentation injection?

Yes, Kubernetes Monitoring supports automated OpenTelemetry instrumentation injection. You can use Grafana's Kubernetes Monitoring Helm chart and OpenTelemetry Operator Instrumentation Custom Resources to automatically inject and configure OTel SDKs into your cluster workloads.

Why do I need to standardize resource attributes in my OTLP telemetry pipeline?

You need to standardize resource attributes in your OTLP telemetry pipeline to ensure consistent, correlated telemetry across multiple languages and infrastructure. Setting attributes like deployment.environment allows you to observe real system behavior end-to-end and filter traces effectively in Grafana.

Can I use tail sampling strategies to drop healthy traces and keep errors in OpenTelemetry?

Yes, you can use tail sampling strategies in OpenTelemetry to drop healthy traces and keep errors. By running a collector pipeline with Grafana Alloy or the OTel Collector, you can apply sampling processors that evaluate trace data post-completion to retain only error traces.