opentelemetry

Configure OpenTelemetry collectors and instrumentation for distributed tracing and metrics.

Updated Apr 15, 2026

Search Tags:#observability #opentelemetry #sampling #distributed tracing #collector #otlp #auto-instrumentation

Ready to run

npx skills add https://github.com/ToanPV90/dotfiles --skill opentelemetry-toanpv90

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: opentelemetry
Source: https://github.com/ToanPV90/dotfiles/tree/main/agents/.agents/skills/opentelemetry
Command: npx skills add https://github.com/ToanPV90/dotfiles --skill opentelemetry-toanpv90

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Instrumentation across services often produces fragmented, vendor-specific telemetry that makes latency, failures, and user-impact hard to understand and troubleshoot.

Core Features & Use Cases

Vendor-neutral observability: Correlate distributed traces, metrics, and logs using consistent OpenTelemetry semantics for multi-service systems.
Collector-based production pipeline: Receive OTLP, transform/normalize data, manage sampling and cardinality, and export to tracing, metrics, and logging backends.
Practical instrumentation paths: Support SDK setup and auto-instrumentation for Python and Node.js, plus Kubernetes operator-based injection for existing workloads.

Quick Start

Install and configure an OpenTelemetry Collector, then instrument your service (SDK or auto-instrumentation) to export traces and metrics to the collector endpoint.

Frequently Asked Questions about opentelemetry

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

FAQPage Schema

How do I set up distributed tracing for microservices using OpenTelemetry?▼

To set up distributed tracing, configure an OpenTelemetry Collector to receive OTLP data, then instrument your microservices using SDKs or auto-instrumentation to export traces and metrics to the collector endpoint.

What is the best way to correlate traces, metrics, and logs across different services?▼

The best way to correlate traces, metrics, and logs is using vendor-neutral OpenTelemetry semantics to apply consistent service metadata tagging across your distributed system for unified observability.

How do I control telemetry data volume and cardinality with an OpenTelemetry Collector?▼

You control telemetry data volume and cardinality by configuring a collector pipeline that applies tail-based sampling and cardinality control before exporting data to your tracing, metrics, and logging backends.

Can I use OpenTelemetry auto-instrumentation for existing Kubernetes workloads?▼

Yes, you can instrument existing Kubernetes workloads by using a Kubernetes operator to automatically inject OpenTelemetry instrumentation, avoiding manual SDK setup for your services.

Does OpenTelemetry support auto-instrumentation for Python and Node.js applications?▼

Yes, OpenTelemetry supports practical auto-instrumentation paths for Python and Node.js applications, allowing you to automatically generate traces and metrics without modifying application code extensively.

Why do I need a vendor-neutral observability pipeline for distributed systems?▼

You need a vendor-neutral observability pipeline to avoid fragmented, vendor-specific telemetry, enabling consistent trace-to-log correlation and unified troubleshooting for latency and failures across microservices.

chambear2809

splunk-observability-k8s-auto-instrumentation-setup

Render and manage Splunk/OpenTelemetry Kubernetes auto-instrumentation overlays for Java, Node.js, Python, .NET, Go, Apache, Nginx, and SDK workloads.

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