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Signoz Open Source Observability Platform

ASecurity

SigNoz is an open-source observability platform built around OpenTelemetry for logs, metrics, and traces in one place. It is a practical fit when you want Datadog-style visibility with a self-hosted stack, first-party docs, and active upstream maintenance.

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  • Added June 2, 2026
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  • cli

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A100/100

Scanned June 2, 2026

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SKILL.md
---
name: "SigNoz Open-Source Observability Platform"
slug: "signoz-open-source-observability-platform"
description: "SigNoz is an open-source observability platform built around OpenTelemetry for logs, metrics, and traces in one place. It is a practical fit when you want Datadog-style visibility with a self-hosted stack, first-party docs, and active upstream maintenance."
github_stars: 26517
verification: "security_reviewed"
source: "https://github.com/SigNoz/signoz"
author: "SigNoz"
publisher_type: "Company"
category: "Monitoring & Alerts"
framework: "Multi-Framework"
tool_ecosystem:
  github_repo: "SigNoz/signoz"
  github_stars: 26517
---

# SigNoz Open-Source Observability Platform

SigNoz is an open-source observability platform built around OpenTelemetry for logs, metrics, and traces in one place. It is a practical fit when you want Datadog-style visibility with a self-hosted stack, first-party docs, and active upstream maintenance.

## Prerequisites

Docker, OpenTelemetry, ClickHouse

## Installation

Requirements and caveats from upstream:
- Monitor exceptions automatically in Python, Java, Ruby, and Javascript. For other languages, just drop in a few lines of code and start monitoring exceptions.
- ### Deploy using Docker(self-hosted)
- Please follow the steps listed [here](https://signoz.io/docs/install/docker/) to install using docker

Basic usage or getting-started notes:
- Monitor and debug your LLM applications with comprehensive observability. Track LLM calls, analyze token usage, monitor performance, and gain insights into your AI application's behavior in production.
- SigNoz LLM observability helps you understand how your language models are performing, identify issues with prompts and responses, track token usage and costs, and optimize your AI applications for better performance...
- See the detailed stack trace for all exceptions caught in your application. You can also log in custom attributes to add more context to your exceptions. For example, you can add attributes to identify users for which...

- Source: https://github.com/SigNoz/signoz
- Extracted from upstream docs: https://raw.githubusercontent.com/SigNoz/signoz/HEAD/README.md

## Documentation

- https://signoz.io/docs/

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/signoz-open-source-observability-platform/)

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