---
title: "Keep Hits 12k Stars Unifying 130 Monitoring Tools With AI Alert Correlation"
subtitle: "Keep unifies alerts from 130+ monitoring tools into one dashboard, adds LLM-driven correlation, and automates response with YAML workflows."
url: "https://alphasignal.ai/news/keep-hits-12k-stars-unifying-130-monitoring-tools-with-ai-alert-correlation"
author: "AlphaSignal Newsroom"
author_url: "https://alphasignal.ai/editorial-team"
company: "AlphaSignal"
company_url: "https://alphasignal.ai/company/alphasignal"
published: "2026-04-24T15:49:13.000Z"
updated: "2026-08-22T00:49:52.972Z"
type: "Repo"
topics:
  - "Open Source"
  - "Infra"
subtopics:
  - "Model Serving"
  - "Monitoring"
upvotes: 38
source_url: "https://github.com/keephq/keep"
comments: 0
truncated: true
---

# Keep Hits 12k Stars Unifying 130 Monitoring Tools With AI Alert Correlation

> Keep unifies alerts from 130+ monitoring tools into one dashboard, adds LLM-driven correlation, and automates response with YAML workflows.

Alert fatigue is the quiet productivity killer of every on-call rotation. [Keep](https://github.com/keephq/keep), a Python-based open-source project that recently crossed 12k GitHub stars, tries to fix it by consolidating alerts from every monitoring tool you already run and layering AI-driven correlation and workflow automation on top.

The platform unifies more than 130 monitoring tools into a single pane of glass, aggregating signals from providers like Datadog, Prometheus, Grafana, CloudWatch, New Relic, and PagerDuty so teams stop switching between dashboards to figure out what broke. The architecture centers on three components: a provider system for bidirectional integrations, a correlation engine powered by pluggable LLMs, and a workflow automation system that feels like GitHub Actions for monitoring infrastructure.

![Keep alert management dashboard showing filtered incident feed with severity, status, and source columns](https://github.com/keephq/keep/raw/main/assets/sneaknew.png?raw=true) 

## Cutting through the noise

Most incident tools centralize notifications without recognizing that a dozen alerts describe the same underlying database outage. Keep's approach leans on a rules engine plus LLMs to group related events. A Google CEL-based rules engine evaluates incoming alerts against user-defined correlation rules, automatically bundling related events into high-fidelity incidents. One useful architectural detail: Keep stores alert history indefinitely by default (configurable via retention policies), which enables temporal correlation. In practice, that means recognizing patterns like "this alert always precedes that alert by five minutes" and proactively grouping them, something most incident management tools can't do because they don't retain sufficient history.

_Preview only. Full text requires an AlphaSignal Pro account._

## Sources

- [keephq/keep GitHub repository](https://github.com/keephq/keep)
- [Keep documentation - Introduction](https://docs.keephq.dev/overview/introduction)
- [Keep: Building an Open-Source AIOps Platform That Actually Reduces Alert Fatigue](https://starlog.is/articles/automation/keephq-keep/)
- [Keep: Open-Source AIOps & Alert Management Platform](https://openapps.pro/apps/keep)
- [keep | The Open Source Drop](https://www.opensourcedrop.com/tools/keephq/keep)