Keephq: Open-Source AIOps Platform
date
Dec 5, 2024
damn
language
en
status
Published
type
Products
image
https://www.ai-damn.com/1733404502537-24120305534387862161.jpg
slug
keephq-open-source-aiops-platform-1733404521038
tags
AIOps
Alert Management
Open Source
IT Operations
summary
Keephq is an open-source AIOps platform designed to streamline alert and event management for IT operations teams. It offers a comprehensive suite of features that enhance operational capabilities through AI technology, making it suitable for a wide range of users from startups to large enterprises. With over 90 integration options, Keephq aims to reduce alert fatigue and improve response times in complex environments.
Product Introduction
Keephq is an open-source AIOps platform that serves as a comprehensive solution for managing large-scale alerts and events. It enhances IT operational capabilities through advanced AI technology, providing users with essential tools to streamline alert management and improve team efficiency. Suitable for various organizations, from startups to major enterprises, Keephq is designed to handle complex environments effectively.
Key Features
- Integration Capabilities: Supports high-quality integration with monitoring systems, IRM ticket systems, source control, and change management tools.
- Single-View Interface: Offers a unified dashboard for alerts using Common Express Language for advanced querying and data analysis.
- AI Technology: Utilizes AI to enhance alert correlation and response efficiency, reducing alert fatigue for IT teams.
- Wide Audience: Designed for SREs, engineers, and operations teams managing large volumes of alerts.
- Free Trial: Provides potential users the opportunity to explore the platform before committing to a paid plan.
Product Data
- Funding: Announced $2.7 million in seed funding in 2024.
- GitHub Followers: Has 7.8k followers, indicating strong community support.
- Monthly Visits: Approximately 5,343 visits with a bounce rate of 49.35%.
- Page per Visit: Users average 3.4 pages per visit with a visit duration of 51 seconds.