What question did this study set out to answer?

To develop an autonomous AIOps platform that transitions IT infrastructure from reactive to proactive management.

May 7, 20260 citationsOpen Access

IntelliOps: An Agentic AIOps Platform for Autonomous IT Infrastructure Monitoring, Predictive Failure Detection, and Self-Healing

APA. S. Patil PSPratyush Sawle PSPratik Salunke

Key Points

To develop an autonomous AIOps platform that transitions IT infrastructure from reactive to proactive management.
Utilized a 7-layer architecture for monitoring and predictive analytics.
Integrated AI technologies such as Gemini 1.5 Flash, LangChain, and LangGraph.
Implemented a continuous loop for system observation and self-healing.
Achieved predictive failure detection up to 15 minutes in advance using LSTM neural networks.
Enabled self-healing to resolve root causes in seconds.
Reduced operational costs by automating routine IT support tasks.

Abstract

IntelliOps is an autonomous, Agentic AI-powered IT Operations platform designed to transition enterprise infrastructure from reactive troubleshooting to proactive self-healing through a sophisticated 7-layer architecture. By integrating Gemini 1.5 Flash with LangChain and LangGraph, the system executes a continuous "Retrieve-Reason-Act-Observe-Reflect" loop that monitors system telemetry via psutil, predicts potential crashes up to 15 minutes in advance using LSTM neural networks, and resolves root causes in seconds. The platform features a proprietary 3-stage learning mechanism that stores incident data in a ChromaDB vector database, allowing it to build "institutional memory" and autonomously promote intervention rules once they meet a 75% user approval threshold. Developed with a PyQt6-based interface, IntelliOps provides real-time monitoring and a collaborative AI assistant to reduce server downtime and operational costs by automating routine IT support tasks

Perguntar à IA

Bookmark

View Full Paper