On-Premise AIOps Infrastructure for a Software Editor SME: An Experience Report

TL;DR

This paper presents an on-premise AIOps infrastructure built with open-source tools for a software SME, demonstrating its feasibility and providing insights into its design and implementation.

Contribution

It introduces a comprehensive, open-source-based AIOps infrastructure tailored for SMEs, including design rationale and integration strategies, filling a gap in private, cost-effective AIOps solutions.

Findings

Successful deployment of on-premise AIOps in a real company

Guidelines for selecting data management systems

Insights into integrating open-source AIOps components

Abstract

Information Technology has become a critical component in various industries, leading to an increased focus on software maintenance and monitoring. With the complexities of modern software systems, traditional maintenance approaches have become insufficient. The concept of AIOps has emerged to enhance predictive maintenance using Big Data and Machine Learning capabilities. However, exploiting AIOps requires addressing several challenges related to the complexity of data and incident management. Commercial solutions exist, but they may not be suitable for certain companies due to high costs, data governance issues, and limitations in covering private software. This paper investigates the feasibility of implementing on-premise AIOps solutions by leveraging open-source tools. We introduce a comprehensive AIOps infrastructure that we have successfully deployed in our company, and we provide the rationale behind different choices that we made to build its various components. Particularly, we provide insights into our approach and criteria for selecting a data management system and we explain its integration. Our experience can be beneficial for companies seeking to internally manage their software maintenance processes with a modern AIOps approach.