Data Silos A Roadblock for AIOps

TL;DR

This paper discusses how data silos hinder the adoption of AIOps in IT operations, analyzing their causes, impacts, and potential solutions to improve data centralization.

Contribution

It provides an in-depth analysis of data silos in organizations, highlighting their effects on AIOps implementation and proposing strategies to overcome these barriers.

Findings

81% of organizations have data scattered across silos

Data silos significantly impede AIOps adoption

Solutions for data centralization can facilitate AIOps deployment

Abstract

Using artificial intelligence to manage IT operations, also known as AIOps, is a trend that has attracted a lot of interest and anticipation in recent years. The challenge in IT operations is to run steady-state operations without disruption as well as support agility" can be rephrased as "IT operations face the challenge of maintaining steady-state operations while also supporting agility [11]. AIOps assists in bridging the gap between the demand for IT operations and the ability of humans to meet that demand. However, it is not easy to apply AIOps in current organizational settings. Data Centralization is a major obstacle for adopting AIOps, according to a recent survey by Cisco [1]. The survey, which involved 8,161 senior business leaders from organizations with more than 500 employees, found that 81% of them acknowledged that their data was scattered across different silos within their organizations. This paper illustrates the topic of data silos, their causes, consequences, and solutions.