Part 3/11:

• Difficulty in log analysis, making it hard to pinpoint root causes swiftly.

For example, when a critical application crashes, human responders often struggle to diagnose issues promptly, risking revenue loss and damage to reputation. The human element introduces delays and errors, highlighting the need for smarter, automated solutions.

What is AI Ops? A Definition and Core Components

According to Gartner, AI Ops combines big data analytics and machine learning to automate IT operations. The core idea is to ingest vast amounts of operational data—logs, metrics, traces—from various sources, analyze them using AI, and then generate actionable insights or even automatic remediation.

The speaker explained the fundamental flow of AI Ops in three key stages: