What Is AIOps? Artificial Intelligence for IT Operations

First coined by Gartner in 2017, artificial intelligence for IT operations (AIOps) refers to the application of machine learning to big data analytics for the automation and management of IT operations. Take any area of IT operations—log analytics, application monitoring, service desk, incident management, etc.—augment it with AI, and you’ve got AIOps. There are many ways AI can be integrated into existing IT operations to help your team be more proactive, accurate, and productive. Let’s take a closer look at the basics of AIOps. 

What Is an AIOps Platform? 

Modern IT deployments must increasingly deal with bigger and faster data demands. This data is often unstructured and streaming in real time from a large network of siloed sources. AIOps platforms help ITOps teams make sense of the volume, variety, and velocity of big data. 

Gartner defines AIOps platforms as tools that help organizations consolidate siloed data sources into big data to enable continuous insights across IT operations and monitoring (ITOM).

How AIOps Automation Streamlines Traditional Operations

The best way to understand AIOps is to consider what a typical IT operations professional must do to respond to a disruption of services and how AI can automate the process. Gartner breaks the cycle of responding to and resolving disruptions into three steps: 

1. Observe: The initial incident that triggered the disruption must be noticed for someone to respond to it. An AIOps platform automatically ingests logs, metrics, alerts, events, and other data needed to understand what is going on behind the scenes of an app when the incident occurred. Instead of a human manually pulling that information from disparate data sources and trying to make sense of it all, the platform will consolidate all of this data and identify patterns. 
   
2. Engage: This step involves analyzing the monitored information and diagnosing the root cause of the disruption. Relevant information for resolving the issue is contextualized and passed on to the responsible operations personnel best equipped to resolve it. The AIOps tool can perform risk analyses, automate communication of responsibilities, and package relevant data for IT operations staff. 
3. Act: The directly responsible individual (DIR) resolves the issue, restoring service to the application. Scripts, run books, and application release automation (ARA) can be created that will automatically run the next time the AIOps tool detects this particular issue. 

By automating parts of the process, AIOps can help IT operations respond to disasters faster, minimizing recovery time objectives (RTOs) and recovery point objectives (RPOs). 

Common AIOps Solutions

There are probably as many AIOps tools out there as there are IT operations that could be automated. Here’s a list of typical ITOps roles that may be automated with machine learning:

• Application management
• Technical management
• Incident management
• Service desk management
• Configuration management
• Infrastructure management
• Disaster mitigation

When picking an AIOps solution, it’s important to choose the tools that make the most sense for your organization’s IT operations needs. Check out “5 Ways AIOps Helps DBAs Beat Burnout” to learn more about how AIOps can help your business. 

Pure1 AIOps Platform 

Pure1® is an AIOps platform that helps consolidate all your data sources into a single storage management solution. Powered by AI, Pure1 Meta® automates the tracking, monitoring, and analysis of your infrastructure by leveraging predictive analytics to identify issues before they become a problem. Knowledge is power, and Pure1 can help you take back control of your data.