By IT Brew Staff
less than 3 min read
Definition:
Artificial intelligence for IT operations, or AIOps, is the process of using AI, machine learning, and data analytics to better manage IT systems.
Use cases for AIOps
Companies may leverage AIOps platforms to target several needs. For example, AIOps can help with threat and anomaly detection by flagging things like unusual login activity. AIOps is also good for root-cause analysis, which is when a platform examines data to identify the cause of a problem, as well as enact automated incident response.
The benefits of AIOps
The case for using AIOps platforms is a good one. AIOps can help organizations save money when issues are detected early and addressed without significant downtime. Since anomalies can be discovered before they become huge problems, AIOps helps IT teams take a more proactive approach to security.
There’s yet another cybersecurity benefit: For employees, AIOps can help address “alert fatigue” by reducing the number of false positives teams face.
AIOps platforms also automate a lot of manual and repetitive tasks, allowing for teams to be more efficient with their time, along with giving them a unified view into their organization’s IT infrastructure.
It’s not all that easy
There are a few challenges that organizations face when trying to leverage AIOps. For one, AIOps works best in a unified data environment, something many organizations struggle to achieve. “Dirty data,” or datasets that are missing information or values, can also reduce the accuracy of AIOps.
