What is AIOps?



The term “AIOps” stands for “artificial intelligence for IT operations.” Originally coined by Gartner in 2017, it refers to the way data and information from an application environment are managed by an IT team -- in this case, using AI. Here’s Gartner’s definition:

“AIOps platforms utilize big data, modern machine learning and other advanced analytics technologies to directly and indirectly enhance IT operations (monitoring, automation and service desk) functions with proactive, personal and dynamic insight. AIOps platforms enable the concurrent use of multiple data sources, data collection methods, analytical (real-time and deep) technologies, and presentation technologies.

Since AIOps is an emergent space, the definition is highly fluid. But the core elements consist of:

The Elements of AIOps

 Machine Learning

 Performance baselining

 Anomaly detection

 Automated root cause analysis

 Predictive insights

AIOps Use Cases

AIOps has the potential to help IT professionals in three major areas:

Decrease MTTR

Decrease MTTR

AIOps platforms provide faster resolutions to outages and other problems, and in the process, decrease MTTR and costs associated with performance challenges.

Proactive performance monitoring

Proactive performance monitoring

Build a more proactive approach to performance monitoring. By taking in the totality of application environment data, AIOps platforms connect performance insights to business outcomes.

Drive faster and better decision-making

Drive faster and better decision-making

AIOps platforms can help surface insights to IT professionals to drive better and faster decision-making.

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