AIOps is short for Artificial Intelligence for IT Operations. Cognitive Operations, Algorithmic IT Operations and IT Operations Analytics (ITOA) are other names you might recognize.
AIOps is the application of big data analytics and machine learning to IT operations data to intelligently identify patterns and augment common processes and tasks.
Industry analyst have defined a set of capabilities that an AIOps solution should provide. These include:
- Collecting data from many sources such as: networks, applications, databases, and cloud as well as in a variety of forms including metrics, events, topology, log files, streaming and unstructured data like social media post and documents (natural language processing).
- Managing the data, storing the data in a single place accessible for analysis and reporting, also including functions like indexing and expiration
- Analyzing the data including pattern detection, anomaly detection and predictive analytics
- Conducting root cause analysis (RCA) which involves reducing the volumes of data to the few (or one) most likely causes.
- Acting as a strategic overlay that aggregates multiple monitoring tools and other investments
Why is AIOps needed?
No human can process the explosion of data IT Operations is expected to handle, and more systems are providing data that IT needs to monitor most notably Internet of Things (IoT). For example, a locomotive can produce terabytes of data during a trip. In IT terms this explosion is called Big Data.
Benefits of AIOps
The benefits users have found using AIOps include:
- Reduced workload on IT Operations staff because AI is helping with the analysis
- Faster root cause analysis (RCA) because AI pinpoints the problem or reduces the number of items operators must look at to a small set
- Prevent problems before customers are impacted via anomaly detection
- Faster Mean Time to Resolve (MTTR)