ITOA software can be provided on premises or via a cloud provider. The tool gathers and analyzes all the data from disparate live running sources, including log, agent, and wire data. For instance, it collects data from operating systems, hypervisors, applications, databases, network devices, and the web. ITOA uses Big Data principles to extract, correlate, combine, and analyze data to derive useful insights under data-driven monitoring practices.
So, how do ITOA tools work? These artificial intelligence-powered tools monitor the entire system, collecting information from disparate IT operations sources such as wire data, agent data, machine data (event logs), and transactional operations. Next, the tool stores and indexes the data in a data store.
The next step involves processing, normalizing, and turning the data into useful information. The software creates a baseline, learning what is normal for the system or environment, then combining and correlating different data sets to detect abnormal patterns.
Finally, the tool sends alerts with recommendations on the issues it found.
This provides organizations with a heads-up over operations, enabling them to diagnose, prioritize, and resolve issues quickly and efficiently. ITOA tools leverage automation to solve low-level or common problems, saving time and effort from IT Ops.
Common applications for ITOA systems are:
Root cause analysis: Helps pinpoint unknown root causes of system behavior problems.
Problem assignment: Provides insights on how these problems may be resolved.
Service impact analysis: Enables organizations to determine the potential impact of the issues so they can be fixed in the most timely and effective way.
Control of service performance and availability: Predicts the state of the system and how the issues can affect performance.
Application behavior learning in real time: Correlates and compares the behavior of applications, creating a baseline for future comparisons.