Artificial Intelligence for IT Operations promises to transform IT Operations - according to Gartner.
What are the Building Blocks and how can you validate the value and feasibility for your organization?
Artificial Intelligence for IT Operations, is a term coined by Gartner. AIOps is powered by two core technologies that continue to go through a riveting pace of development, Big Data and Machine Learning (ML).
The availability of Big Data and Machine Learning capabilities powers the massive computing required to analyze the thousands, millions, and billions of data points and log files harvested by AIOps tools. Using smart machine learning algorithms, and artificial intelligence, AIOps gathers and analyzes data from different sources and automatically identifies issues through the multiple IT layers and across the stack to ultimately trigger intelligent remediation.
If data harvesting is the floor, then the learning and correlation engine represents the two walls of the building. Using the power of AI and machine learning (ML), AIOps learns the normal behavior patterns of the data, identifies and correlates relationships, and makes sense out of a vast amount of events. Using anomaly detection, AIOps detects abnormalities that can lead to significant problems.
A bonus capability from all the data and actionable insight are dashboards and reports. In practice, the data is real-time business intelligence. Possibly better than any traditional BI tool, real-time with built-in anomaly detection and predictive analytics.
The ability to leverage this data and insight for reports and dashboards for stakeholders across an organization - from technical to managers and executives will be crucial to the required governance of IT that the profit & loss of businesses rely on.
Last, but certainly not least, taking action with AIOps forms the roof. Every capability before this one enables you to take action whether that action is manual or automated. Once the data from many sources has been harvested, processed by the anomaly detection engine, and analyzed for context-aware, domain agnostic anomalies, then the resulting probable root cause can be identified and acted upon quickly. This may be manual action or automated action by triggering auto-healing scripts.
Achieve effortless IT monitoring with truly automated AIOps platform.