First, it’s about processing data fast: AIOps gives you the ability to enable real-time data correlation, and even better, almost all data is a candidate for this processing. Raw data can be ingested into smart algorithms powered by machine learning and big data. This can help you derive new insights from your raw data sets. This data ingestion and analysis can then help you create and set new targets for key metrics such as mean time to detect and mean time to repair.

Second, it’s about data-driven decision making: Machine learning is based on algorithms that can learn from data without relying on rules-based programming. AIOps brings key ML techniques to your IT operations, including pattern matching, predictive analysis, historical data analysis, and causal analysis. This helps with decision making by enabling purely data-driven, automated responses. Such automated responses to incidents eliminate human error and data noise. This newfound automation allows your staff to focus on resolution instead of detection.

Third, IT work will become more proactive: No matter what purpose and mission your organization has, your success depends on how satisfied your customers or clients are with your products or services. In a competitive environment, it is no longer enough to respond to actual events. It’s now essential to predict possible issues and bottlenecks. This means IT operations must be able to predict and remediate performance issues across your applications, services, and infrastructure before they materialize and cause issues for customers or partners. AIOps helps enable this shift.