AIOps is a new technology to increase the speed and accuracy of AI and IT operations. With the increasingly complex network system, IT operations have become more challenging. Operators are struggling to manage all the network and traffic with traditional tools. AI can capture extensive data, analyze them, predict, and prevent future issues. It saves operators time and energy. They can focus on their core works.
AIOps Use Cases
AIOps is the combination of AI and Operation teams to get the best out of it. From day to day work to service management, AIOps can automatically manage many operational tasks. To better understand its uses, here are five key use cases of AIOps:
1. Data Management and Performance Analysis
For performance analysis, operators need to analyze a vast volume of data. Manually processing data takes a huge time but gives error results. AI and ML solve this issue. It processes large data and analyzes them. Then it provides error-free predictions to prevent issues.
2. Outlier Detection
Outlier data means to identify changes in patterns in operation tasks. ML learns patterns from historical data. It compares new data with historical data to find even the most minor changes in patterns. Automation speeds up the detection process to find it at an earlier stage and send signals to the operation teams.
3. Correlation Analysis
Correlation analysis can identify related warnings and determine how to fix them. But in the traditional system, operators can only determine the warnings. AI can separate notable events according to their similarities. It helps operators to manage events, reduce traffic and noises continuously.
4. IT Service Management
IT service management refers to every task involved in managing IT services like – designing, building, delivering, supporting, and managing. It helps to manage infrastructure in a multi-cloud environment. Its prediction ability is high. It also manages multiple devices connected across a single network.
Automation is the core of AIOps. It automatically collects all the necessary data from reliable sources and correlates them. Thus it increases the speed and accuracy. It continuously monitors the performance, usage, and availability of the cloud infrastructure.
AIOPs improve operating functions and system performance. It helps to increase customer satisfaction by improving the quality of the software. Businesses need to implement AIOps as early as possible to stay ahead of the competition.