What is AI ops?

AI ops is a term that refers to the use of artificial intelligence (AI) capabilities, such as natural language processing and machine learning models, to automate and streamline IT operations processes. AI ops can help IT teams to collect and analyze large volumes of data from various sources, such as IT infrastructure components, application performance monitoring tools, and service ticketing systems, and to identify and resolve issues related to application performance and availability.

To illustrate how AI ops works, here are some examples of how it can benefit different IT operations scenarios:

- Incident management: AI ops can help IT teams to reduce the number of incidents by detecting and preventing issues before they escalate, using predictive analytics and anomaly detection techniques. For example, AI ops can alert IT teams of potential disk failures or memory leaks before they affect the application performance. AI ops can also help IT teams to reduce the mean time to resolution (MTTR) by diagnosing root causes and suggesting or executing remediation actions, using causality determination and automation capabilities. For example, AI ops can automatically restart a service or scale up a resource when an issue is detected.

- Change management: AI ops can help IT teams to assess the impact and risk of changes by analyzing historical data and simulating scenarios, using machine learning models and what-if analysis techniques. For example, AI ops can predict how a change in configuration or code will affect the application performance and availability, and suggest the optimal time and method for implementing the change.

- Capacity management: AI ops can help IT teams to optimize the utilization and allocation of resources by forecasting demand and supply, using machine learning models and optimization techniques. For example, AI ops can anticipate the peak load and traffic patterns of an application, and recommend the best way to scale up or down the resources accordingly.

AI ops can improve IT operations management by providing end-to-end visibility and context across the IT landscape, and by bridging the gap between siloed teams and tools. AI ops can also enhance user experience and satisfaction, by reducing downtime and improving service quality.

AI ops is considered to be the future of IT operations management, as it can help IT teams to cope with the increasing complexity and dynamism of the IT environment, and to meet the rising expectations of users and business stakeholders for uninterrupted and high-performing applications.