AI and ML, together with the right sensors and data sources, can make mid-large sized enterprise IT ops easier to manage

Artificial Intelligence for IT operations (AIOps) is an approach to IT infrastructure management that uses Big Data and Machine Learning to automate the necessary IT operations.

An AIOps platform collects data from various sources, including system logs, application performance monitoring (APM), and network monitoring tools. This data is then analyzed in real-time to identify issues and anomalies.

The machine learning algorithms used by AIOps platforms are constantly evolving, which means they can become more effective at identifying and resolving IT issues over time. This can help improve the efficiency of IT operations teams and the quality of service for end-users.

Should mid-large enterprises adopt AIOps?

The larger enterprises can align with an AIOps approach to manage IT infrastructure for a variety of reasons:

  • Operational efficiency: Automating and integrating data from disparate systems with AI can help mid-large enterprises improve their ability to identify and resolve problems quickly and efficiently.
  • By reducing the number of false positives and negatives generated by monitoring systems (and the need for manual intervention), AIOps can help reduce improve labor efficiency and overall IT operational costs.
  • Enterprises can use AI in their IT Ops to identify and resolve potential risks and compliance issues before they impact the business, by providing a more complete and accurate picture of the IT infrastructure.
Arun Prasath R, CIO, EverestIMS Technologies

Six benefits in detail

The deep learning of AI and ML features in an IT infrastructure helps organizations go from a proactive to a predictive state of operations by providing a real-time view of the entire IT environment, detecting issues early, and offering recommendations for remediation. Such smart ops can even help reduce mean-time-to-repair and improve service levels. Also:

  • Detect anomalies that usually go unnoticed

AIOps platforms can use data from multiple IT data sources to detect anomalies caused by hardware/software failures, configuration changes, or user errors. Anomalies can include clustering, outlier detection, and time-series analysis. Once an anomaly is detected, the smart platform can generate an alert sent to the appropriate IT staff.

  • Discover hidden relationships between discrete systems and processes

Applying big data analytics and ML to IT operations data helps administrators to discover hidden relationships between discrete systems and processes and all the variables. Knowing these latent relationships helps IT teams identify and diagnose problems in real-time to predict and prevent future issues.

In addition, AI IT Ops platforms can offer valuable insights into the behavior of systems and processes, which can be used to improve the design of future systems.

  • Improve capacity planning

Traditional capacity planning methods are often based on intuition and experience, which can lead to errors in judgment.

On the other hand, AI can provide a more objective and data-driven approach to capacity planning. This can enable firms to utilize their resources better and avoid over- or under-capacity.

In addition to improving accuracy, AI can help businesses save time and money. By automating the process, enterprises can free up resources that can be better spent on other tasks. AI can also help enterprises to keep track of a more significant number of variables and identify patterns that go unnoticed by a human workforce.

  • Enhance performance monitoring and service delivery

The predictive analytics features of AIOps can forecast the use of resources and performance issues, easing the service desk workload by assessing the patterns of support tickets, usage, and customer interaction. It enables anomaly detection and identifies the problems to fix issues proactively.

  • Enable digital-first operations

Enhancing IT operations with AI adds business value with a digital solution that reduces time and labor leaving teams to focus on other business areas, including innovation and expansion. AIOps enables end-to-end visibility into an enterprise’s applications and infrastructure.

  • Enhance customer experiences

AIOps offers real-time insights from customer activity and predictive analytics that enable data-driven decisions. Understanding customers trends helps improve product and service delivery, leading to richer customer experiences.

With the right platform for adding AI/ML to IT operations, organizations can self disrupt their IT infrastructure in a positive way, taking system availability and performance to a new level regardless of the complexity of operations.