Atri Mandal, HEAL’s AI/ML expert, has written a second blog about the 4P strategy, this time primarily focusing on solution recommendation which gives useful suggestions to the SREs on how to fix problems pro-actively.

Modern IT environments have become much more complex to manage thanks to hybrid infrastructures and comprehensive instrumentation that generate metrics, alerts and events data constantly. ITOps (IT Operations) and SRE (Site Reliability Engineering) teams are tasked with providing superior performance and user experience for the numerous applications while not letting the budget out of hand.

In the recent past, every enterprise has had to deal with an outage, leading to war rooms where ITOps teams are put on the spot. While they take on the burden of ensuring 100% uptime, it is often the tools they employ which don’t live up to their promises. Especially in the wake of the pandemic, with working norms being redefined, ITOps teams have been under even greater pressure to deliver. While they strive to be efficient and rely on cutting-edge technology, uptime is often elusive.

Modern workflows are primarily aimed at one thing—reducing operational complexities so that stakeholders can focus on initiatives that boost business and innovation. For IT teams, Artificial Intelligence and Machine Learning play key roles in bringing this goal to life. And even though AIOps is considered to be not yet in mature stages, there is no denying that IT teams that do not adopt AI processes will be left behind. By 2023, the market for AIOps tools is predicted to reach $11.02 B.