There’s an AI-led developer and operations (DevOps) evolution afoot which is stoking SREs’ increasingly critical efforts to assure and improve the customer experience by automating the toil out of observability. This movement feeds on a supercharged process of turning telemetry into actionable insight by automatically drawing anomalies, changes and events out of the full-stack event and telemetry data, and analyzing it for correlation and causality.

In the evolving world of IT monitoring, I see that many organizations want to move to predictive monitoring. They usually allocate a significant budget for this type of effort that ultimately fails to yield the desired return on investment. Often, organizations are already collecting and processing large amounts of IT telemetry streams and using multiple solutions to monitor their systems. So, predictive monitoring seems like the logical next step.

Artificial intelligence for IT operations (AIOps) means a lot of different things to a lot of different people, so a definition of what it is and what it does is difficult to nail down. In an age where digital acceleration is priority zero, companies are evaluating cultural shifts towards new operating models like service ownership to unlock efficiency in a complex world of hybrid cloud environments, AIOps emerges as an attractive potential investment to solve central IT aches and pains.

Artificial Intelligence for ITOps (AIOps) can help accelerate incident response with all the incident context, impact assessment, triage data and collaboration & automation tools at one place.

Today, network automation has shifted from nice-to-have to must-have. Automating key NOC processes (ranging from simple to complex) offers a wide range of benefits. But don't take my word for it — the ROI numbers speak for themselves.

Gartner recently released their top strategic technology trends for 2021. It’s no surprise that these trends reflect what many of us and our organizations have been experiencing, dealing with ongoing challenges during this global pandemic.

Are your current expensive, traditional or legacy monitoring tool implementations holding you back? It may be time to look into Observability architectures.