Operations | Monitoring | ITSM | DevOps | Cloud

Humans are naturally visual creatures. Several of us are visual learners, meaning, we learn by seeing things in action. Tracing is seeing things in action. Troubleshooting where and why something is slow or flat out broken, with clear visual indication, is incredibly powerful.

AIOps is a term Gartner invented to describe a general trend of applying AI techniques to IT Operations data sources to provide additional insights and scale to the teams operating today’s complex software system. AIOps is essentially a feature or set of features to analyze, combine, and collect data. Unfortunately, the lack of AI in these solutions often turns many people off, but this promise is still possible.

What drives an enterprise’s decision to adopt an AIOps platform? Which key problems are they trying to solve? Once it’s deployed, how can they track its value, and explain it to non-IT business leaders? What cultural and technology changes does an AIOps deployment trigger?

Network/Security Operations Center (NOC/SOC) engineers and service desk personnel are tasked to process numerous incidents as quickly as possible. However, to resolve an incident they are required to to perform various activities including collecting various operations data including metrics, logs, traces and more from different tools. In many cases, the process also involves coordinating with other IT personnel or creating a war room to bring the incident to closure.

Based on our interactions with buyers evaluating vendors in the AIOps market, much of what we’re hearing chimes with this quote - “What will AI allow us to automate? We'll be able to automate everything that we can describe. The problem is: it's not clear what we can describe.” Stephen Wolfram, computer scientist and physicist.