“Welcome to Tomorrowland.” That’s how Moogsoft Chairman and CEO Phil Tee kicked off the launch event of Moogsoft Express, the next-generation AIOps and observability solution built from the ground up for DevOps and SRE teams. The reference to a better future is fitting. With its arrival, Moogsoft Express helps these teams maintain visibility and control over increasingly complex CI/CD pipelines, so they can detect issues earlier, fix them faster and prevent outages.

In this final installment of this blog series, we’ll discuss the importance of monitoring your observability data. Collecting and analyzing your metrics, logs, and traces in real-time is incredibly important and will provide you with the cues, signals, and insights you need to build your service assurance strategy. Only when applied with AIOps will you achieve true operational scale and automation.

Selecting the right AIOps platform is just the beginning. It’s crucial for the technology to be implemented quickly and efficiently, and to demonstrate value quickly. This is true for any major technology investment but it is particularly true of AIOps. Why? AIOps, and AI in general, has in recent years been the subject of extreme hype. Its promise seems boundless. At the same time, it is poorly understood by those outside — and even inside — of the IT community.

Information Technology (IT), like many other industries, is tapping into the latest advancements in Machine Learning (ML) and Artificial Intelligence (AI) to solve a decades-old problem in the IT management world. History can teach us many things, and by diving into years of accumulated IT data, we can find meaningful insights and use them to guide the future.

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.