The movies are filthy with examples of artificial intelligence. Some, like the first Terminator, are evil. Some, like the Star Wars droids, work for the good guys. And so many of them are flatly iconic—Blade Runner (both of them), 2001: A Space Odyssey, War Games, Westworld (the movie and the HBO series), Matrix[i] … the list keeps going and going.
There are times when running the same application on every node in a specific set of nodes in a cluster, or even the entire cluster is required. These are usually applications that provide some kind of system management functionality. Examples include storage processes which use local storage devices attached to the nodes, and log consolidation and diagnostic services which often feed data into an AIOps solution.
When it comes to “business as usual,” the workflow of IT teams today likely looks quite different than it did even a few months ago. Because of this, being able to adapt and put new safeguards in place that ensure uninterrupted business operations is more important than ever. In fact, it’s a necessity.
“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.