Understanding AIOps & Probable Root Cause Analysis

Presented by

Robert Harper, Chief Scientist, Moogsoft & Richard Whitehead, Chief Evangelist, Moogsoft

About this talk

Despite decades of R&D dedicated to Root Cause Analysis — and counter to the claims of numerous technology vendors who claim to offer it — the traditional approach to RCA and concepts behind it have been flawed. Leading analysts like Gartner agree that Root Cause Analysis is still a people-dependent process. Furthermore, they recommend that ITOps leaders leverage machine learning technology to provide contextualized information across the production stack, understand similarity in events from the past, and accommodate human interaction so that the algorithms can learn from human behavior over time. Moogsoft’s unique Probable Root Cause is the first technique that can understand causality in unpredictable IT environments with a significant degree of certainty, and without reliance on a model. In this webinar recording, Moogsoft executives Richard Whitehead and Robert Harper discuss this innovative approach to Root Cause Analysis, and how it can change the way your operations teams address IT incidents.
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Moogsoft develops AIOps technology that helps enterprise IT Ops and DevOps teams become faster, smarter and more effective. Moogsoft AIOps’ real-time machine learning algorithms help teams remediate issues that impact their customers’ experience by: • Reducing operational noise (alert fatigue) across your production stack • Proactively detecting Incidents and correlating Events across your monitoring ecosystem • Streamlining collaboration and workflow across teams and toolsets • Codifying knowledge to make operators smarter when encountering future Incidents