We spoke with Guy Fighel, General Manager & GVP Product Engineering at New Relic about AI and AIOps. What role does artificial intelligence play when it comes to monitoring and observability? What are the best practices when implementing AI within your team?

JAXenter: Hello Guy and thanks for taking the time for this interview. At the Future of AI conference, you spoke about AI, AIOps, and the role of artificial intelligence when it comes to Noise Reduction. So for starters, what exactly is “Noise Reduction”?

Guy Fighel: Today, with the proliferation of IT monitoring tools, the volume of daily alerts an SRE or DevOps team has to deal with is often in the tens of thousands. But the problem is more than just seeing the forest for the trees: The world of SRE and DevOps teams is all about fast responses. The ability to quickly diagnose and resolve a problem can mean thousands of dollars or clicks.

Overwhelming IT noise means that IT Ops and DevOps teams are flooded with false positives (aka ‘symptom’ alerts) on an everyday basis, making the identification of root cause nearly impossible. And, in order to deal with this overwhelming situation, organizations often filter alerts so that only those deemed high-severity (commonly known as P0 or P1 issues) reach the responding team. This creates a blind spot in the organization’s operational visibility, since low-severity alerts are often precursors to the high-severity ones, leading to what everyone hates – alert fatigue. Reducing this ‘noise’ for IT operations teams and helping teams prioritize alerts and find signals through the noise is more important than ever.

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