How to use AI to extract root cause from observability data

Presented by

Udo Strick, Waste Management, Joe Connelly, Chipotle & Jason Walker, BigPanda

About this talk

Constantly evolving IT environments have created an order-of-magnitude increase of change and complexity. Containers, CI/CD, microservices, and cloud-native applications deliver a deluge of alert and change data across a multi-cloud IT stack, making it nearly impossible to pinpoint the root cause of incidents - especially in real-time. The result: Reliance on manual, error-prone processes that strain already limited IT resources. A new approach is needed to identify the specific change causing an incident in real-time so organizations ensure service reliability while harnessing the power of hybrid cloud. Join our panel of IT leaders across diverse industries as they discuss how they prioritize AIOps strategies to accomplish faster and more reliable incident root cause discovery, impact incident triage, and significantly reduce mean-time-to-resolution (MTTR) beyond what manual resources can achieve. Attendees will learn: - The current state of root cause discovery - How to optimize the application of AI/ML through enrichment and correlation - The importance of clean, enriched data for reliable and reportable results
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BigPanda Inc. enables its customers to organize and mobilize the world’s DevOps and ITOps data. BigPanda’s Incident Intelligence and Automation platform, powered by AIOps, empowers some of the world’s largest brands to keep business running, prevent service outages, and improve incident management to deliver extraordinary customer experiences. BigPanda’s platform is critical for organizations across industries and enterprises of all sizes, from small and medium to Fortune 500 companies, to power their digital services.