Major advancements in distributed architecture, multi-cloud, containerization, and the rise of microservices have created a vast array of multi-dimensional system data; data that, in turn, results in excessive noise that can stifle an organization’s ability to identify and resolve service incidents. In this talk, Data Science Lead, Mitra Goswami, shares how her team approaches the AIOps landscape to identify key opportunities for creating successful feedback loops that can feed into automation. She will highlight a few different happy paths or good incident learning curves that make good candidates for automation.

You’ll learn about:

• The challenge and opportunity for automation in incident response
• How PagerDuty for AIOps utilized a “systems thinking approach” to identify optimal ways for grouping incidents
• Considerations around designing happy paths and promising opportunities for auto-remediation