by Sam Weston
Enterprise observability is entering a new phase as artificial intelligence changes both the applications companies need to monitor and the way operations teams respond when something goes wrong.
Traditional observability platforms were built around deterministic software and telemetry, such as logs, metrics and traces. But AI applications and agents behave differently, producing outputs that can vary even when given similar inputs. At the same time, enterprises increasingly expect observability platforms to move beyond identifying problems and provide enough context for humans and AI agents to diagnose, remediate and potentially act on those problems.
That transition provides the backdrop for Dynatrace’s acquisition of Arize AI, which brings AI observability, evaluation and agent monitoring capabilities into Dynatrace’s broader application observability platform.
In the latest episode of theCUBE Research’s AppDevANGLE podcast, Practice Lead and Principal Analyst Paul Nashawaty spoke with Steve Tack, chief product officer of Dynatrace, and Aparna Dhinakaran, co-founder and chief product officer of Arize AI, about why application observability and AI observability are converging and what that means for enterprise operations.
