Tech
June 9

Redefining operational maturity in Kubernetes with machine learning and automation

Advances in intelligent tooling are helping redefine operational goals for cloud platform teams. Learn how machine learning and intuitive automation will play an inevitable role in meeting objectives, and maybe even redefining your approach to initiatives like FinOps.
Talk abstract

The age of artificial intelligence is upon us, both dramatically improving the quality of the insights derived from complicated datasets, as well as accelerating time-to-value. As organizations’ cloud engineering practices mature and are accelerated through initiatives like FinOps, there can be unintended hurdles that surface along the way to implementing everything-as-code. Namely, the speed at which humans can make good decisions from complicated data like resource utilization metrics, and the time it can take to update and implement those changes using GitOps or even Jira tickets. In this session, learn how intelligent infrastructure automation tools can help overcome these hurdles, reduce the cognitive burden of keeping platforms running efficiently, and free up cycles for engineering teams to focus on a more diverse set of goals; even if that means bucking conventional cloud-native wisdom.

Brian Likosar
Sr. Solution Architect, StormForge

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