Ed Fullman On Stage
summary
Claims concrete outcomes: ML reduces noisy alerts and burnout by suppressing normal peaks, demonstrated with DataDog AI anomaly detection improving on baseline statistical models. References Google DORA data (36,000 assessments) and a 40% higher organizational performance when teams stay user-focused and 20% higher job satisfaction from that focus. Describes a Veritas Automata SaaS that combines Rancher K3s, GitOps, Mender OTA, ROS2 and Hyperledger Fabric to run blockchain + IoT + ML at edge and cloud and the tradeoffs of customization, data retention and vendor lock-in.
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chapters (7)
- 0:00Introduction and speaker background
- 3:18Presentation objectives and Dora report
- 7:14Google Dora report AI insights
- 10:02Machine learning devops use cases
- 14:41DataDog AI anomaly detection
- 19:47Transformational leadership with AI
- 22:21Reducing burnout in devops teams
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