Practical MLOps for Network Operations at Uber

Host Philip Gervasi talks with Uber's Vishnu Acharya about how Uber applies machine learning and MLOps to network operations at hyperscale. Vishnu explains Uber’s intentionally simple network design across on-prem and multi-cloud, then shares practical machine learning use cases like predictive capacity planning, hardware failure rate-tracking, and alert correlation to reduce noise and speed mitigation. They also discuss organizational issues, including building blended network/software teams, partnering with internal ML groups, and focusing on service-level outcomes over hype.