2025-09-20 –, 101 (Capacity 48)
This talk explores how platform engineering teams can build a self-service AI/ML infrastructure on Kubernetes—enabling dynamic provisioning, policy enforcement, and full observability—while allowing data scientists to stay focused on model development.
While ClusterAPI simplifies cluster provisioning, managing AI/ML workloads demands a full-lifecycle approach. We demonstrate how to extend ClusterAPI with tools like Backstage, OpenFeature, k0s, Prometheus, Sveltos, and k0rdent to build a scalable, secure, and automated AI/ML platform.
Key takeaways include:
- AI/ML cluster provisioning with ClusterAPI and k0s
- Policy-driven multi-cluster automation
- Controlled model rollouts with feature flags
- Self-service ML environments via an Internal Developer Platform
- Observability and performance monitoring at scale
Join me to discover how a Kubernetes-native approach can empower your AI/ML platform engineering journey.
Intermediate - attendees should be familiar with the subject
Prithvi Raj is working as a Community Manager & Developer Advocate at Mirantis and is leading the community efforts for the OSPO at Mirantis including the k0s project, k0smortron, and the other OSS projects Mirantis is contributing to. He previously led the LitmusChaos project community, and has helped scale a community of 3000+ folks from scratch.
He is also a CNCF Ambassador and has closely worked to co-organize KCD Bengaluru, Chaos Carnival and LitmusChaosCon
He was previously at Harness.