Observing & Securing
GenAI Applications on Kubernetes
Learn to identify GPU waste, troubleshoot performance issues,
and secure workload egress.
and secure workload egress.
This session focuses on practical, production-ready techniques for observing and securing Gen AI applications where performance, reliability, and security are tightly coupled.
Limited to 500 attendees.
Registration closes 24 hours before the event.
Nick Chase leads the AI practice for CloudGeometry and chairs the Models, Applications, & Data workstream of the LF AI&Data Generative AI Commons. He brings deep expertise in cloud-native AI/ML infrastructure and Kubernetes architectures.
Veronika’s tech career spans from early black-box testing of VB6 apps to architecting modern cloud platforms. As Technical Marketing Manager at Tigera, she blends an English Literature background with deep technical expertise, using her CKA and CKAD certifications to translate complex Kubernetes and cloud-native concepts into practical guidance.
Dinesh is driving channel success across partners, SIs, resellers, and distributors. With 10+ years in SaaS and cybersecurity sales, account management, and BD, he holds an MBA plus Microsoft/Azure security certifications focused on cloud and network security.
