Sponsored by Yugabyte
As cloud-native AI deployments accelerate, Kubernetes practitioners face critical architectural and data decisions that determine success or failure. This webinar will discuss several critical design considerations for production-ready, data-centric AI systems. These include building on flexible and open standards, consolidating disparate data sources, achieving elastic scale while managing costs, ensuring compliance and security, and maintaining enterprise reliability. This session will discuss DocumentDB, the fast-growing open source document database and the benefits to AI systems of a multi-modal database approach. We’ll examine RAG architectures and demonstrate practical patterns for deploying AI workloads that integrate seamlessly with the CNCF ecosystem, helping platform engineers avoid lock-in and build truly portable, scalable AI systems.
