Building Resilient Hybrid Cloud-Native Architectures for Edge Inference

The intersection of cloud-native principles and edge computing necessitates robust, scalable architectures capable of handling intermittent connectivity and resource constraints. This talk explores the design patterns for building resilient hybrid infrastructure tailored for local inference tasks. We will discuss the challenges of maintaining state and orchestrating services across distributed environments using Kubernetes. The session will detail how to architect control planes that gracefully handle edge node disconnections and the strategies for deploying containerized AI workloads seamlessly across diverse hardware environments. By focusing on the foundational cloud-native technologies, attendees will learn how to construct reliable systems that bring computation directly to the user's environment.