The mandate is clear: deploy AI to the edge. Yesterday. The promise is huge—automated defect detection, smarter retail, and predictive maintenance, all without costly cloud backhaul. But the reality is… messy. Edge ops don’t sleep, and “cloud-native” tools weren’t built for the chaos of flaky networks, resource-starved hardware, and massive cluster sprawl. You need the self-healing power of Kubernetes, but datacenter distros crumble under edge constraints. Worse, you’re expected to ship updates continuously. That points to GitOps, but the toolchain to securely connect your CI/CD pipeline to a thousand distributed K8s clusters has been missing. It’s time for a better way. In this no-fluff session, edge computing expert Sachin Vasudeva, VP of Product for ZEDEDA, gets straight to the code and concepts. You’ll learn how to:
- Build bulletproof, GitOps-based CI/CD workflows that automate delivery from repo to edge.
- Deploy high-availability Kubernetes applications that are actually designed to survive in the wild.
- Unleash the full power of your AI models on hardware like NVIDIA Jetson GPUs.
See how the GitOps + K8s + GPU formula solves for speed, scale, and stability, turning your edge into a genuine advantage.
