Presented by Kasm TechnologiesEnterprise infrastructure teams have spent the better part of a decade pushing workloads into Kubernetes. Applications, APIs, batch jobs, data pipelines — if it runs in a container, it belongs in the cluster. The operational benefits are well-established: declarative configuration, horizontal scaling, self-healing, native integration with CI/CD pipelines and observability tooling. Kubernetes has become the default operating model for production workloads.Except for desktops.Secure desktop and application delivery — the kind that enterprises depend on for remote work, privileged access, and regulated-industry workflows — has remained stubbornly outside the Kubernetes model. Legacy virtual desktop infrastructure was built in a different era, for a different set of assumptions: pre-allocated VM pools, bespoke management planes, proprietary appliances, and operational tooling that has nothing to do with how modern platform teams work. The result is a split infrastructure reality: a modern, cloud-native application layer on one side, and a manually managed, operationally isolated desktop layer on the other.That split is expensive. It means different tooling, different scaling behaviors, different observability approaches, and different operational runbooks. Platform engineers who are proficient in Kubernetes still have to context-switch into an entirely different mental model the moment a desktop infrastructure problem arises.The more fundamental issue is that this split is unnecessary. Secure, containerized workspace delivery is a workload that Kubernetes is architecturally well-suited to run. Sessions are containers. Scaling is demand-driven. Configuration should be declarative. The only thing missing was a platform built to take advantage of that alignment.Why the timing is rightThe appetite for Kubernetes-native workspace delivery has grown significantly as organizations mature their container platform investments. Platform teams that have spent years standardizing on Helm, GitOps workflows, and Kubernetes-native obser …
