GKE Autopilot mode gets burstable workloads and smaller Pod sizes
Autopilot mode for Google Kubernetes Engine (GKE) is our take on a fully managed, Pod-based Kubernetes platform. It provides category-defining features with a fully functional Kubernetes API with support for StatefulSet with block storage, GPU and other critical functionality that you don’t often found in nodeless/serverless-style Kubernetes offerings, while still offering a Pod-level SLA and a super-simple developer API.
But until now, Autopilot, like other products in this category, did not offer the ability to temporarily burst CPU and memory resources beyond what was requested by the workload. I’m happy to announce that now, powered by the unique design of GKE Autopilot on Google Cloud, we are able to bring burstable workload support to GKE Autopilot.
Bursting allows your Pod to temporarily utilize resources outside of those resources that it requests and is billed for. How does this work, and how can Autopilot offer burstable support, given the Pod-based model? The key is that in Autopilot mode we still group Pods together on Nodes. This is what powers several unique features of Autopilot such as our flexible Pod sizes. With this change, the capacity of your Pods is pooled, and Pods that set a limit higher than their requests can temporarily burst into this capacity (if it’s available).
