True elasticity has long been the holy grail of cloud-native engineering. And while Kubernetes has revolutionized resource management, workloads that run sporadically (e.g., batch processors, event-driven workers, and development environments) still consume compute resources while they wait for work, driving up costs.

We’re addressing this head-on in Google Kubernetes Engine (GKE) 1.37 with a native way to scale to and from zero . A new collection of features allows you to scale down your workloads completely to zero replicas so that they stop consuming resources. At the same time, you can quickly and easily restart these workloads on GKE capacity buffers when demand returns, so you waste less infrastructure. This isn't just about saving money, but about decoupling the cost of always-on infrastructure from workload readiness.

For years, Kubernetes Event-Driven Autoscaling (KEDA) , an optional Kubernetes component, was the go-to solution for scaling to zero. While powerful, KEDA adds complexity to an environment.

Managed service; no extra components.

Requires management of ScaledObject CRDs & operators.

Native HPA & CRDs (minimal YAML).

Can exceed 10,000 lines of YAML for large fleets.

Internalized signal path reduces reaction time.