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August 05, 2025
The M4 machine series is generally available in GKE Standard clusters.
July 28, 2025
In GKE version 1.32.2-gke.1359000 and later, you can now configure collection scheduling for single-host and multi-host TPU node pools by using compute classes. Collection scheduling lets you set a Service Level Objective (SLO) for your TPU workloads.
In GKE version 1.33.2-gke.1335000 and later, the GKE Gateway controller supports Gateway API v1.3 CRDs.
November 26, 2024
Cluster autoscaler and node auto-provisioning support the C4 machine family in GKE version 1.28.15-gke.1159000, 1.29.10-gke.1227000 or later.
May 02, 2024
The new release of the GKE Gateway controller (2024-R1) is now generally available. With this release, the GKE Gateway controller will provide the following new capabilities and fixes:
New capabilities:
- Gateway API CRDs v1.0.0
- Cloud Armor backend security policy support for Regional external Gateways
- Self-managed certificates with Certificate Manager on Regional internal & external Gateways
- Google-managed certificates with Certificate Manager on Regional internal & external Gateways [Preview]
Bug fixes:
- Fixed missing permissions to MCI service agent role for regional SSL policy
To learn more about our GKE Gateway controller capabilities, see the supported capabilities per GatewayClass.
April 10, 2024
The N4 machine family is generally available in GKE Standard clusters running on GKE 1.29.3-gke.1121000 and later. You can select this family by using the --machine-type flag when creating a cluster or node pool. The following limitations apply:
- Confidential GKE nodes is not supported.
- Local SSD is not supported.
hyperdisk-balancedis the only supported boot disk type.
This note was updated on June 3, 2024. The GKE version required for N4 machine type support has been updated.
March 11, 2024
Private clusters created on GKE versions 1.29.0-gke.1384000 and later use Private Service Connect (PSC) for nodes to privately communicate with the control plane. There is no price increase for using GKE private clusters running on PSC.
For private clusters created with a different GKE version, the clusters continue to use VPC Peering for node-to-control plane communication.
Opportunistic bursting and lower Pod minimums are now available on newly created GKE Autopilot clusters at version 1.29.2-gke.1060000 or later, and on existing clusters created at 1.26 or later that have been fully upgraded (including all nodes) to 1.29.2-gke.1060000 or later. To learn more, see Configure Pod bursting on GKE.
March 04, 2024
GPU workloads running in Autopilot mode can now be configured using the Accelerator Compute Class. This configuration supports resource reservations, Compute Engine committed use discounts, and a new pricing model in GKE versions 1.28.6-gke.1095000 and later, and 1.29.1-gke.1143000 and later.
December 19, 2023
You can now modify the vm.max_map_count Linux kernel attribute for nodes in a GKE Standard cluster node pool using the node system configuration. To learn more, see Sysctl configuration options.
August 25, 2023
GKE now delivers insights and recommendations to ensure your workloads are ready for disruption using features such as Pod Disruption Budgets. To learn more, see Ensure stateful workloads are disruption-ready.
July 24, 2023
GKE Autopilot supports extended duration Pods from 1.27 or later with the cluster-autoscaler.kubernetes.io/safe-to-evict=false annotation. To learn more, see how to extend the run time of Autopilot Pods.
July 11, 2023
Starting in GKE version 1.27, cluster autoscaler always considers Compute Engine Reservations when making the scale-up decisions. The node pools with matching unused reservations are prioritized when choosing the node pool to scale up, even when the node pool is not the most efficient one. Additionally, unused reservations are always prioritized when balancing multi-zonal scale-ups.
For more information, see how to use cluster autoscaler.
June 01, 2023
Agones on GKE users will get recommendations and insights if they did not install the Agones controller on dedicated nodes.