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GKE icon Google Kubernetes Engine (GKE)

A scalable and automated Kubernetes service

GKE is a simple way to automatically deploy, scale, and manage Kubernetes.
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New customers can use $300 in free credits to try out GKE.

Features

Automatic provisioning and management

GKE's Autopilot mode is a hands-off, fully managed solution that manages your entire cluster’s infrastructure and requires no configuring and monitoring—while still delivering a complete Kubernetes experience. And with per-pod billing, Autopilot ensures you pay only for your running pods, not system components, operating system overhead, or unallocated capacity. 
GKE autopilot in text over plane icon

VIDEO

Introducing GKE Autopilot: Managed K8s, fully automated and highly optimized

06:36

Pod and cluster autoscaling

GKE implements full Kubernetes API, 4-way autoscaling, release channels, multi-cluster support, and scales up to 15000 nodes. Horizontal pod autoscaling can be based on CPU utilization or custom metrics. Cluster autoscaling works on a per-node-pool basis and vertical pod autoscaling continuously analyzes the CPU and memory usage of pods, automatically adjusting CPU and memory requests.
Developer advocate explaining autoscaling for GKE

VIDEO

Autoscaling with GKE: Clusters and nodes

09:00

Prebuilt Kubernetes applications & templates

Get access to enterprise-ready containerized solutions with prebuilt deployment templates, featuring portability, simplified licensing, and consolidated billing. These are not just container images, but open source, Google-built, and commercial applications that increase developer productivity. Click to deploy on-premises or in third-party clouds from Google Cloud Marketplace.
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Browse 100+ click-to-deploy and third party services for GKE

Container-native networking and security

Privately networked clusters in GKE can be restricted to a private endpoint or a public endpoint that only certain address ranges can access. GKE Sandbox for the Standard mode of operation provides a second layer of defense between containerized workloads on GKE for enhanced workload security. GKE clusters inherently support Kubernetes Network Policy to restrict traffic with pod-level firewall rules.
Explore GKE’s robust security configurations

Automated tools for easily migrating workloads

Migrate to Containers makes it fast and easy to modernize traditional applications away from virtual machines and into containers. Our unique automated approach extracts critical application elements from the VM so you can easily insert those elements into containers in GKE or Anthos clusters without the VM layers (like Guest OS) that become unnecessary with containers. This product also works with GKE Autopilot.
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Watch the webinar on migrating Windows Workloads with GKE

Backup for GKE

Backup for GKE is an easy way for customers running stateful workloads on GKE to protect, manage, and restore their containerized applications and data.

Identity and access management

Control access in the cluster with your Google accounts and role permissions.

Hybrid networking

Reserve an IP address range for your cluster, allowing your cluster IPs to coexist with private network IPs via Google Cloud VPN.

Security and compliance

GKE is backed by a Google security team of over 750 experts and is both HIPAA and PCI DSS compliant.

Integrated logging and monitoring

Enable Cloud Logging and Cloud Monitoring with simple checkbox configurations, making it easy to gain insight into how your application is running.

Cluster options

Choose clusters tailored to the availability, version stability, isolation, and pod traffic requirements of your workloads.

Auto scale

Automatically scale your application deployment up and down based on resource utilization (CPU, memory).

Auto upgrade

Automatically keep your cluster up to date with the latest release version of Kubernetes.

Auto repair

When auto repair is enabled, if a node fails a health check, GKE initiates a repair process for that node.

Resource limits

Kubernetes allows you to specify how much CPU and memory (RAM) each container needs, which is used to better organize workloads within your cluster.

Container isolation

Use GKE Sandbox for a second layer of defense between containerized workloads on GKE for enhanced workload security.

Stateful application support

GKE isn't just for 12-factor apps. You can attach persistent storage to containers, and even host complete databases.

Docker image support

GKE supports the common Docker container format.

OS built for containers

GKE runs on Container-Optimized OS, a hardened OS built and managed by Google.

Private container registry

Integrating with Google Container Registry makes it easy to store and access your private Docker images.

Fast consistent builds

Use Cloud Build to reliably deploy your containers on GKE without needing to setup authentication.

Workload portability, on-premises and cloud

GKE runs Certified Kubernetes, enabling workload portability to other Kubernetes platforms across clouds and on-premises.

GPU and TPU support

GKE supports GPUs and TPUs and makes it easy to run ML, GPGPU, HPC, and other workloads that benefit from specialized hardware accelerators.

Built-in dashboard

Google Cloud console offers useful dashboards for your project's clusters and their resources. You can use these dashboards to view, inspect, manage, and delete resources in your clusters.

Spot VMs

Affordable compute instances suitable for batch jobs and fault-tolerant workloads. Spot VMs provide significant savings of up to 91% while still getting the same performance and capabilities as regular VMs.

Persistent disks support

Durable, high-performance block storage for container instances. Data is stored redundantly for integrity, flexibility to resize storage without interruption, and automatic encryption. You can create persistent disks in HDD or SSD formats. You can also take snapshots of your persistent disk and create new persistent disks from that snapshot.

Local SSD support

GKE offers always-encrypted local solid-state drive (SSD) block storage. Local SSDs are physically attached to the server that hosts the virtual machine instance for very high input/output operations per second (IOPS) and very low latency compared to persistent disks.

Global load balancing

Global load-balancing technology helps you distribute incoming requests across pools of instances across multiple regions, so you can achieve maximum performance, throughput, and availability at low cost.

Linux and Windows support

Fully supported for both Linux and Windows workloads, GKE can run both Windows Server and Linux nodes.

Hybrid and multi-cloud support

Take advantage of Kubernetes and cloud technology in your own data center. Get the GKE experience with quick, managed, and simple installs as well as upgrades validated by Google through Anthos.

Serverless containers

Run stateless serverless containers abstracting away all infrastructure management and automatically scale them with Cloud Run.

Usage metering

Fine-grained visibility to your Kubernetes clusters. See your GKE clusters' resource usage broken down by namespaces and labels, and attribute it to meaningful entities.

Release channels

Release channels provide more control over which automatic updates a given cluster receives, based on the stability requirements of the cluster and its workloads. You can choose rapid, regular, or stable. Each has a different release cadence and targets different types of workloads.

Software supply chain security

Verify, enforce, and improve security of infrastructure components and packages used for container images with Container Analysis.

Per-second billing

Google bills in second-level increments. You pay only for the compute time that you use.

How It Works

When using GKE, Kubernetes apps run on a cluster, which is made up of at least one control plane and machines called nodes. Nodes run the services supporting the containers that make up your workloads. The control plane then decides what runs on those nodes, including scheduling and scaling.
View documentation
GKE technical diagram

Google Kubernetes Engine in a minute (1:21)

Common Uses

Continuous integration and delivery

Migrate workloads

Deploying and running applications

Pricing

How GKE pricing works

After free credits are used, total cost is based on cluster operation mode, cluster management fees, and applicable multi-cluster ingress fees.

Free tier

The GKE free tier provides $74.40 in monthly credits per billing account that are applied to zonal and Autopilot clusters.

Free

Cluster operation mode

Standard mode

Uses Compute Engine nodes in the cluster. You are billed for each instance according to Compute Engine's pricing.

$0.10

per cluster per hour

Autopilot mode

A flat fee per cluster, plus the CPU, memory, and compute resources that are provisioned for your Pods.

$0.10

per cluster per hour

Cluster management fees

The cluster management fee applies to all GKE clusters irrespective of the mode of operation, cluster size or topology. 

$0.10

per cluster per hour

Multi-cluster ingress pricing

Standalone

Multi-cluster ingress standalone pricing is based on the number of Pods considered Multi Cluster Ingress backends.

$3.00

per backend Pod per month (730 hours)

Anthos

Multi-cluster ingress is included as part of Anthos for no additional charge. 

Free

for Anthos users

How GKE pricing works After free credits are used, total cost is based on cluster operation mode, cluster management fees, and applicable multi-cluster ingress fees.
Service Description Price (USD)
Free tier

The GKE free tier provides $74.40 in monthly credits per billing account that are applied to zonal and Autopilot clusters.

Free
Cluster operation mode

Standard mode

Uses Compute Engine nodes in the cluster. You are billed for each instance according to Compute Engine's pricing.

$0.10

per cluster per hour

Autopilot mode

A flat fee per cluster, plus the CPU, memory, and compute resources that are provisioned for your Pods.

$0.10

per cluster per hour
Cluster management fees

The cluster management fee applies to all GKE clusters irrespective of the mode of operation, cluster size or topology. 

$0.10

per cluster per hour
Multi-cluster ingress pricing

Standalone

Multi-cluster ingress standalone pricing is based on the number of Pods considered Multi Cluster Ingress backends.

$3.00

per backend Pod per month (730 hours)

Anthos

Multi-cluster ingress is included as part of Anthos for no additional charge. 

Free

for Anthos users

Learn more about GKE pricing. View all pricing details

Pricing calculator

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