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Google Kubernetes Engine (GKE)
Start free
Overview
Guides
Reference
Samples
Resources
Documentation
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Overview
Guides
Reference
Samples
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Discover
Product overview
Explore GKE documentation
Overview
Main GKE documentation
GKE AI/ML documentation
GKE networking documentation
GKE security documentation
GKE fleet management documentation
Try it
Create a cluster in the console
Explore your cluster
Fine-tune GKE services with Gemini assistance
Learn fundamentals
Start learning about GKE
Learn Kubernetes fundamentals
Start learning about Kubernetes
Introducing containers
Kubernetes comic
Kubernetes.io
Video playlist: Learn Kubernetes with Google
Learn GKE essentials
Video playlist: GKE Essentials
Common GKE user roles and tasks
Get started
Cluster lifecycle
Cluster administration overview
Cluster configuration
Deploying workloads
GKE cluster architecture
Workflows and tools
gcloud CLI overview
GKE in the Google Cloud console
Provision GKE resources with Terraform
Install kubectl and configure cluster access
Use the GKE remote MCP server
Learning path: Containerize your app
Overview
Understand the monolith
Modularize the monolith
Prepare for containerization
Containerize the modular app
Deploy the app to a cluster
Learning path: Scalable apps
Overview
Create a cluster
Monitor with Prometheus
Scale workloads
Simulate failure
Centralize changes
Production considerations
Design and plan
Code samples
Best practices for GKE
Set up GKE clusters
Plan clusters for running your workloads
Compare features in GKE Autopilot and Standard
About regional clusters
About feature gates
About machine support with GKE clusters
Design your GKE cluster with Gemini
Design for resource obtainability with Gemini
Set up Autopilot clusters
About GKE Autopilot
Create Autopilot clusters
Extend the run time of Autopilot Pods
Prepare to use clusters
Use labels to organize clusters
Manage GKE resources using Tags
Set up clusters for multi-tenancy
About cluster multi-tenancy
Plan a multi-tenant environment
Set up multi-tenant logging
Enhance scalability for clusters
Plan for scalability
Plan for large GKE clusters
About capacity buffers
Configure capacity buffers
Provision extra compute capacity for rapid Pod scaling
Consume reserved zonal resources
About quicker workload startup with fast-starting nodes
Reduce and optimize costs
Design and configure GKE clusters for cost optimization
Configure autoscaling for workloads
Scaling deployed applications
Autoscale workloads horizontally
About horizontal Pod autoscaling
Collect horizontal Pod autoscaler event logs
Autoscale Pods by using custom or external metrics
Scale to and from zero using HPA
Scale to zero using KEDA
Autoscale workloads vertically
About vertical Pod autoscaling
Scale container resource requests and limits
Collect vertical Pod autoscaler event logs
Accelerate application startup using CPU startup boost
Configure autoscaling for infrastructure
Configure granular resource limits
View GKE costs
View cost-related optimization metrics
Provision storage
About storage for GKE clusters
Use Kubernetes features, primitives, and abstractions for storage
Use StatefulSets
About volume snapshots
Use volume expansion
Populate volumes with data from Cloud Storage
About the GKE Volume Populator
Automate data transfer to Hyperdisk ML
Block storage
Provision and use Persistent Disks
Using the Compute Engine Persistent Disk CSI driver
Persistent volume attach limits
Using pre-existing persistent disks
Using persistent disks with multiple readers (ReadOnlyMany)
Provision and use Hyperdisk
About Hyperdisk
Scale your storage performance using Hyperdisk
Optimize storage performance and cost with Hyperdisk Storage Pools
Accelerate AI/ML data loading using Hyperdisk ML
Provision and use GKE Data Cache
Accelerate read performance of stateful workloads with GKE Data Cache
Manage your persistent storage
Clone persistent disks
Back up and restore Persistent Disk storage using volume snapshots
Optimize disk performance
About optimizing disk performance
Monitor disk performance
Local SSD and ephemeral storage
Create a Deployment using an EmptyDir Volume
File storage
Provision and use Lustre volumes
About Managed Lustre for GKE
Create and use a volume backed by Managed Lustre
Access existing Managed Lustre instances
Expand Managed Lustre volumes
Provision Managed Lustre on GKE using Cluster Toolkit
Provision and use Filestore
Access Filestore instances
Back up and restore Filestore storage using volume snapshots
Object storage
Quickstart: Cloud Storage FUSE CSI driver for GKE
About the Cloud Storage FUSE CSI driver for GKE
Set up the Cloud Storage FUSE CSI driver
Mount Cloud Storage buckets as ephemeral volumes
Mount Cloud Storage buckets as persistent volumes
Configure the Cloud Storage FUSE CSI driver sidecar container
Optimize Cloud Storage FUSE performance
Automate performance tuning with performance profiles
Manual performance tuning
Deploy and manage workloads
Deploy Autopilot workloads
Plan resource requests for Autopilot workloads
About Autopilot workloads in GKE Standard
Run Autopilot workloads in Standard clusters
Configure node attributes with ComputeClasses
About GKE ComputeClasses
About built-in ComputeClasses in GKE
About custom ComputeClasses
Control autoscaled node attributes with custom ComputeClasses
Apply ComputeClasses to Pods by default
About Balanced and Scale-Out ComputeClasses in Autopilot clusters
Choose predefined ComputeClasses for Autopilot Pods
Best practices for ComputeClasses
Deploy workloads on optimized hardware
Minimum CPU platforms for compute-intensive workloads
Configure Pod bursting in GKE
Analyze CPU performance using the PMU
Run high performance computing (HPC) workloads with H4D
Best practices for running HPC workloads
Deploy workloads that have special security requirements
About privileged workload admission in Autopilot mode
Create allowlists for privileged workloads in Autopilot mode
GKE Autopilot partners
Privileged open source workloads in Autopilot mode
Restrict privileged Autopilot workloads in organizations
Control privileged workload admission in Autopilot mode
Troubleshoot privileged Autopilot workloads and allowlists
Deploy workloads that require specialized devices
About dynamic resource allocation (DRA) in GKE
Prepare your GKE infrastructure for DRA
Deploy DRA workloads
Snapshot and restore workloads with Pod snapshots
About Pod snapshots
Prepare for Pod snapshots
Trigger a Pod snapshot
Restore a workload from a Pod snapshot
Troubleshoot Pod snapshots
Migrate workloads
Manage workloads
Isolate your workloads using namespaces
Continuous integration and delivery
Plan for continuous integration and delivery
Deploy workloads by application types
AI/ML workloads
AI/ML orchestration on GKE
About GKE Hypercluster
Databases, caches, and data streaming workloads
Data on GKE
Plan your database deployments on GKE
Web servers and applications
Ensure workloads are disruption-ready
Deploy a stateless app
Allow direct connections to Autopilot Pods using hostPort
Run Django
Manage and optimize clusters
Manage cluster lifecycle changes to minimize disruption
Optimize your usage of GKE with insights and recommendations
Manage a GKE cluster
Optimize workload performance
Upgrade clusters and node pools
About GKE cluster upgrades
Plan for cluster upgrades
About release channels
Use release channels
About Autopilot cluster upgrades
Auto-upgrade nodes
Manually upgrade a cluster's control plane or node pools
About node upgrade strategies
About maintenance windows and exclusions
Configure maintenance windows and exclusions
About rollout sequencing with custom stages
Sequence the rollout of cluster upgrades with custom stages
About cluster upgrades with rollout sequencing
Sequence the rollout of cluster upgrades
Control the frequency of disruption from auto-upgrades
Get notifications for cluster events
About cluster notifications
Receive cluster notifications through Pub/Sub
Configure cluster to receive email notifications
