Google Kubernetes Engine (GKE)

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

Use fleets to organize clusters and workloads, and assign resources to multiple teams easily to improve velocity and delegate ownership. Team scopes let you define subsets of fleet resources on a per-team basis, with each scope associated with one or more fleet member clusters.

You might choose multiple clusters to separate services across environments, tiers, locales, teams, or infrastructure providers. Fleets and the Google Cloud components and features that support them strive to make managing multiple clusters as easy as possible.

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

GKE runs Certified Kubernetes, enabling workload portability to other Kubernetes platforms across clouds and on-premises. You can also run your apps anywhere with consistency using GKE on Google Cloud, GKE on AWS, or GKE on Azure.

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

Manage, observe, and secure your services with Google’s implementation of the powerful Istio open source project. Simplify traffic management and monitoring with a fully managed service mesh.

Create and enforce consistent configurations and security policies across clusters, fleets, and teams with managed GitOps config deployment.

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

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

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

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

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

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

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

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

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

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

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

GKE supports the common Docker container format.

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

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

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

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.

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.

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.

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 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.

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

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

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 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.

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

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