Secure and customizable compute service that lets you create and run virtual machines on Google’s infrastructure.
New customers get $300 in free credits to spend on Google Cloud. All customers get a general purpose machine (e2-micro instance) per month for free, not charged against your credits.
Compute Engine interactive tutorial
In this console-based tutorial, we'll show you how easy it is to create a Linux virtual machine in Compute Engine.
Confidential VMs and Compute Engine
Learn more about Confidential VMs in Compute Engine, including support for end-to-end encryption, compute-heavy workloads, and more security and privacy features.
Boot disk images
Learn about the public images that you can use to create your VMs, or learn how to create and import your own custom images to Compute Engine.
Using the Compute Engine API through client libraries
Use client libraries to create and manage Compute Engine resources in Go, Python, Java, Node.js, and other languages.
Create managed instance groups
Managed instance groups maintain high availability of your applications by proactively keeping your VM instances available.
Virtual Private Cloud (VPC) network overview
A VPC network provides connectivity for your Compute Engine VM instances. Configure your VPC network and firewalls to handle network traffic for your applications.
Identity and Access Management (IAM) overview
Use IAM roles and permissions to manage access and permissions to your Compute Engine resources.
Compute Engine resources
Find Compute Engine pricing along with discounts, benchmarks, zonal resources, release notes, and more.
Explore what you can build on Google Cloud
Find out how to migrate and modernize workloads on Google’s global, secure, and reliable infrastructure.
Whether you’re new to cloud computing, or just getting started on Google Cloud, these recommendations can help you optimize your Compute Engine usage and benefits. The table provides machine type recommendations for different workloads.
Compute Engine provides tools to help you bring your existing applications to the cloud. You can have your applications running on Compute Engine within minutes while your data migrates transparently in the background. Bring your existing applications from your physical servers, VMware vSphere, Amazon EC2, or Azure VMs.
Process petabytes of genomic data in seconds with Compute Engine and our high performance computing solution. Our scalable and flexible infrastructure enables research to continue without disruptions. Competitive pricing and discounts help you stay within budget to convert ideas into discoveries, hypotheses into cures, and inspirations into products.
You can run your Windows-based applications either by bringing your own licenses and running them in Compute Engine sole-tenant nodes or using a license-included image. After you migrate to Google Cloud, optimize or modernize your license usage to achieve your business goals. Take advantage of the many benefits available to virtual machine instances such as reliable storage options, the speed of the Google network, and autoscaling.
|Workload Manager||Now available for SAP workloads, Workload Manager evaluates your application workloads by detecting deviations from documented standards and best practices to proactively prevent issues, continuously analyze workloads, and simplify system troubleshooting.|
|VM Manager||VM Manager is a suite of tools that can be used to manage operating systems for large virtual machine (VM) fleets running Windows and Linux on Compute Engine.|
|Batch||Batch is a fully managed batch service, which allows for jobs to be scheduled, queued, autoscaled, and executed on Compute Engine instances.|
|Live migration for VMs||Compute Engine virtual machines can live-migrate between host systems without rebooting, which keeps your applications running even when host systems require maintenance.|
|Confidential VMs||Confidential VMs are a breakthrough technology that allows you to encrypt data in use—while it’s being processed. It is a simple, easy-to-use deployment that doesn't compromise on performance. You can collaborate with anyone, all while preserving the confidentiality of your data.|
|Sole-tenant nodes||Sole-tenant nodes are physical Compute Engine servers dedicated exclusively for your use. Sole-tenant nodes simplify deployment for bring-your-own-license (BYOL) applications. Sole-tenant nodes give you access to the same machine types and VM configuration options as regular compute instances.|
|Custom machine types||Create a virtual machine with a custom machine type that best fits your workloads. By tailoring a custom machine type to your specific needs, you can realize significant savings.|
|Predefined machine types||Compute Engine offers predefined virtual machine configurations for every need from small general purpose instances to large memory-optimized instances with up to 11.5 TB of RAM or fast compute-optimized instances with up to 60 vCPUs.|
|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.|
|Instance groups||An instance group is a collection of virtual machines running a single application. It automatically creates and deletes virtual machines to meet the demand, repairs workload from failures, and runs updates.|
|Persistent disks||Durable, high-performance block storage for your VM instances. Compute Engine offers two forms of persistent disk: Google Cloud Hyperdisk and Persistent Disk. You can create persistent disks in HDD or SSD formats. You can also take snapshots and create new persistent disks from that snapshot. If a VM instance is terminated, its persistent disk retains data and can be attached to another instance.|
|Local SSD||Compute Engine 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.|
|GPU accelerators||GPUs can be added to accelerate computationally intensive workloads like machine learning, simulation, and virtual workstation applications. Add or remove GPUs to a VM when your workload changes and pay for GPU resources only while you are using them.|
|TPU Accelerators||Cloud TPUs can be added to accelerate machine learning and artificial intelligence applications. Cloud TPUs can be reserved, used on-demand or available as preemptible VMs.|
|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||Run your choice of OS, including Debian, CentOS Stream, Fedora CoreOS, SUSE, Ubuntu, Red Hat Enterprise Linux, FreeBSD, or Windows Server 2008 R2, 2012 R2, and 2016. You can also use a shared image from the Google Cloud community or bring your own.|
|Per-second billing||Google bills in second-level increments. You pay only for the compute time that you use.|
|Commitment savings||With committed-use discounts, you can save up to 57% with no up-front costs or instance-type lock-in.|
|Container support||Run, manage, and orchestrate Docker containers on Compute Engine VMs with Google Kubernetes Engine.|
|Reservations||Create reservations for VM instances in a specific zone. Use reservations to ensure that your project has resources for future increases in demand. When you no longer need a reservation, delete the reservation to stop incurring charges for it.|
|Right-sizing recommendations||Compute Engine provides machine type recommendations to help you optimize the resource utilization of your virtual machine (VM) instances. Use these recommendations to resize your instance’s machine type to more efficiently use the instance’s resources.|
|Placement Policy||Use Placement Policy to specify the location of your underlying hardware instances. Spread Placement Policy provides higher reliability by placing instances on distinct hardware, reducing the impact of underlying hardware failures. Compact Placement Policy provides lower latency between nodes by placing instances close together within the same network infrastructure.|