Compute
Documentation and resources for running your workloads on virtual machines for ML, high-performance computing, and more.
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Learn about the six deployment archetypes, including the use cases and design considerations for each deployment archetype.
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Recommendations to help you plan and provision resources to match the requirements and consumption patterns of your cloud workloads.
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Recommendations to optimize the performance of workloads in Google Cloud.
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Study cloud computing, ways to use Google Cloud, and different compute options.
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Learn about the wide range of options for hosting applications on Google Cloud.
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Virtual machines
Create a VM.
Configure and deploy scalable, high-performance virtual machine (VM) instances and instance groups.
Get visibility into your project's use of virtual machine (VM) instance resources.
Compute Engine resources are hosted in multiple locations worldwide. These locations are composed of regions and zones.
Images
OS images for virtual machines.
Use operating system (OS) images to create boot disks for your virtual machine (VM) instances.
Learn general operating system (OS) details and feature support for the OS images that are available on Compute Engine.
Bring up your Docker containers on Google Cloud quickly, efficiently, and securely.
Deploy VM images that are optimized for data science and ML tasks.
Block storage
Expand this section to see relevant products and documentation.
Provide always-encrypted solid-state storage for Compute Engine VMs.
Use durable network storage devices that your virtual machine (VM) instances can access like physical disks in a desktop or a server.
Use scalable, high-performance storage service with a comprehensive suite of data persistence and management capabilities.
Migration
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Unified platform that helps you accelerate your end-to-end cloud journey from your current on-premises or cloud environments to Google Cloud.
Migrate servers and VMs from on-premises or another cloud to Compute Engine.
Migrate VMs from on-premises or other clouds directly into containers in GKE.
Assess your mainframe workloads and generate codebase documentation with generative AI.
Move your mainframe data to Google Cloud.
Simultaneously run workloads on your mainframe and on Google Cloud, and compare their outputs.
Workloads
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A supercomputer architecture that employs systems-level codesign to boost efficiency and productivity across AI training, tuning, and serving.
Schedule, queue, and execute batch jobs at scale with a fully managed batch service on Google Cloud.
Add GPUs to your workloads for machine learning, scientific computing, and 3D visualization.
Learn the machine families, machine series, and machine types that you can choose from to create a virtual machine (VM) instance.
Migrate and run your VMware workloads natively on Google Cloud.
Leverage your SAP data in innovative ways, all while running your SAP applications more reliably, securely, and cost-effectively.
End-to-end solutions to manage your SAP and Microsoft SQL Server workloads running on Google Cloud.
Deploy high performance computing (HPC) environments on Google Cloud.
Learn how to manage the network your VMs belong to.
Set up permissions uses IAM roles to control access to your VMs.
Store objects with global edge caching.
VMs on Google Cloud hardened by a set of security controls that help defend against rootkits and bootkits.
A type of virtual machine that enables enhanced performance and security for high-memory workloads using AMD Secure Encrypted Virtualization (SEV).
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2025年10月24日 UTC.
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