Google Distributed Cloud

Google Distributed Cloud extends Google Cloud infrastructure, services, and Kubernetes to your data centers and edge locations. Depending on your regulatory, latency, and infrastructure requirements, you can deploy Google Distributed Cloud in the following ways:

  • Air-gapped: Fully disconnected hardware and software for complete sovereignty and strict compliance.
  • Connected: Google-managed hardware deployed on site and connected to Google Cloud for unified operations.
  • Software only (on-premises): Enterprise Kubernetes running on your own bare metal servers or existing VMware infrastructure.

Go to the Distributed Cloud portfolio page for more overview information.

免费试用

Google Cloud新用户首次注册即可获得300美元赠金。此外，无论新老用户，均可免费使用20多款产品，积累动手实践经验。

免费试用

Google Cloud新用户首次注册即可获得300美元赠金。此外，无论新老用户，均可免费使用20多款产品，积累动手实践经验。

Air-gapped

Operate sovereign cloud workloads in environments completely disconnected from the public internet and Google Cloud. Distributed Cloud air-gapped provides Google-engineered hardware and software operated entirely within your sovereign perimeter to meet strict regulatory, national security, and data sovereignty mandates. It's available as full data center racks, ruggedized tactical appliances, or local validation sandboxes.
Deploy a fully disconnected hardware and software environment to operate sovereign cloud services under strict regulatory controls.
Run node-scale AI, container, and VM workloads on ruggedized, portable hardware in remote or field locations.
Build and validate applications in a simulated Google Distributed Cloud air-gapped environment without requiring physical hardware.
Build, deploy, and manage machine learning applications and pretrained generative AI models in a secure, fully air-gapped environment.

Connected

Run low-latency container and virtual machine workloads on Google-managed hardware installed in your data center. Distributed Cloud connected lets you bring Google Cloud services and private generative AI models to your local network perimeter without having to manage the underlying physical hardware.
Run latency-sensitive container and VM workloads on Google-managed dedicated hardware deployed on site.
Deploy turnkey Gemini generative AI models securely on private, Google-connected hardware within your network perimeter.

Software only (on-premises)

Deploy enterprise Kubernetes on your existing infrastructure without purchasing dedicated Google hardware. Create, scale, and operate production Kubernetes clusters on your physical bare-metal servers or existing VMware infrastructure.
Deploy and operate enterprise Kubernetes clusters directly on your physical hardware infrastructure with direct control over performance, security, and network latency.
Create, manage, and scale enterprise Kubernetes clusters on your existing VMware infrastructure using Google Cloud features.
Deploy and serve third-party LLMs on Distributed Cloud bare metal using GPUs across multiple nodes.

Pricing and training

Explore hardware subscription tiers and software pricing, or build your team's technical skills with structured learning paths for cloud architects and developers.
Get pricing and hardware subscription details for Google Distributed Cloud offerings.
Study managing container-based applications across multiple clouds, or between on-premises and cloud environments.
Study designing, building, analyzing, and maintaining cloud-native applications.