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Fallstudie | Building Flexible GPU Clouds with HAMi at DaoCloud

Discover how DaoCloud operates two major cloud native platforms for AI workloads—D.run Compute Cloud and DaoCloud Enterprise—using HAMi to achieve >80% GPU utilization across 10,000+ GPUs spanning 10+ data centers.

10,000+
GPUs across platforms
>80%
average GPU utilization
20-30%
reduction in operating costs

Unternehmensuebersicht

DaoCloud operates two major cloud native platforms for AI workloads. D.run Compute Cloud is a public GPU cloud serving individual developers and small teams, while DaoCloud Enterprise (DCE) is a private Kubernetes platform for enterprise customers running both training and inference.

Two major cloud native platforms

D.run Compute Cloud for public GPU cloud

DaoCloud Enterprise (DCE) for private K8s

10+ data centers across China and Hong Kong

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DaoCloud

Cloud-native Plattformanbieter fuer KI-Workloads

Challenges in GPU Resource Management

As GPU demand grew rapidly across both platforms, several challenges emerged that required a flexible GPU virtualization solution.

Whole-card Allocation

Many inference workloads used only a fraction of GPU resources, leaving significant capacity underutilized

Heterogeneous Hardware

Need to support mainstream NVIDIA GPUs while integrating domestic accelerators from multiple vendors

Multi-tenant Governance

Enterprise customers wanted shared GPU pools with department-level quotas and clear isolation

Cloud Native Alignment

GPU sharing solution had to stay fully cloud native, vendor-agnostic, and compatible with CNCF tooling

HAMi as the Unified GPU Layer

DaoCloud adopted HAMi, a CNCF Sandbox project, for heterogeneous AI computing virtualization, as the unified GPU layer across both D.run and DCE. HAMi provides device virtualization, vGPU partitioning, and scheduling for heterogeneous accelerators in Kubernetes clusters.

D.run Compute Cloud: vGPU-SKUs fuer oeffentliche GPU-Nutzer

Auf D.run integrierte DaoCloud HAMi in jeden regionalen Kubernetes-Cluster.

vGPU Slicing

Physical GPUs partitioned into multiple vGPU slices with defined compute and memory

SKU-based Marketplace

vGPU slices exposed as standardized SKUs in a central marketplace

Multi-region Deployment

7 active regions across Mainland China and Hong Kong, over 10 data centers

Domestic Accelerator Support

Extended HAMi to support domestic GPU vendors under unified abstraction

DaoCloud Enterprise (DCE): Gemeinsamer GPU-Pool fuer Unternehmen

Auf DCE baute DaoCloud einen zentralisierten GPU-Ressourcenpool mit HAMi auf.

Unified GPU Pool

Enterprise users contribute and consume GPUs from central pool

Quotas & RBAC

vGPU resources integrated with existing quota and access systems

Simplified Experience

AI engineers request resources without worrying about hardware differences

Gemeinsame Entwicklung von HAMi mit der Community

DaoCloud ist einer der fruehesten und aktivsten Mitwirkenden von HAMi.

Contributed real-world insights from D.run and DCE back to the open-source community

Collaborated upstream to improve GPU over-subscription mechanisms and node configuration

Helped maintain documentation and deployment guides for production adoption

Significant Results: Cost Reduction and Improved Efficiency

By integrating HAMi, DaoCloud consolidated previously fragmented GPU resources into a more unified, efficient, and scalable GPU layer across both public and private clouds.

GPU Utilization

>80%

Average utilization per card after HAMi deployment

Cost Reduction

20-30%

Reduction in GPU-related operating costs

Unified Abstraction

Single Layer

Across NVIDIA and domestic GPUs

Deployment Scale

10,000+ GPUs

Across 10+ data centers

Multi-region

7 Regions

Active D.run regions across China

Open Collaboration

Active

Contributing improvements upstream

HAMi is more than compatible with DaoCloud's business, it's something we've built together. As one of HAMi's earliest contributors, we've witnessed its evolution from inception to maturity. HAMi now runs across both D.run and DCE, and our real-world improvements continuously flow back to the community. HAMi and DaoCloud share the same open-source DNA, and we'll continue contributing to HAMi to bring true vGPU technology to the world.
Captain, AI/LLM Infra Product Lead, DaoCloud

Open-Source Partnership Success

DaoCloud has successfully integrated HAMi across both its public and private GPU cloud platforms, achieving dramatic improvements in utilization and cost efficiency while contributing back to the open-source community.