HAMi Joins the Vultr Open Source Alliance
The HAMi community is pleased to announce that HAMi has joined the newly launched Vultr Open Source Alliance as one of its six founding members, alongside Spinifex, Upbound, Qdrant, Valkey, and NetBird.
The Alliance was announced on November 10, 2026. It brings together open source projects and infrastructure providers to help organizations deploy and operate open source technologies with the performance, scale, and control of production-grade cloud infrastructure.
Making GPU Infrastructure More Open and Efficient
As AI workloads continue to grow, efficient GPU resource management has become increasingly important for organizations building and operating AI infrastructure.
HAMi, a CNCF Incubating project, addresses this challenge by enabling GPU sharing, resource isolation, and heterogeneous accelerator scheduling in Kubernetes environments.
By allowing multiple workloads to share GPU resources while maintaining resource boundaries, HAMi helps organizations improve utilization and make more efficient use of their computing infrastructure.
Why the Vultr Open Source Alliance Matters
The Vultr Open Source Alliance brings together open source technologies and cloud infrastructure to make enterprise adoption easier.
For HAMi, this creates opportunities to explore how open source GPU resource management can complement cloud GPU infrastructure and Kubernetes environments.
Vultr's Cloud GPU and managed Kubernetes offerings provide a relevant foundation for exploring GPU sharing, workload isolation, and resource optimization for AI applications.
More broadly, the collaboration reflects a shared commitment to open, interoperable, and portable infrastructure that gives developers greater flexibility and control.
Thanks to Vultr for Supporting the HAMi Community
We would like to thank Vultr for its continued support of the HAMi community.
Vultr has provided test environments for the community's release validation. During the HAMi v2.11.0 release, the community was able to validate new capabilities on Vultr's cloud GPU test environments. This kind of support helps the community test on real infrastructure and keeps open source development close to production environments.
Looking Ahead
As a founding member of the Alliance, the HAMi community looks forward to exploring opportunities for technical collaboration, including deployment guidance, reference architectures, and practical resources that help developers evaluate and adopt GPU sharing technologies.
Our goal remains unchanged: to make heterogeneous computing resources more accessible, efficient, and manageable through open source.
We welcome opportunities to collaborate with infrastructure providers, developers, and the broader cloud native community to advance open AI infrastructure.
