This article was originally published on the CNCF blog on August 7, 2026.
Projects that want to share a GPU on Kubernetes have to work around an API instead of with it. The device plugin interface could count devices, and that was the whole vocabulary: nvidia.com/gpu: 1. It meant one whole card, take it or leave it. HAMi, which the CNCF Technical Oversight Committee (TOC) accepted as an incubating project on July 15, 2026, built its entire pipeline (mutating webhook, scheduler extender, annotations, in-container enforcement) to express what that vocabulary couldn't: "give this pod 8,000 MiB and 10% of a GPU, and make the limit stick."
Then, the vocabulary changed. Dynamic Resource Allocation (DRA) reached general availability in Kubernetes v1.34 and is enabled by default since v1.35. With the consumable capacity feature, a pod can now ask the scheduler itself for a slice of a device's memory, natively, with no annotations involved.
So the question I keep seeing in the HAMi communication channels is: does DRA make HAMi obsolete? The short answer is no, but the complete answer depends on which of HAMi's jobs you're talking about. One of them, encoding fractional requests where the scheduler can see them, is exactly what DRA absorbs. The other, enforcing those fractions inside the container at CUDA-call granularity, is a job DRA was never designed to do. HAMi's response has been to split accordingly: keep the enforcement, and rebuild the encoding on top of DRA across 3 repositories. Let's walk through both halves, then look at what running the DRA stack takes today.
The HAMi community is proud to announce the official release of HAMi v2.9.0. This represents a milestone version in terms of heterogeneous device virtualization depth, scheduler ecosystem expansion, and Kubernetes native standards alignment.
v2.9.0 introduces the Ascend 910C HAMi-core mode, HAMi-DRA general availability, and Volcano vGPU upgrade to v0.19, along with systematic enhancements in observability, security, and stability. This release also welcomes 19 new contributors for the first time.
This article provides a detailed overview of the major updates in v2.9.0.
KCD Beijing 2026 was one of the largest Kubernetes community events in recent years.
Over 1,000 people registered, setting a new record for KCD Beijing.
The HAMi community not only gave a technical talk but also set up a booth, engaging deeply with developers and enterprise users from the cloud-native and AI infrastructure fields.
The topic of this talk was:
From Device Plugin to DRA: GPU Scheduling Paradigm Upgrade and HAMi-DRA Practice
This article combines the on-site presentation and slides for a more complete technical review. Slides download: GitHub - HAMi-DRA KCD Beijing 2026.
The HAMi community is proud to announce the official release of HAMi v2.8.0. This represents a milestone version in terms of architectural completeness, scheduling reliability, and ecosystem alignment.
v2.8.0 not only introduces multiple key feature updates but also delivers systematic enhancements in Kubernetes native standard alignment, heterogeneous device support, production readiness, and observability, making HAMi more suitable for AI production clusters that require long-term operation with high stability and clear evolution paths.
This article provides a detailed overview of the major updates in v2.8.0.
