Insights, tutorials, and news from our team
A CNCF case study on how China Merchants Bank built a unified AI compute scheduling platform on Kubernetes and HAMi, enabling heterogeneous resource pooling, topology-aware scheduling, and fine-grained accelerator sharing. Hardware pool utilization reached 100%, cross-machine scheduling dropped 30%, and partitioning granularity went down to 1 GB memory / 1% compute.
On July 2, 2026, HAMi officially graduated to a CNCF Incubating project. Following its acceptance as a Sandbox project in August 2024, this milestone marks HAMi's growth from a promising newcomer into trusted infrastructure widely adopted in real production environments.
KAI Scheduler originates from the core scheduling engine of Run:ai, was open-sourced by NVIDIA, and has entered the CNCF Sandbox. Led by Dynamia, the HAMi-core integration has now landed in the KAI Scheduler mainline, giving its GPU sharing capability hard runtime memory isolation.
After the landmark Keynote Demo at KubeCon EU 2026, the HAMi community is heading to KubeCon India 2026. CNCF Ambassador Saiyam Pathak will deliver a keynote featuring a live GPU sharing demo on NVIDIA DGX Spark.
A community contributor's deep dive into diagnosing and fixing vGPU scheduling delays (from seconds to 10+ minutes) after upgrading a 200-node GPU cluster from Volcano 1.7 to Volcano 1.12 + hami-dp. Root cause analysis of API Server throttling, patch delays, and resource view timeouts.
A hands-on guide covering HAMi, DRA-mode deployment, GPU memory and compute partitioning, native DRA usage, and DevicePlugin-compatible migration.
GPU management in research labs has always been a headache. Boardware spent three years evolving from VM-exclusive access to a Kubernetes + HAMi cloud-native solution, ultimately achieving physical isolation of Agent RL training and inference on a 12-GPU cluster. This is the seventh article in the HAMi Community Meetup Shenzhen recap series.
Sangfor Cloud AI Chief Architect Jia Haojie shares a complete enterprise AI computing governance practice — from the computing challenges of the Agent era to intelligent routing and safety guardrails of the AI Computing Gateway, to Volcano + HAMi production-grade vGPU scheduling.
HAMi v2.9.0 is officially released! Ascend 910C user-space virtualization (HAMi-core mode) delivers fine-grained memory and compute sharing, HAMi-DRA reaches production readiness based on Kubernetes DRA standards, Vastai device support is added, and security and observability are comprehensively enhanced.
Get the latest technical articles, tutorials, and HAMi community updates.