HAMi is coming to KubeCon China 2026!
Dynamic MIG, GPU virtualization at scale, and heterogeneous AI infrastructure, see what the HAMi community will be sharing in Shanghai.
https://t.co/TsCYWVd1nr
#HAMi#KubeCon#AIInfra
HAMi v2.10.0 is released.
New features include Flexible MIG, composable scheduling strategies, broader accelerator support, and deeper Kubernetes ecosystem integrations.
Learn more:
https://t.co/Uru8LqQ0CV
#HAMi#Kubernetes#CloudNative#AIInfrastructure
🎂 HAMi turns 5!
Five years ago today, HAMi had its first commit and began an open source journey toward making GPU sharing and heterogeneous computing more efficient.
A huge thank you to all contributors, users, and ecosystem partners who have shaped HAMi along the way.
New HAMi lab: run two KServe Predictor replicas on one NVIDIA GPU with HAMi DRA GPU sharing.
Follow the step-by-step guide:
https://t.co/ZbpFnRo1Zb
#HAMi#KServe#Kubernetes
Want to contribute to open-source GPU infrastructure? HAMi has four projects open for LFX Mentorship 2026 Term 3.
Apply to become a mentee by August 18:
https://t.co/SvXcg6Sbtg
#LFXMentorship#OpenSource
Meet HAMi at KubeCon + CloudNativeCon Japan 2026 in Yokohama, Jul 28–30. Find us at Booth T-6, Project Pavilion (Pacifico Yokohama 3F).
#KubeConJapan#KubeCon#HAMi
Excellent blog on GPU sharing in Kubernetes with @HAMiProject. It clearly explains Time Slicing, MPS, MIG, and how HAMi enables fine-grained GPU sharing for better utilization. Thanks @SaiyamPathak, Shubham Katara, and @kubesimplify.
https://t.co/5dBeqPVbAm
Learn how HAMi GPU slicing works with Kueue quota admission, allowing two vGPU jobs to run while keeping excess workload suspended before scheduler-level Pending.
https://t.co/MZgagnj8eA
#Kubernetes#GPU#Kueue#HAMi
GPUs are expensive. Idle compute is, too.
At vLLM Meetup Shanghai, HAMi author Li Mengxuan shared a practical path from single-node vLLM to PD disaggregation + GPU virtualization.
Recap: https://t.co/fSmLsjLV5x
#vLLM#HAMi
🚀 Are you really using your compute efficiently?
At the latest vLLM Meetup, HAMi co-creator Mengxuan Li shared the 3 stages of optimizing LLM inference clusters and why GPU utilization is only the beginning.
#HAMi#vLLM#LLM#GPU#AIInfrastructure#Kubernetes
HAMi is now a CNCF Incubating Project!
HAMi helps platform teams efficiently share and schedule GPUs and other accelerators on Kubernetes through vendor-neutral GPU virtualization, making AI infrastructure more efficient as workloads scale.
Congratulations to the HAMi team on this milestone! 🚀
Learn more: https://t.co/CC8JvoCC2E
@CloudNativeFdn Thank you, CNCF! We’re proud of this milestone. If anyone want to explore or contribute, feel free to join our Discord: https://t.co/HHnNQ0wKCz
🚀 HAMi is heading to WAIC 2026!
Visit us at Booth H2-B401 to explore how open source is making heterogeneous GPU resource management more efficient for AI infrastructure.
Looking forward to meeting developers, users, and ecosystem partners in Shanghai. #WAIC2026
🎉 The recording of the July 8 #HAMi Community Meeting is now live!
It's also the first video on the new HAMi Community YouTube channel 🚀
📺 https://t.co/TmMtqkv2Gr
Subscribe for future community meetings, demos, and technical updates.
#CNCF#Kubernetes
New lab from the HAMi community is live! 🎉
Explore how @volcano_sh vGPU works with Gang Scheduling and Queues in this hands-on lab.
https://t.co/4TfOo1RPYZ
#HAMi#Kubernetes#GPU