A GPU Workshop and Cloud Native's Developer Experience Gap
Notes from ContainerDays Singapore 2026.
Blog
In-depth articles and insights on open source, AI, cloud-native, DevOps, and software engineering.
From Cloud Native to AI Native: Reinvent the Wheel?
Cloud native to AI native: reuse or reinvent?
Why We Still Need GPU Partitioning
Bigger models make GPU partitioning matter more.
KubeCon China 2026 Recap
Returning to Shanghai after eight years, I see cloud native becoming the infrastructure foundation for AI.
GPU Scheduling Landscape and mutex Semantics
Why GPU scheduling matters: how the default scheduler misses node, card, and topology placement, how HAMi v2.10 fills the gaps, and what mutex really means on kind.
HAMi-core and KAI Scheduler
GPU sharing is moving from soft allocation to governance—scheduling decisions and runtime isolation can finally be reconciled.
After HAMi's CNCF Incubating: From a Community of Code to a Network of Consensus
Code is cheap; consensus is the new scarce good.
Olares and HAMi: Desktop AI Workstation Inflection
HAMi moves from cluster to desktop with Olares.
Every Nation Begins with Textiles
From Anji bamboo weaving to industrialization
Why GPU Is the Foundation of AI
A GPU explainer for Kubernetes veterans new to AI. Maps token, model, training, inference, Transformer, Tensor Core, HBM, and KV cache to concepts you already know.