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.
GPU
From GPU utilization to productive GPU-hours.
From GPU to Token: The 8-Layer Observability Stack for AI Infrastructure
From GPU hardware, Kubernetes scheduling, inference engines to token cost — understanding the 8-layer observability architecture for modern AI infrastructure.
Token Is More Than a Billing Unit, It's Becoming the Resource Unit of the AI Era
The Linux Foundation’s Tokenomics Foundation signals a shift: tokens are becoming a core resource in the AI era, much like CPUs in the cloud era.
KubeCon EU 2026 Day One Observations
KubeCon Europe 2026 Day One: How Kubernetes is adapting to the AI infrastructure wave and the evolution of the GPU resource layer.
From Spatial Data to AI Open Source: Technical Standards, Data Sovereignty, and the Global Divide
How technical standards and data sovereignty shape AI open source paths and infrastructure competition in the global AI era.
Joining Dynamia: Embarking on a New Journey in AI Native Infrastructure
Joining Dynamia as Open Source Ecosystem VP to drive AI-native infrastructure ecosystem development, transforming compute from hardware consumption to core asset.
2025 Year in Review: How AI Is Shifting the Focus of Software Engineering
In 2025, software engineering shifts from code-centric to runtime and cost governance. AI and Agents move complexity to runtime, compute, and budget layers, reshaping engineering value.