Architecting AI Infrastructure
A practical series on GPU consumption models, vSphere and VCF placement decisions, and efficiency trade-offs for production AI platforms.
This series explains how AI infrastructure behaves under real constraints: GPU non-fungibility, placement decisions, and practical sizing trade-offs.
Browse all parts below.
All parts
- Why GPU Placement Becomes the Defining Problem
(Part 1)Feb 9, 2026
- GPU Consumption Models as the First Architectural Choice in Production AI
(Part 2)Feb 11, 2026
- How vSphere DRS Makes GPU Placement Decisions
(Part 3)Feb 13, 2026
- How vSphere GPU Modes and Assignment Policies Determine Host Level Placement
(Part 4)Feb 17, 2026
- How Same Size vGPU Mode and Right-sizing Shape GPU Placement Efficiency
(Part 5)Feb 19, 2026
- Mixed Size vGPU Mode in Practice
(Part 6)Feb 24, 2026
- Same Size vs Mixed Size Placement at Cluster Scale
(Part 7)Mar 1, 2026
- MIG Partitioning, Placement Geometry, and Stranded Capacity
(Part 8)Mar 6, 2026