Nomadic infrastructure design for AI workloads

In a blog post on nomadic compute designs for AI workloads, the author discusses building sustainable systems using simple components for flexibility and cost-efficiency. Objects are stored without egress fees, reducing reliance on provider-specific features that impose vendor lock-in. The post further explores production readiness, cloud dependency strategies, and concepts for orchestrating easily replaceable compute resources.

• AI workloads generate high revenue for cloud companies.
• Egress fees can be costly for data transfer.
• Nomadic compute optimizes cost-effectiveness.
• Using references improves efficiency.
• Efficient orchestration can reduce costs.