Production AI Inference Infrastructure: An Evaluation Guide

An endpoint that works in evaluation is not the same as infrastructure that holds in production. As traffic grows, context windows expand, and inference becomes embedded in customer-facing applications, weaknesses in reliability, visibility, cost control, security, and support quickly become more apparent. 

This evaluation guide gives you a practical framework for understanding whether your infrastructure is ready for real-world demand, including the right questions you should bring to vendors and apply to your own stack.

  • Why availability alone does not guarantee reliable performance at production scale
  • What it takes to trace latency, utilization, and cost back to infrastructure behavior
  • How to match execution paths and economics to workload maturity
  • Which security controls matter once inference becomes business-critical
  • Why production support requires more than an SLA
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