Latest / The Cloud Business Podcast with Fexingo: AWS, Azure, GCP, and Enterprise Infrastructure
The True Cost of Cloud AI Inference Lock-in
Lucas and Luna explore the hidden costs of running large language model inference on a single cloud. They break down a real enterprise case where a company spent $1.3 million in unexpected egress fees moving training data out of AWS, then faced a 40% markup on GPU compute because they couldn't easily switch to Azure. The episode examines why inference workloads create deeper lock-in than storage or compute ever did, and how the cloud giants are pricing GPU time to penalize portability. Lucas explains the 'inference anchor'—a term he borrows from a hyperscaler pricing…
The skinny
The skinny isn't ready yet — notes appear once the transcript is processed.