An inference platform on Azure starts with the gateway, not the GPU.
How to choose where models run on Azure, and the shared front door that turns them into a platform: identity, token limits, failover and cost per team.
FIELD NOTES / CLOUD & DEVOPS
Practical delivery workflows and thoughtful platform engineering.
How to choose where models run on Azure, and the shared front door that turns them into a platform: identity, token limits, failover and cost per team.
What a platform team should give AI agents before they reach real tools, and three real incidents that show what happens without it.
Why a Markdown-first, static publishing workflow is a good starting point for a personal engineering blog.