I'm gathering rough numbers for a future finance discussion. As AI-assisted infrastructure management becomes more common, especially through MCP, automation tools, or GitOps workflows, I'm curious what people actually spend. For those using AI to help manage production clusters, roughly how many credits or tokens do you consume per week per cluster?
4 Answers
Our production usage is also effectively zero. We may use an AI coding assistant during an incident or for investigation, but it isn’t connected directly to the cluster or running continuously.
Zero so far. We don’t use AI to manage production clusters, so there’s no recurring token or credit cost.
I’m skeptical that fully AI-managed production clusters are widespread yet. Giving an assistant a service account and unrestricted kubectl access creates significant privilege and safety concerns, so many teams are likely experimenting rather than operating this way at scale.
I use an AI assistant with kubectl occasionally, usually by collecting logs or command output locally and providing that context for analysis. That keeps usage limited and avoids giving the model broad production access, so the weekly cost is difficult to measure but very small.
Even if the tooling can technically perform the operations, the access controls, approval steps, and audit requirements make autonomous production management a much bigger decision than simply estimating token usage.