Case 20
Cost and Token Observability
Cost and Token Observability: Problem: AI and cloud costs can grow quietly when usage is disconnected from teams, services, and deployment changes. Constraints: Token attribution, cloud tags, model pricing, request volume, budget alerts, and developer-readable reports. Architecture: Cost telemetry tied to services, AI gateway requests, deployment events, dashboards, and threshold-based feedback loops. Result: Cost becomes an operational signal teams can understand before it becomes a finance surprise.
- Problem
- AI and cloud costs can grow quietly when usage is disconnected from teams, services, and deployment changes.
- Constraints
- Token attribution, cloud tags, model pricing, request volume, budget alerts, and developer-readable reports.
- Architecture
- Cost telemetry tied to services, AI gateway requests, deployment events, dashboards, and threshold-based feedback loops.
- Result
- Cost becomes an operational signal teams can understand before it becomes a finance surprise.
Related topics: AI infrastructure, Kubernetes/EKS, GitOps, Terraform, observability, platform engineering, cloud architecture.