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The controls and limits placed on AI resource usage (e.g., API calls, compute time) to enforce governance policies and prevent runaway costs or abuse.
Implements throttling, rate-limiting, and daily or monthly caps on resource consumption per user, team, or application. Quotas protect against denial-of-service, uncontrolled spending, and model-extraction attacks. Governance defines quota policies aligned to SLAs and budgets, monitors usage dashboards, and auto-notifies or blocks users when thresholds are reached, ensuring fair usage and cost predictability.
Real world example:
A research organization sets a monthly GPU-hour quota of 100 hours per project. When a project exceeds 80 hours, an automated notification emails the team lead; at 100 hours, further training jobs are queued until quota increases are approved - preventing unexpected cloud charges and resource contention.
