Budget Control

Tyk AI Studio provides a Budget Control system to help organizations manage and limit spending on Large Language Model (LLM) usage.

Purpose

The primary goals of the Budget Control system are:

• Prevent Overspending: Set hard limits on costs associated with LLM API calls.
• Cost Allocation: Track and enforce spending limits at different granularities (e.g., per organization, per specific LLM configuration).
• Predictability: Provide better predictability for monthly AI operational costs.

Scope & Configuration

Budgets are typically configured by administrators and applied at specific levels:

• Organization Level: A global budget limit for all LLM usage within the organization.
• LLM Configuration Level: A specific budget limit tied to a particular LLM setup (e.g., a dedicated budget for a high-cost gpt-4 configuration).
• (Potentially) Application/User Level: Granular budgets might be assignable to specific applications or teams (depending on implementation specifics).

Configuration Parameters:

• Limit Amount: The maximum monetary value allowed (e.g., $500).
• Currency: The currency the budget is defined in (e.g., USD).
• Time Period: The reset interval for the budget, typically monthly (e.g., resets on the 1st of each month).
• Scope: Which entity the budget applies to (Organization, specific LLM Configuration ID, etc.).

Administrators configure these budgets via the Tyk AI Studio UI or API.

Enforcement

Budget enforcement primarily occurs at the Proxy & API Gateway:

1. Request Received: The Proxy receives a request destined for an LLM.
2. Cost Estimation: Before forwarding the request, the Proxy might estimate the potential maximum cost (or rely on post-request cost calculation).
3. Budget Check: The Proxy checks the current spending against all applicable budgets (e.g., the specific LLM config budget AND the overall organization budget) for the current time period.
4. Allow or Deny:
   • If the current spending plus the estimated/actual cost of the request does not exceed the limit(s), the request is allowed to proceed.
   • If the request would cause a budget limit to be exceeded, the request is blocked, and an error is returned to the caller.

Integration with Other Systems

• Analytics & Monitoring: The Analytics system provides the cost data used to track spending against budgets. The current spent amount for a budget period is derived from aggregated analytics data.
• Model Pricing: The pricing definitions are essential for the Analytics system to calculate costs accurately, which in turn feeds the Budget Control system.
• Notification System: Budgets can be configured to trigger notifications when spending approaches or reaches defined thresholds (e.g., alert admin when 80% of budget is consumed, notify user/admin when budget is exceeded).

Benefits

• Financial Control: Prevents unexpected high bills from LLM usage.
• Resource Management: Ensures fair distribution of AI resources according to allocated budgets.
• Accountability: Tracks spending against specific configurations or organizational units.

Budget Control is a critical feature for organizations looking to adopt AI technologies responsibly and manage their operational costs effectively.