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AI Cost Monitoring Architecture
Architecture for tracking and analyzing AI API usage, token consumption, and cost trends across teams and projects.
Architecture for monitoring and optimizing AI infrastructure costs in production applications.
Key Design Decisions
- Token tracking: Separate service for token tracking enables accurate cost calculation and billing.
- Response caching: Caching identical prompts dramatically reduces costs but requires careful cache key design.
- Rate limiting: Per-user rate limits prevent abuse and control costs, implemented with Redis sliding window.