AI applications depend on constrained services: model providers, embedding APIs, vector databases, browser tools, code execution sandboxes, and third-party business APIs. Each service may enforce request limits, token limits, concurrency limits, daily quotas, spend tiers, or safety throttles. Without a control layer, traffic spikes turn into 429 errors, retries make the spike worse, and cost overruns can look like product growth until the bill arrives.

In this chapter, we build the core pieces of an API management layer for AI workloads: rate limits, priority queues, budgets, upstream throttling, load shedding, and API key hygiene.