The Meter Is Running on Every Request

The cost of using a service multiplies with each request, often unnoticed until it becomes a significant issue. Running a demo may only cost a few pennies, but once the service is live, the expenses become tied to what users do, making them a feature expense rather than an abuse of the system. By treating cost like latency, logging it alongside duration for each request and user, you can better understand who is consuming the most resources.

To control costs, set limits per user, such as hourly or daily caps. Decide in advance what happens when those limits are reached, preventing one user's excessive usage from affecting everyone else. Examine the prompts sent to the service; many are repetitive boilerplate, with unnecessary context added out of uncertainty. Trimming these repetitions reduces costs and improves efficiency. Caching repeated requests is also crucial, as users often ask similar questions in nearly identical wording.

Avoid sending every request to a single model; much traffic is straightforward and inexpensive, while a few complex requests can be costly. Focus on optimizing these high-cost queries. Recognize that cost is a feature property, like response time and error rates, which are only revealed through detailed monitoring and analysis. Like latency, cost management should be a continuous effort, not something discovered only at month-end in a summary report. The service's costs are running now; it's time to review them and act accordingly.