A team runs a production RAG chat application on Azure AI Foundry. Users complain about occasional high response costs. The team suspects that a subset of requests injects excessively large retrieved context into the prompt, inflating input token counts. Before changing any prompts, they want to confirm which requests consume the most input tokens versus output tokens, and correlate that with the specific deployment. Which observability capability should they use to gather this evidence?