Cost Optimization
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Per-App Bedrock Cost Tracking with Inference Profiles
Application inference profiles put cost allocation tags on Bedrock calls, turning one shared bill into per-team lines. The tag design is the hard part.
Your LLM Bill Is an Observability Problem
A surprising Bedrock bill is not a pricing problem, it is a visibility one. If you cannot attribute tokens to a feature, tenant, or agent, you cannot manage it.
Batch Inference on Bedrock: Half Price If You Can Wait
Amazon Bedrock batch inference runs at 50 percent of on-demand pricing. The only cost is latency. For any job where nobody is waiting, that trade is free money.
Prompt Caching on Bedrock: The 90% Discount Most Teams Ignore
Bedrock prompt caching reads a repeated prefix at 90 percent off, but a cache write costs more than not caching. The breakpoint decides which you get.
Stop Fine-Tuning. You Need RAG, a Cache, and Better Prompts
Fine-tuning plus provisioned throughput is the expensive answer to most LLM problems. The cheaper path is retrieval, prompt caching, and better prompts.