Effectively use prompt caching on Amazon Bedrock
Machine Learning Blog
The article discusses the new prompt caching feature on Amazon Bedrock, which helps reduce response latency and costs for generative AI applications by caching frequently used prompt contexts.
- Prompt caching can reduce latency up to 85% and costs up to 90%
- Works by caching specific portions of prompts across multiple API calls
- Best suited for workloads with long, repetitive context like document Q&A, coding assistants, and agentic workflows
- Requires careful prompt structuring with static and dynamic content
- Available for select Anthropic Claude and Nova models
The feature allows developers to optimize AI application performance by strategically caching prompt prefixes, with CloudWatch metrics providing insights into cache performance and potential cost savings.
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