Category: HAQM Bedrock Guardrails

As we continue our five-part series on optimizing costs for generative AI workloads on AWS, our third blog shifts our focus to HAQM Bedrock. In our previous posts, we explored general Cloud Financial Management principles on generative AI adoption and strategies for custom model development using HAQM EC2 and HAQM SageMaker AI. Today, we’ll guide you through cost optimization techniques for HAQM Bedrock, AWS’s fully managed service that provides access to leading foundation models. We’ll explore making informed decisions about pricing options, model selection, knowledge base optimization, prompt caching, and automated reasoning. Whether you’re just starting with foundation models or looking to optimize your existing HAQM Bedrock implementation, these techniques will help you balance capability and cost while leveraging the convenience of managed AI models.