Category: Generative AI

AWS is committed to empowering the FinOps community with the knowledge, tools, and best practices needed to excel in cloud financial management. Our dedication to the FinOps community goes beyond providing world-class cloud services—we’re invested in your professional growth and success. Through our comprehensive digital training portfolio, we aim to equip FinOps professionals with the expertise needed to drive meaningful cost optimization, establish effective governance frameworks, and demonstrate clear business value from cloud investments. Today, we’re excited to share updates to our Cloud Financial Management training courses and introduce a specialized new course designed specifically for the growing demands of generative AI cost management.

As we continue our five-part series on optimizing costs for generative AI workloads on AWS, our third blog shifts our focus to Amazon Bedrock. In our previous posts, we explored general Cloud Financial Management principles on generative AI adoption and strategies for custom model development using Amazon EC2 and Amazon SageMaker AI. Today, we’ll guide you through cost optimization techniques for Amazon 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 Amazon Bedrock implementation, these techniques will help you balance capability and cost while leveraging the convenience of managed AI models.