Modern generative AI applications often need to stream large language model (LLM) outputs to users in real-time. Instead of waiting for a complete response, streaming delivers partial results as they become available, which significantly improves the user experience for chat interfaces and long-running AI tasks. This post compares three serverless approaches to handle Amazon Bedrock LLM streaming on Amazon Web Services (AWS), which helps you choose the best fit for your application.
Amazon SageMaker AI is a fully managed ML service. With SageMaker AI, data scientists and developers can quickly and confidently build, train, and deploy ML models into a production-ready hosted environment. It provides a UI experience for running ML workflows that makes SageMaker AI ML tools available across multiple integrated development environments (IDEs). Within a few steps, you can deploy a model into a secure and scalable environment from the SageMaker AI console.
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