AWS demonstrates building a self-service LLM gateway with Bedrock and LiteLLM
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In a technical article, AWS demonstrated a solution for building a self-service LLM gateway: using Amazon Bedrock Application Inference Profiles together with LiteLLM running on AWS Fargate to wrap Amazon Bedrock as an OpenAI-compatible API. According to the article, the result is that users can invoke Bedrock models through an OpenAI-compatible interface, while the underlying layer is still handled by Bedrock's inference configuration. This solution is currently only a build demonstration given in an official AWS blog, and the article does not provide performance or cost data after actual deployment.
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- AWS Machine Learning BlogBuilding a self-service LLM gateway with Amazon Bedrock and LiteLLM
This post describes a pattern for a self-service LLM gateway that runs LiteLLM on AWS Fargate to expose Amazon Bedrock models through an OpenAI-compatible API, using Bedrock Application Inference Profiles for per-model quota isolation and scoped IAM access. It covers configuration of developer tools, LiteLLM model mapping with per-token costs for budget enforcement, CDK constructs for inference profiles, Langfuse observability, CloudWatch TPM alarms, and lessons learned from scaling to several hundred developers.
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