The architecture utilizes LiteLLM to serve models like Claude Sonnet and Claude Haiku to tools such as Claude Code, Continue, and Cursor through a unified base URL. Traffic routes through Amazon Route 53, Amazon CloudFront, and an Application Load Balancer to ensure robust delivery. Amazon RDS PostgreSQL tracks spend state and virtual keys, while Amazon ElastiCache for Valkey handles caching and rate-limiting. A built-in portal also integrates with corporate single sign-on so developers can generate bounded API keys independently.
Key points
The proxy pattern isolates underlying infrastructure details while exposing foundation mo…: The proxy pattern isolates underlying infrastructure details while exposing foundation models under centralized organizational control.
Platform and finance teams can manage per-user quotas, track latencies, and enforce cost…: Platform and finance teams can manage per-user quotas, track latencies, and enforce cost guardrails automatically.
Self-service portals integrated with corporate single sign-on empower developers to gener…: Self-service portals integrated with corporate single sign-on empower developers to generate keys within administrative spend limits.
Sources checked by our analysis pipeline: 1
Artificial Intelligence
Building a self-service LLM gateway with Amazon Bedrock and LiteLLM
Developers want AI coding assistants with minimal setup. With a large language model (LLM) gateway and LiteLLM, they can quickly access foundation models (FMs) available on Amazon Bedrock while you gain visibility and usage control. Platform teams need to monitor latency and errors, finance teams need to attribute inference costs to teams and projects, and security teams need consistent access controls. An LLM gateway can help address these needs by providing a centrally managed access point to the models that power coding assistants.
In this post, we show how to build a self-service LLM gateway using Amazon Bedrock Application Inference Profiles with LiteLLM running on AWS Fargate to abstract Amazon Bedrock behind an OpenAI-compatible API. With this pattern, developers can access foundation models through a single API with a dedicated key while you gain per-user cost controls and model performance observability. By the end, you will understand the pattern well enough to build your own version from the illustrative snippets and AWS Cloud Development Kit (AWS CDK) constructs.…
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