Building a Self-Service LLM Gateway with Amazon Bedrock and LiteLLM

At a glance

This guide shows how to build a single entry point that lets developers use several AI models on Amazon Bedrock for coding tools. It is called an LLM gateway, a central server that manages access to multiple AI models. Developers connect with their own keys, while operators manage usage and costs.

Key points

1. 1

   LiteLLM, a proxy program that lets several AI models be called in the same way, runs on AWS Fargate, a service that runs containers without server management.

2. 2

   Developers create their own API keys (access credentials) in a web portal, and operators set the spending limits within which they can work.

3. 3

   Each model gets its own inference profile, a set of usage and quota settings, so usage can be tracked and controlled per model.

4. 4

   Usage, response delays, and errors are monitored to check costs and performance for each user.

Why it matters

When many teams use AI tools, tracking costs and managing security can become scattered. This approach controls access and spending in one place, which helps a company use AI safely at wider scale.