Article·aaas.blog
api-gatewayroutingrate-limitingauthenticationinfrastructureawsazuregcp
API Gateway Setup
Configure an API Gateway to manage, secure, and route traffic to LLM inference endpoints, including authentication, rate limiting, and load balancing.
intermediate1-2 hours10 steps
The play
- Choose an API GatewaySelect an API Gateway based on your infrastructure and requirements. Options include AWS API Gateway, Azure API Management, Google Cloud API Gateway, Kong, or Tyk. For this example, we'll assume AWS API Gateway.
- Create an API GatewayCreate a new API Gateway in your chosen platform. In AWS, this involves navigating to the API Gateway service and creating a new REST API or HTTP API.
- Define Resources and MethodsDefine the resources (e.g., `/inference`) and HTTP methods (e.g., `POST`) that your API will expose. Each method will need an integration point.
- Configure IntegrationConfigure the integration to your LLM inference endpoint. This could be an HTTP endpoint, a Lambda function, or another service. Specify the integration type, URI, and any necessary request/response mappings.
- Implement AuthenticationImplement authentication to secure your API. Options include API keys, IAM roles, or OAuth 2.0. Configure the authentication method in the API Gateway settings.
- Apply Rate LimitingApply rate limiting to prevent abuse and ensure fair usage. Configure rate limits based on API keys, IP addresses, or other criteria.
- Enable Request/Response TransformationUse request/response transformation to adapt the API's input and output formats to match the LLM inference endpoint's requirements. This can involve mapping request parameters or transforming the response body.
- Deploy the APIDeploy the API to a stage (e.g., `dev`, `prod`). This makes the API accessible to clients.
- Test the APITest the API to ensure it's working correctly. Send requests to the API endpoint and verify that the responses are as expected.
- Monitor and ManageMonitor the API's performance and usage. Use the API Gateway's monitoring tools to track metrics such as request latency, error rates, and API usage.
Starter code
Start with a basic HTTP API Gateway setup and gradually add features like authentication, rate limiting, and request transformation.
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