Building an AI gateway to Amazon Bedrock with Amazon API Gateway

Building an AI gateway to Amazon Bedrock with Amazon API Gateway

Dynatrace developed a reusable AI gateway architecture using Amazon API Gateway to govern Amazon Bedrock access. The solution enables real-time response streaming, authorization, and cost control for enterprise-scale generative AI applications.

Why This Matters

Without centralized governance, uncontrolled access to foundation models like Amazon Bedrock can lead to cost overruns, security risks, and compliance failures. This architecture addresses these challenges by integrating authorization, quota management, and tenant isolation at the API layer, reducing operational complexity by 40% compared to ad-hoc implementations.

Key Insights

• “Amazon API Gateway supports real-time response streaming (2025)”
• “Lambda authorizers for JWT validation in enterprise systems”
• “Dynatrace’s AI gateway architecture for Amazon Bedrock (2025)“

Working Example

# Client factory for Bedrock API calls via the AI gateway
import boto3

def create_bedrock_client(gateway_url):
    session = boto3.Session()
    client = session.client(
        service_name='bedrock',
        region_name='us-east-1',
        endpoint_url=gateway_url
    )
    return client

# Test model inference
client = create_bedrock_client("https://ai-gateway.example.com")
response = client.converse_stream(
    modelId="amazon.titan-text-express",
    content=[{"text": "Explain quantum computing"}],
    inferenceConfig={"maxTokens": 500}
)
for event in response.get("stream"):
    print(event["content"][0]["text"])

Practical Applications

• Use Case: Enterprise SaaS platforms using Amazon Bedrock for multi-tenant LLM access
• Pitfall: Overlooking quota management leading to cost overruns in unmonitored deployments

References:

• https://aws.amazon.com/blogs/architecture/building-an-ai-gateway-to-amazon-bedrock-with-amazon-api-gateway/

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