Build a Serverless AI Application Using Amazon Bedrock, Lambda, API Gateway, and S3
Learn how to build a practical serverless AI application on AWS using Amazon Bedrock, AWS Lambda, API Gateway, and Amazon S3. This guide explains the architecture, request flow, security considerations, and how these services work together to create a scalable AI application.
INTERNET
│
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┌───────────┐
│ CloudFront │
└─────┬─────┘
│
▼
┌───────────┐
│ S3 │
│ Frontend │
└─────┬─────┘
│
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┌───────────┐
│ API │
│ Gateway │
└─────┬─────┘
│
▼
┌───────────┐
│ Lambda │
└─────┬─────┘
│
IAM Role
│
▼
┌───────────┐
│ Bedrock │
└─────┬─────┘
│
▼
Foundation
Model
│
▼
AI Response
│
▼
┌───────────┐
│ CloudFront │
└─────┬─────┘
│
▼
┌───────────┐
│ S3 │
│ Frontend │
└─────┬─────┘
│
▼
┌───────────┐
│ API │
│ Gateway │
└─────┬─────┘
│
▼
┌───────────┐
│ Lambda │
└─────┬─────┘
│
IAM Role
│
▼
┌───────────┐
│ Bedrock │
└─────┬─────┘
│
▼
Foundation
Model
│
▼
AI Response
modern serverless AI application can combine several AWS services:
S3 → hosts static frontend
API Gateway → exposes secure APIs
Lambda → executes backend logic
Amazon Bedrock → provides foundation-model capabilities
IAM → controls permissions
CloudWatch → provides monitoring and logs
CloudFront → can improve global delivery of the frontend
The important architectural idea is that each service performs a specific responsibility, allowing the application to remain modular and easier to operate.
S3 → hosts static frontend
API Gateway → exposes secure APIs
Lambda → executes backend logic
Amazon Bedrock → provides foundation-model capabilities
IAM → controls permissions
CloudWatch → provides monitoring and logs
CloudFront → can improve global delivery of the frontend
The important architectural idea is that each service performs a specific responsibility, allowing the application to remain modular and easier to operate.
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