AWS
AI & ML
starter
Image Analysis Pipeline — AWS Architecture Template
Uploaded images are analysed by Rekognition via a Lambda trigger, with labels stored in DynamoDB and moderation alerts on SNS.
Why this architecture works
- Rekognition provides production-grade vision models with zero training or hosting effort
- Event-driven S3 triggering analyses each image exactly once, the moment it arrives
- Labels in DynamoDB make image search and filtering instant instead of re-analysing on read
- Moderation findings publish to SNS so review workflows react in seconds
- Pay-per-image pricing keeps cost proportional to actual usage with no idle capacity
What's inside (6 resources)
Image Uploads
aws-s3
Analysis Trigger
aws-lambda
Rekognition
aws-rekognition
Labels Store
aws-dynamodb
Moderation Alerts
aws-sns
Pipeline Metrics
aws-cloudwatch
From template to running infrastructure
- Open this template in the CloudForge visual designer (free account, no credit card).
- Customize resources, names, and connections on the drag-and-drop canvas — or ask Vani, the AI architect, to adapt it.
- Generate production-ready Terraform or CloudFormation in one click.
- Review the plan diff and security scan, then deploy with human approval.