Built an architecture for instant approvals backend
Designed an architecture that makes intelligent decisions in milliseconds - perfect for fraud detection, approvals, and access control.


Designed an architecture that makes intelligent decisions
in milliseconds - perfect for fraud detection, approvals,
and access control.
The Challenge:
- Process 50K+ events per second
- Score each event with ML models
- Respond in under 500ms
- Archive everything for compliance
The Solution:
- Stream processing (Apache Flink)
- ML inference (AWS SageMaker)
- Feature store (DynamoDB)
- Lambda architecture (hot + cold paths)
Real-World Applications:
- Detect credit card fraud as it happens
- Approve insurance claims in real-time
- Control network access with zero-trust
- Monitor IoT devices & send commands
Questions? Reach out on https://www.linkedin.com/in/arif-rahman-da/
Written by Data Engineering
Senior engineer with expertise in data engineering. Passionate about building scalable systems and sharing knowledge with the engineering community.
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