Serverless Object Tracking

AWS Lambda DynamoDB Python S3 API Gateway

The Challenge

The existing infrastructure for object tracking was built on always-on EC2 instances, leading to significant idle time and high costs during periods of low traffic. Scaling to handle burst workloads required manual intervention and slow boot times, creating latency bottlenecks for real-time tracking applications.

The Solution

I re-architected the entire backend to a fully Serverless model on AWS. By migrating compute logic to AWS Lambda and state management to DynamoDB (NoSQL), the system became event-driven, scaling automatically from 0 to 1000+ concurrent requests within seconds.

  • Designed a high-throughput event pipeline using S3 triggers and Lambda.
  • Optimized DynamoDB access patterns for single-digit millisecond latency.
  • Implemented Infrastructure as Code (IaC) for reproducible deployments.

Key Outcomes

12x

Cost Reduction

Auto

Zero-Maintenance Scaling

Project Info

  • Role Data Science Engineer
  • Timeline July 2021 - Present
  • Team Cloud Platform Engineering
  • Core Tech AWS Serverless, Python