scalable image classification
aws
The project focused on enhancing system performance and scalability by optimizing auto-scaling policies and CloudWatch alarms, and implementing custom step-scaling based on m1-m2 metrics, resulting in a processing time reduction of over 50%. Additionally, a scalable AWS architecture was implemented for image classification using Python/Boto S3 and Java/AWS SDK, enabling efficient processing of over 100 image requests with an average processing time of less than one second.