High-Performance Data Transfer Service
Developed cross-partition S3 object data transfer service for enterprise cloud migrations, serving as core data transfer engine for AWS services including RDS, SageMaker, AWS Hardware Infra. Achieved 3TB/min transfer speeds with 1,000x performance improvement, earning company-level "Invent and Simplify" breakthrough award.
Project Overview
This high-performance data transfer service is a cross-partition S3 object data transfer solution designed for enterprise cloud migrations, serving as the core data transfer engine for AWS services including RDS, SageMaker, and AWS Hardware Infrastructure. The system achieved 3TB/min transfer speeds with a 1,000x performance improvement, earning the company-level "Invent and Simplify" breakthrough award.
When dealing with cross-partition transfers and migrations from other cloud providers, the biggest challenge was that all data had to traverse the public internet without access to AWS's backbone network. Consequently, transfer nodes frequently faced IP restrictions from competitors or the Chinese firewall, resulting in throttling issues and timeout errors. I implemented numerous optimizations to overcome these challenges.
Key Achievements
Core Technical Features
Designed high-throughput system achieving efficient transfers between AWS Global and China regions without backbone network connectivity.
Engineered dynamic cluster scaling (1-10k nodes), reducing idle resource costs by 80%.
Designed intelligent file segmentation distributing single files across entire cluster for parallel transmission, enabling <1min transfer time for 1TB files.
Built serverless dashboard enabling enterprise customers to monitor transfer progress and initiate data migration tasks. Scaled to serve 300+ global customers processing millions of tasks monthly, reducing support tickets by 80%.
File Transfer Strategies Based on File Size
Core Architecture: Dynamic file transfer strategies based on object size
Small File Transfer Strategy (<10MB)
- • Uses simple GetObject and PutObject operations
- • Reads and uploads the entire file at once
- • Single-threaded processing, no need to combine multiple parts
- • Faster execution with lower overhead
Medium File Transfer Strategy (10MB-1GB)
- • Uses Multipart Upload API
- • Single worker node handles the entire file
- • Divides the file into multiple chunks for parallel upload
- • Improves bandwidth utilization and supports resumable transfers
Giant File Transfer Strategy (>1GB)
- • Uses distributed processing approach
- • Entire worker cluster collaborates on a single file
- • Uses Step Functions to coordinate the entire process
- • Maximizes parallelism and network utilization
Technical Challenges & Solutions
Faced IP restrictions and firewall issues during cross-partition transfers, resolved through intelligent routing and retry mechanisms.
Customers are extremely sensitive to both performance and cost, achieved cost control through dynamic scaling and resource optimization.
Designed distributed architecture to handle TB-scale file parallel transmission, ensuring high throughput.
Official Resources
Business Impact
Scaled to 300+ global enterprise customers across semiconductor, automotive, consumer electronics, and technology sectors — processing millions of transfer tasks monthly as core AWS infrastructure.
Reduced idle resource costs by 80% through dynamic scaling (1-10K nodes), passing significant cost efficiency gains to enterprise customers.
Automated operations reducing support tickets by 80%. Partner enablement program trained 64 partner employees, making this the default S3 migration tool for strategic partners.
Tech Stack
All data, metrics, screenshots, and demos shown are based on publicly available information or anonymized data.