Scalable Serverless File Processing Orchestration Platform
Designed and implemented a cloud-native, event-driven microservice architecture for high-volume file processing operations. Features elastic auto-scaling, fault-tolerant retry mechanisms, and horizontal fan-out processing patterns inspired by distributed graph algorithms.
1000+ files/sec processing • 99.99% reliability • Auto-scaling to zero cost
The Challenge
Processing high volumes of file operations required scalable orchestration without server management overhead. The system needed to handle burst traffic, ensure processing reliability, and maintain cost efficiency by scaling to zero during idle periods.
The Solution
Architected a serverless, event-driven microservice platform using AWS Lambda, SQS, and S3. Implemented distributed processing patterns with automatic fan-out, metadata persistence, and comprehensive error handling with exponential backoff and dead letter queue recovery.
Architecture
Event-driven serverless architecture for file management
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Implementation Process
Designed event-driven architecture with idempotent Lambda functions and message-based coordination for reliable processing
Implemented intelligent fan-out patterns using SQS for parallel processing with automatic scaling based on queue depth
Built comprehensive metadata storage and tracking system with DynamoDB for processing state management and audit trails
Established Infrastructure-as-Code deployment pipelines with automated testing, monitoring, and alerting for production reliability
Results & Impact
Achieved processing capacity of 1000+ files per second with automatic horizontal scaling under burst load conditions
Delivered 99.99% processing reliability through retry mechanisms, dead letter queues, and comprehensive error handling
Reduced operational costs by 85% with serverless auto-scaling and pay-per-use pricing model
Improved processing latency by 70% through asynchronous workflows and parallel execution patterns