EventFlow - Serverless Pipeline
Lambda + EventBridge + Terraform
Developed fully serverless event-driven architecture showcasing modern cloud-native patterns with AWS managed services. System demonstrates SAGA pattern for distributed transactions, event sourcing with DynamoDB Streams for audit trails, CQRS for read/write separation, dead letter queues for reliability. Implements EventBridge for event routing, SQS for async processing, Step Functions for workflow orchestration. Deployed entirely via Terraform IaC. Tested with simulated event load demonstrating auto-scaling, fault tolerance, cost optimization.
The Challenge
Traditional server-based architectures require over-provisioning for peak loads with low utilization. Need cost-effective auto-scaling system handling traffic spikes while maintaining low latency and guaranteed event delivery. Event-driven patterns (SAGA, event sourcing, CQRS) complex to implement correctly. Infrastructure reproducibility requires IaC.
The Solution
Architected serverless event-driven demo using AWS Lambda for compute, EventBridge for event routing, SQS for async processing, DynamoDB for state storage. Implemented SAGA pattern for distributed transactions, event sourcing with DynamoDB Streams, CQRS read/write separation. Step Functions orchestrate complex workflows. Terraform IaC for reproducible infrastructure. Dead letter queues for fault tolerance.
Technology Stack
Architecture
- Event-driven architecture with EventBridge event bus
- SAGA pattern via Step Functions state machines
- Event sourcing: append-only log in DynamoDB with Streams
- CQRS: separate read models materialized from event stream
- Lambda layers for shared utilities and dependencies
- SQS for async processing with FIFO ordering support
- Dead letter queues for failed event handling
- Terraform IaC managing entire AWS stack
- CloudWatch alarms for monitoring and alerting
- X-Ray distributed tracing across Lambda functions
Key Features
Results & Impact
- Fully serverless architecture with AWS Lambda + EventBridge + SQS + DynamoDB
- SAGA pattern implementation for distributed transaction coordination
- Event sourcing with DynamoDB Streams capturing all state changes
- CQRS pattern separating read/write models for scalability
- Step Functions orchestrating complex multi-step workflows
- Dead letter queues with retry policies for fault tolerance
- Terraform IaC deploying entire stack: 15+ AWS resources
- Tested with simulated load: 1K+ events/sec with auto-scaling