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Decathlon

Real-Time Data Integration and Synchronization Hub

BackendLambdaNode.jsKafkaDynamoDBAWSCronJobsMicroservices

Real-Time Data Integration and Synchronization Hub (Event-Driven Architecture)

Overview

Development of a real-time data integration and synchronization platform based on Event-Driven Architecture and AWS microservices, designed to ensure high availability, scalability, and eventual consistency.

The system consumes high volumes of data from a SAP ERP, processes events at scale, and distributes consolidated data across multiple corporate domains in a resilient and low-latency manner.

Strategic keywords: corporate data integration, real-time synchronization, event-driven architecture, AWS microservices, Apache Kafka, AWS Lambda, DynamoDB, asynchronous processing, high availability, distributed systems.

Architecture

The architecture was designed using loosely coupled microservices, asynchronous communication, and fault-tolerant patterns.

Architectural Pattern

  • Microservices
  • Event-Driven Architecture
  • Asynchronous event processing
  • Eventual consistency in distributed environments

Technologies and Services

  • Apache Kafka for ingestion of third-party events.
  • Amazon SQS (Simple Queue Service) for decoupled queuing and flow control.
  • Amazon SNS (Simple Notification Service) for secure message routing and pub/sub.
  • Dead Letter Queues (DLQ) for structured failure handling.
  • AWS Lambda (Serverless) for on-demand event processing and transformation.
  • Amazon DynamoDB (NoSQL) for high-performance storage with millisecond reads.
  • Data modeling using Single-Table Design and optimized partition key strategies.

Key Contributions

  • Built high-throughput event-driven microservices.
  • Integrated hybrid data flows (Kafka + AWS native messaging services).
  • Designed scalable DynamoDB schemas optimized for performance.
  • Implemented resilience mechanisms including:
    • Automatic retries
    • Dead Letter Queues
    • Circuit breakers
    • Structured exception handling
  • Ensured reliability and stability in distributed systems.

Impact

  • Reduced cross-system data propagation time.
  • Improved reliability in enterprise data synchronization.
  • Scalable architecture prepared for transaction growth.
  • Fault-tolerant platform with automated recovery mechanisms.

Event-driven architecture implemented with a strong focus on scalability, resilience, and production-grade reliability.