Legacy Migration to Event-Driven Architecture
Successfully migrated a legacy Master Data Management system to a modern event-driven architecture using Kafka, improving data consistency and real-time processing capabilities.
The Challenge
A major financial institution needed to modernize their Party Master Data Management (MDM) system, which was causing data inconsistencies and delays in critical business processes. The legacy system couldn't handle real-time requirements and was becoming a bottleneck.
- Tight coupling between systems causing cascading failures
- Batch processing causing delays up to 24 hours for data updates
- Data inconsistencies across multiple consuming systems
- Inability to support real-time risk assessment and compliance checks
- Complex dependencies making changes risky and time-consuming
Our Solution
We designed and implemented an event-driven architecture using Apache Kafka as the central nervous system, enabling real-time data distribution and eventual consistency across all consuming systems.
Event Sourcing Pattern
Implemented event sourcing to capture all changes as immutable events, providing a complete audit trail and enabling temporal queries.
Kafka Streams Processing
Built stream processing applications to transform, enrich, and validate party data in real-time before distribution to consumers.
Schema Registry Integration
Established Avro schemas with backward/forward compatibility to ensure safe evolution of data contracts between systems.
Phased Migration
Executed a zero-downtime migration using the Strangler Fig pattern, gradually moving consuming systems from batch to streaming.
Technologies Used
Results & Impact
The migration transformed the organization's data distribution capabilities, enabling real-time decision-making and significantly improving data quality and system reliability.
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