Anatomy of Micro services based & distributed Master Data Management Architecture

Please note this is improved version of previously[1] explained architecture.

[1] http://dhanuka84.blogspot.com/2017/06/master-data-management-for-distributed.html

Master Data Change Detection

1. Admin Panel will change or add master data.
2. Changes goes to DB.
3. Update Hibernate First Level Cache.
4. Distribute data via Kafka.
5. Kafka Consumer detect master data change notification.
6. Update Hazelcast Distributed map with which master data has been changed.
7. Scheduler application task read from HZ map and get to know about which master data changed.
8. Get latest data for changed master data from master data micro service.
9. Update LocalEntityMap with business key and Entity.
10. Update Business key to Primary key map.
11. Removed master data notification record from HZ distributed map.

Scheduler Application Load Balancing

1. Get Business key to primary key mapping to all master data.
2. Update Business key to primary key mapping
3. Read Business key to primary key map then load balanced among HZ cluster members.
4. update HZ distributed map.
5. Keep business keys which load balanced to local application node.

Processing using master data within scheduler task

1. Read from HZ distributed map and get master data local to this node for processing and Keep them for processing.
2. Take business keys to process.
3. Get locally cached master data for business keys for processing.
4. If can’t find in the cache get from micro service.