Process instance modification Batches


We are using Process instance modification api to submit asynch batches to process the Bulk data in camunda. The challenge is that when users submit heavy count of batches back to back the DB CPU Utilization shoots to peak and remains the same until all the batches are processed. Hence we plan to go for Sharding at DB level.

Currently we are using MySQL DB on aws to process the data. Could you please suggest as to how the sharding can be done in MySQL from Camunda perspective as camunda guide recommends to use DB in Active Active with RC mode. Any documentation or guidance would be of great help


@Gaga Camunda provides cluster configuration for mariadb. For MySQL cluster configurations, it’s not documented yet.

Configuration for MariaDB Galera Cluster

You can refer these points:

The current GA version is MySQL Cluster 7.3. MySQL 5.6 is integrated and bundled with MySQL Cluster.
SQL Server Always On is a flexible design solution to provide high availability (HA) and disaster recovery (DR). It is built upon the Windows Failover Cluster , but we do not require the shared storage between the failover cluster nodes.

Thanks a ton for these pointers

if we migrate the existing MySQL RDS AWS to AWS Aurora (MySQL engine) with replication mode. Will this work smoothly in Camunda as Aurora provides the scaling capability on the fly . Any hints would be of great help. Please suggest. Thanks