Mainframe replication handles large-scale data processing in high-volume transaction environments. Its stability and reliability make it suitable for critical business applications such as banking and government services, where data integrity and long-term uptime are essential.
The mainframe replication pipeline facilitates data transfer and synchronization between mainframe systems and modern data environments, enabling real-time replication with minimal latency.
Note: You must have the Replication Designer role to configure and manage replication
pipelines. A workspace manager can assign the role from the Manage User page.
Mainframe replication page
Create and manage mainframe replication pipelines on the Mainframe Replication page, which lists all pipelines with their details.
What's changed: In the new user experience, the Mainframe Replication page uses a project-centric list with Health, Project, Rows Captured, Rows Applied, Longest Current Latency, and Last Updated columns. You can also use Add Project, Start Selected, and Stop Selected on this page. For more information on the new experience, see About the new user experience.
- +Create Pipeline: Create a new pipeline by specifying source, target, replication options, and other details.
- Pipeline list: Each row corresponds to a pipeline with the following columns:
- Health: Current health status with visual indicators (for example, red for error).
- Pipeline Name: Name of the pipeline.
- Rows Captured: Number of rows captured from the source.
- Bytes Captured: Volume of data captured.
- Rows Applied: Number of rows applied to the target.
- Current Latency(s): Latency of captured data.
- Type: Whether the pipeline is high volume or advanced.
Note: Email notifications are sent to the replication designer when the pipeline status changes to Action Required.
After a pipeline is created, three views are available:
- Overview: A summary of all pipeline information.
- Details Snapshot: Pipeline and table-level statistics, statuses, warnings, and errors.
- Backlog and Latency: Details about latencies and replicated data.