About data flows

Ops Center Protector User Guide
Version
7.7.x
Audience
anonymous
Part Number
MK-99PRT002-08
ft:lastEdition
2023-10-26

A Data Flow is a diagrammatic representation of the nodes involved in a data protection scenario where each node is represented by an icon. Data flow diagrams identify both physical and logical entities and the connections between them. The data that is to be protected flows from a Source Node to a Destination Node during the data protection process by way of a Mover; the direction of movement being indicated by an arrow on the connector between nodes. Data is transferred in scheduled batches indicated by a solid Batch mover. For host based backups, data transmitted across a network can be compressed to reduce bandwidth utilization and bandwidth throttling schedules can be applied to movers, to ensure that data protection activity does not degrade normal network performance.

Node Groups can be placed on data flows so that multiple nodes having common properties can be treated as one entity.

Each node in a data flow plays a part in implementing the data protection scenario by having a Policy assigned to it (see About policies). Once a data flow is constructed, it must be Activated before it becomes operational. An active data flow can be Deactivated to stop that data protection process.
Note: Deactivating a hardware storage dataflow marks replications within it as eligible for being torn down. The actual teardown process must be initiated by the user via the user interface. See About two-step teardown.
The process of compiling a data flow performs validity checks on the data flow and assigned policies, then generates a set of rules for each node in the data flow. The compiled rules are distributed to the affected nodes and activated; the participating nodes use these rules to act autonomously. The operation of a data flow can be monitored in real-time using the same data flow diagram rendered as a mimic display (see About monitoring).
Data flow topologies generally fall into one of the following groups (although combinations of these are also possible):
  • One-to-one - data from a single source is backed up to a single destination.
  • Many-to-one - data from multiple sources is backed up to a single destination.
  • One-to-many - data from a single source is backed up to multiple destinations.
  • Many-to-many - data from multiple sources is backed up to multiple destinations.
  • Cascaded - data from a source is backed up to one destination then forwarded on to a second destination.