Flow Data Caller

The Flow Data Caller node enables you to access data from other flows in your workspace, allowing for cross-flow data sharing and integration. This node connects flows together by retrieving specific field outputs from nodes in different flows, creating powerful flow orchestration capabilities.

Choose the source flow containing the data you want to access:

Purpose: Identify which flow contains the data you need to retrieve

Selection Method: Use the dropdown to browse available flows in your workspace

Default State: Shows "None Selected" until a flow is chosen

Connection Point: Can receive flow selection from other flow nodes

Access Requirements: You must have access permissions to the target flow

Choose the specific node within the selected flow:

Purpose: Identify which node's output data you want to access

Selection Method: Use the dropdown to browse nodes available in the selected flow

Default State: Shows "Select a Node" until a node is chosen

Connection Point: Can receive node selection from other flow nodes

Dependency: Only becomes available after selecting a flow

Choose the specific output field from the selected node:

Purpose: Specify which data field you want to retrieve from the target node

Selection Method: Use the dropdown to browse available output fields from the selected node

Default State: Shows "None Selected" until a field is chosen

Refresh Option: Use the refresh icon to update available fields if the output field has been updated in the containing flow and node

Main Output: Displays the retrieved data in the Output section

Data Format: Preserves the original format and structure of the source data

Real-time Access: Retrieves current data from the source flow when executed

Connection Point: Retrieved data can feed into other flow nodes for further processing

Flow Selection: Choose the source flow from your workspace

Node Identification: Select the specific node containing the desired output

Field Specification: Choose the exact data field to retrieve

Data Access: Node retrieves the current value from the specified source

Output Delivery: Retrieved data becomes available for downstream processing

Naming Conventions: Use clear, descriptive names for flows to make selection easier

Documentation: Document which flows provide data for others to reference

Version Control: Be aware that changes to source flows affect data retrieval

Access Management: Ensure proper permissions are set for cross-flow access

Field Stability: Use stable output field names in source flows to prevent broken connections

Data Validation: Verify that retrieved data meets expected format and content requirements

Error Handling: Plan for cases where source flows are unavailable or have changed

Update Frequency: Consider how often source data changes and plan execution timing accordingly

Flow Dependencies: Understand the execution order requirements between connected flows

Resource Planning: Account for additional processing time when accessing external flow data

Caching Strategy: Consider data freshness requirements versus performance needs

Network Latency: Factor in potential delays when accessing data from different flow instances

Data Flow Design: Plan cross-flow connections as part of overall system architecture

Dependency Mapping: Document which flows depend on others for data

Modular Design: Create reusable flows that can serve data to multiple consumers

Separation of Concerns: Use data caller patterns to separate data generation from data consumption

Permission Management: Ensure appropriate access controls for sensitive flow data

Data Governance: Implement policies for cross-flow data sharing

Audit Trail: Track which flows access data from others for compliance and debugging

Privacy Considerations: Be mindful of data privacy requirements when sharing across flows

Data Aggregation: Combine outputs from multiple specialized flows

Reporting Systems: Pull data from various source flows into consolidated reports

Monitoring Dashboards: Access real-time data from operational flows

Cross-Team Collaboration: Share data between flows managed by different teams

Microservice Architecture: Implement flow-based microservices with data sharing capabilities

Connection Issues: Verify source flow accessibility and permissions

Field Changes: Check if source node fields have been modified or renamed

Data Format: Ensure retrieved data format matches expectations in consuming flow

Execution Timing: Coordinate execution schedules between dependent flows

The Flow Data Caller provides essential capabilities for building interconnected flow ecosystems, enabling sophisticated data sharing and flow orchestration patterns across your workspace.