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An Eagle workflow may be as simple as getting a file from a vendor location (be it somewhere in the cloud or on an FTP site) and then loading it into the application, or it may be more complex, linking multiple services together, managing exceptions, parallelism, invoking a remote call, and providing notification. Using Eagle’s XML technology, you can build custom data driven workflows to meet their your exact requirements.
What is a Data Driven Workflow (DDW)?
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- Traditional Scheduler – Using Eagle’s scheduler capabilities it's possible to build a workflow that triggers jobs in either a sequence based on basic concurrency logic, or the state of a preceding event. This architecture typically uses a polling mechanism. In some cases, the context of the workflow is not maintained, that is, load securities poll for changes based on the update date and execute an engine on securities that have changed and then publish.
- Data Driven – In a data driven workflow, the context is typically maintained and managed through a series of control messages to maintain and interrogate the status of the service. Using the preceding example, load securities and then pass changed securities to the engine for processing. There is no need for a polling process, the consumer is fed the exact payload to process.
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