Using the Parallel Native Action

the parallel native action in swimlane turbine allows orchestrators to execute multiple paths in parallel, waiting for all branches to complete before continuing downstream this action is ideal for workflows requiring simultaneous processing of tasks with synchronized results overview the parallel native action enables simultaneous execution of multiple actions, optimizing workflows that require concurrent processing by ensuring all parallel tasks complete before proceeding, the action provides precise control over complex playbook flows key benefits of the parallel action native action integrated directly into the playbook builder for streamlined workflow creation concurrent processing enables simultaneous execution of multiple actions, reducing overall processing time synchronized results ensures that all branches complete before the workflow continues, maintaining workflow consistency no connector needed operates within swimlane without external integration wait feature provides a visual indicator showing that the playbook is waiting for parallel branches to complete before proceeding understanding the parallel action using the parallel native action, you can execute multiple paths simultaneously, wait for them to complete, and then continue the playbook flow the action provides both on success and on failure paths based on the outcome of the parallel branches important notes about the wait feature if any action in the group fails, the on failure path is executed if all actions in the group succeed, the on success path is executed once the wait feature completes, the playbook continues downstream to the next path you can use nested loops (loop native actions) within a parallel group entry points are flexible; you can chain actions within the parallel group using on success , on failure , and on complete paths if any action in the parallel group fails, the entire group is marked as a failure action flow options within parallel groups within a parallel group, each action can follow one of the two flow paths on success and/or on failure on complete note you cannot use on complete with on success or on failure in the same action additionally, only one on failure path is allowed per parallel group adding and configuring the parallel action when you drag and drop a parallel native action onto the playbook canvas, the wait visual indicator automatically appears, signifying that the playbook is waiting for all parallel paths to complete first, add entry points for your parallel paths note the wait node ensures that the workflow pauses until all actions in the group are completed configure the on success , on failure , and on complete actions for each path based on your workflow requirements you can now continue building your playbook with the configured parallel paths examples example 1 simultaneous data processing scenario process user data and send notifications simultaneously drag and drop the parallel action onto the playbook canvas add one path for processing user data (e g , updating records) add another path for sending notifications (e g , emails or sms) configure the paths to ensure both tasks run concurrently and complete before proceeding to the next step example 2 multi endpoint api calls scenario call multiple apis in parallel to gather data for a report add the parallel action to your playbook configure each branch to make a different api call (e g , fetching data from different services) ensure all api responses are aggregated before generating the report example 3 parallel file processing scenario process multiple files simultaneously for faster completion add a parallel action to the playbook create branches for processing each file ensure all file processing actions complete before proceeding to the next workflow step best practices handle failures gracefully define clear on failure paths to manage errors effectively limit complexity avoid overly complex parallel structures that may become difficult to manage and debug test thoroughly validate each branch independently before running the complete parallel workflow monitor performance track execution times and optimize for efficiency, especially when processing large data sets concurrently