In System Settings, on the Worker screens, configure the worker components. The worker component is available for configuration if the local machine is configured to act as a worker.
The Alteryx Service Worker is responsible for executing analytic workflows. There must be at least one machine enabled as a worker to execute workflows through the Service. You may configure the same machine to be both the controller and a worker. The actual number of workers needed depends on the required performance for the system.
The General screen includes configuration options such as where temporary files should be stored and whether the machine can run scheduled workflows.
- Allow machine to run scheduled Alteryx workflows: Enabling this machine to run scheduled Alteryx workflows allows it to take requests to run workflows from the Scheduler and from the Gallery. In multi-node deployments, you may want to uncheck this option if you have another machine that will be running workflows, and want this machine to render map tiles or Insights only
- Workflows allowed to run simultaneously: This is the maximum number of scheduled workflows that are allowed to run simultaneously on this machine. You may want to increase this number to improve the responsiveness of scheduled jobs, but the overall processing time may be increased.
- Cancel jobs running longer than (seconds): If you do not want jobs to run for an extended period of time, use this setting to force jobs to cancel after a certain amount of time has passed. This helps free up system resources that might otherwise be taken up by unintentionally long running jobs. This setting only applies to scheduled jobs and does not affect manual runs from the Gallery.
- Quality of Service: In an environment where multiple workers are deployed, Quality of Service determines which jobs are run by each worker. When a job request is handled by a worker, it compares the priority level of the job to the Quality of Service value for the worker. Jobs that have a value greater than or equal to the Quality of Service value for the worker will be handled by that worker. For example, if a worker has a Quality of Service of 0 and is available, the worker will handle any request. However, a worker with a Quality of Service of 3 will only handle jobs that have a value of 3 or higher. This allows resources to be reserved for higher priority requests. For normal operation with one machine configured as a worker, set quality of service to 0.
- 0 = Low (normal workflow execution)
- 1 = Medium
- 2 = High
- 3 = Critical
- 4 = Chained application execution (all apps in the chain aside from the last)
- 6 = Workflow validation requests
- Job Assignment: A specific worker can be assigned to run a job. First, add a job tag for the worker, and then select that job tag when creating a schedule or running a workflow.
- Run unassigned jobs: Select this option to use the worker to run jobs that have not been assigned a job tag.
- Job tags: Add words that can be used to assign a specific worker to run a job. Separate multiple job tags with a comma. The same job tag can be added to multiple workers.
If a worker machine needs to run workflows that access files or data from a location that requires specific credentials to access it, the machine can be configured to run the workflows as a specified user or account. To have the machine run as a different user, enter the Domain, Username, and Password.
For information on setting Run As User permissions, see Set Required Run As User Permissions.
The machine can be enabled to act as a Map Worker, which allows it to render map tiles for Map Questions and the Map Input tool. You can specify the number of processes to be used for tile rendering. The more processes allowed, the more simultaneous tiles can be rendered, but it takes up more system resources.
Enable Insight Worker: The machine can be configured to act as an Insight Worker and render insights, which are interactive dashboards created in Alteryx Designer and published in a Gallery.
Insights allowed to run simultaneously: The maximum number of insights that can run simultaneously on the machine. The more insights that can be run simultaneously, the more system resources used.
Max Cache Size (# of Cache Directories): The maximum number of insights cached on a worker machine. Each insight consists of a description and data file, so each insight cache is a directory that contains those files.
Max Port, Min Port: The range of port numbers designated for use when rendering insights.