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The Active workers table lists one active worker node per row (an example with a single worker is shown in Figure 21) and contains performance metrics for worker processes and server processes. The columns provide the following information:
Name: worker’s identifier (IP address or name)
CPU usage: the computational load of the worker process
Memory usage: the memory usage of the worker process
Machine capacity: indicates the number of cores and amount of RAM available to the worker
Uptime: the duration that the worker has been running
Type: the type of worker (described below)
Actions: selecting the stops a worker while selecting starts a worker (Figure 23)
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Partek Flow supports two types of workers: Partek Flow is installed on the server while those labeled worker run on a remote machine. When the server is configured to accept work, its type is changed to internal to differentiate it from other workers. Multiple workers can be deployed to handle computationally-intensive tasks or to help alleviate a long queue of tasks. Figure 4 3 shows an example with five active workers.
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