If `true`, ML Commons tasks and models run machine learning (ML) tasks on ML nodes only. If `false`, tasks and models run on ML nodes first. If no ML nodes exist, tasks and models run on data nodes. Don't set as "false" on production cluster.
`round_robin` dispatches ML tasks to ML nodes using round robin routing. `least_load` gathers all an ML nodes' runtime information, like JVM heap memory usage and running tasks, then dispatches tasks to the ML node with the least load.
When returning runtime information with the [profile API]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api#profile), ML Commons will run a regular sync up job to sync up newly loaded or unloaded models on each node. When set to `0`, ML Commons immediately stops sync up jobs.
### Values
- Default value: `10`
- Value range: [0, 86,400]
## Predict monitoring requests
### Setting
```
plugins.ml_commons.monitoring_request_count: 100
```
### Description
Controls how many upload model tasks can run in parallel on one node. If set to `0`, you cannot upload models to any node.