The same DLT job (workflow) will use the same cluster in development mode (shutdown in 2h) and new in production (shutdown 0). Although in JSON, you can manipulate that value:
{
"configuration": {
"pipelines.clusterShutdown.delay": "60s"
}
}
You can manipulate Azure's quotas by using different instances, and also, for smaller streams; you can set workers to 0
{
"clusters": [
{
"label": "default",
"node_type_id": "Standard_D3_v2",
"driver_node_type_id": "Standard_D3_v2",
"num_workers": 0
}
]
}
I hope that pools will be added to DLT and serverless options.