Hello @Uma Sundar
custom autoscale can only be enabled when the job is in the running
state.
Custom autoscale in Stream Analytics is enabled when you have a Stream Analytics job with a parallel or embarrassingly parallel topology. This means that the job has multiple inputs or outputs that can be processed independently, allowing for parallel processing.
When you have a job with this topology, you can enable custom autoscale by navigating to the Scale page in the Azure portal and selecting the Custom autoscale option. From there, you can configure the autoscale rules based on metrics such as CPU or memory usage.
Also see the : Custom autoscale - default condition
It's important to note that not all Stream Analytics jobs support custom autoscale. If your job does not have a parallel or embarrassingly parallel topology, you will not be able to enable custom autoscale. In this case, you can still use manual scaling to adjust the number of streaming units allocated to the job.
Please let us know if this helps and can close the case?