Merge pull request #273663 from cloga/lochen/hobo-trigger

Lochen/hobo trigger

Author: PMEds28

articles/machine-learning/how-to-manage-quotas.md

@@ -149,7 +149,7 @@ To request an exception from the Azure Machine Learning product team, use the st
 
 <sup>4</sup> We reserve 20% extra compute resources for performing upgrades. For example, if you request 10 instances in a deployment, you must have a quota for 12. Otherwise, you receive an error. There are some VM SKUs that are exempt from extra quota. See [virtual machine quota allocation for deployment](how-to-deploy-online-endpoints.md#virtual-machine-quota-allocation-for-deployment) for more.
 
-<sup>5</sup> Requests per second, connections, bandwidth etc are related. If you request for increase for any of these limits, ensure estimating/calculating other related limites together.
+<sup>5</sup> Requests per second, connections, bandwidth etc. are related. If you request an increase for any of these limits, ensure estimating/calculating other related limits together.
 
 ### Azure Machine Learning pipelines
 [Azure Machine Learning pipelines](concept-ml-pipelines.md) have the following limits.
@@ -160,13 +160,6 @@ To request an exception from the Azure Machine Learning product team, use the st
 | Workspaces per resource group | 800 |
 
 
-### Azure Machine Learning job schedules
-[Azure Machine Learning job schedules](how-to-schedule-pipeline-job.md) have the following limits.
-
-| **Resource** | **Limit** |
-| --- | --- |
-| Schedules per region | 100 |
-
 ### Azure Machine Learning integration with Synapse
 
 Azure Machine Learning serverless Spark provides easy access to distributed computing capability for scaling Apache Spark jobs. Serverless Spark utilizes the same dedicated quota as Azure Machine Learning Compute. Quota limits can be increased by submitting a support ticket and [requesting for quota and limit increase](#request-quota-and-limit-increases) for ESv3 series under the "Machine Learning Service: Virtual Machine Quota" category.

articles/machine-learning/how-to-schedule-pipeline-job.md

@@ -100,7 +100,7 @@ When you have a pipeline job with satisfying performance and outputs, you can se
       - **Time zone**: the time zone based on which to calculate the trigger time, by default is (UTC) Coordinated Universal Time.
       - **Recurrence** or **Cron expression**: select recurrence to specify the recurring pattern. Under **Recurrence**, you can specify the recurrence frequency as minutely, hourly, daily, weekly and monthly.
       - **Start**: specifies the date from when the schedule becomes active. By default it's the date you create this schedule.
-      - **End**: specifies the date after when the schedule becomes inactive. By default its NONE, which means the schedule will always be active until you manually disable it.
+      - **End**: specifies the date after when the schedule becomes inactive. By default it's NONE, which means the schedule will always be active until you manually disable it.
       - **Tags**: tags of the schedule.
 
     After you configure the basic settings, you can directly select **Review + Create**, and the schedule will automatically submit jobs according to the recurrence pattern you specified.
@@ -492,6 +492,11 @@ Currently there are three action rules related to schedules and you can configur
 | Write  | Create, update, disable and enable schedules in Machine Learning workspace | Microsoft.MachineLearningServices/workspaces/schedules/write  |
 | Delete | Delete a schedule in Machine Learning workspace                            | Microsoft.MachineLearningServices/workspaces/schedules/delete |
 
+## Cost considerations
+
+- Schedules are billed based on the number of schedules, each schedule will create a logic apps host Azure Machine Learning subs on behalf (HOBO) of the user. 
+- The cost of logic apps will change back to the user's Azure subscription, and you can find costs of HOBO resources are billed using the same meter emitted by the original RP. They are shown under the host resource (the workspace).
+
 ## Frequently asked questions
 
 - Why my schedules created by SDK aren't listed in UI?