Any ideas on how to handle timeouts in a pipeline?

[arpost]

Greetings, all. I have a long-running pipeline to which I want to add error-handling in the event an activity times out. I have tried to research online but haven't had any success in figuring out how exactly to tap into the details around timeouts. Does anyone have ideas on how I can get that info?

Ideally, I'd like to capture when a pipeline has a timeout occur. The specific culprit I am encountering is an Until activity. I put together an example below to illustrate:

To be clear, I know I could increase the timeout time; I am specifically wanting to add logic that can know if a pipeline activity times out. Until doesn't provide any Output details, so I wasn't quite sure how to access.

[v-bmanikante]

Hi @arpost ,

May I ask if you have gotten this issue resolved?

If it is solved, please mark the helpful reply or share your solution and accept it as solution, it will be helpful for other members of the community who have similar problems as yours to solve it faster.

Regards,

B Manikanteswara Reddy

[v-bmanikante · Accepted solution]

Hi @arpost ,

If the earlier solution didn't work, please try the below workaround.

To effectively detect and manage timeouts, particularly within the Until activity.in Microsoft Fabric pipelines, you can implement a combination of timeout settings and custom logic. Set the timeout property on the Until activity to define a maximum runtime. Within the loop, we can use a pipeline variable such as TimeoutFlag and introduce a counter that increments with each iteration. If the counter exceeds a defined threshold, set TimeoutFlag to true. After the Until activity, use an If Condition activity to check the value of TimeoutFlag. If it is true, we can route the flow to custom error handling steps, such as logging the issue or sending alerts.

If your issue has been resolved already, it would be great if you could share the steps or the final solution you followed, so others facing a similar issue can benefit from it as well.

Also, please consider marking it as the accepted solution if it helped , this really helps the community.

Regards,

B Manikanteswara Reddy

[v-bmanikante]

Hi @arpost ,

Thank you for reaching out to Microsoft Fabric Community Forum.

As we haven’t heard back from you, we will go ahead and close this ticket for now.

If you need any further assistance, please don’t hesitate to raise a new ticket, we’re always happy to help.

Our sincere apologies if there was any inconvenience caused.

Regads,

B Manikanteswara Reddy

[v-bmanikante]

Hi @arpost ,

As we haven’t heard back from you, we wanted to kindly follow up to check if the solution provided for the issue worked? or Let us know if you need any further assistance?

If our response addressed, please mark it as Accept as solution and click Yes if you found it helpful.

Regards,

B Manikanteswara Reddy

[v-bmanikante]

Hi @arpost ,

We wanted to kindly follow up to check if the solution provided for the issue worked? or Let us know if you need any further assistance?

If our response addressed, please mark it as Accept as solution and click Yes if you found it helpful.

Regards,

B Manikanteswara Reddy
 

[v-bmanikante]

Hi @arpost ,

Thank you for reaching out to Microsoft Fabric Community forum.

Azure Data Factory provides a few helpful error handling patterns to manage failures more gracefully in your pipelines:

• Try-Catch Pattern: Use the “Upon Failure” path to catch errors from previous activities. This lets your pipeline continue even if something fails.
• Do-If-Else Pattern: Use both “Upon Success” and “Upon Failure” paths to define what happens in each scenario—great for conditional logic based on activity outcomes.
• Do-If-Skip-Else Pattern: Similar to Do-If-Else, but includes a dummy activity for “Upon Skipped” to keep the pipeline from failing when some steps are skipped.

You can check the following Microsoft documents to understand how to handle errors in Azure Data Factory pipelines. These guides cover handling timeouts, using retry policies, and implementing error handling patterns like try-catch, fail activity, and more:

🔹 Pipeline failure and error message - Azure Data Factory | Microsoft Learn

🔹 Understanding Pipeline Failures and Error Handling | Microsoft Community Hub

🔹 Execute a Fail activity in Azure Data Factory and Synapse Analytics - Azure Data Factory & Azure Syn...

These should help you implement robust error and timeout handling in your pipelines.

If this post helps, then please consider Accepting as solution to help the other members find it more quickly, don't forget to give a "Kudos" – I’d truly appreciate it!

Regards,
B Manikanteswara Reddy