Azure Data Factory (SSIS) Execution Using Integration Runtime Throws "Unexpected Termination" - azure

I have been using Azure Data Factory V2 for a while to execute SSIS packages from the SSISDB catalouges.
Today (16-11-2018) I have encountered "Unexpected Termination" Failure message without any Warning and Error message.
Things than I have done:
Executing the SSIS package manually from the SSISDB catalogue in SQL Server Management Services (SSMS). What i have noticed is that it took an exceptionally long time to assign the task to a machine. When the package is assigned to a machine, within 1 or two minutes it throws back the Failure message.
There are 3 SSIS packages that is excecuted "sequentially" with the Azure Data Factory Pipeline. Often the 1st package is executed successfully, however the 2nd and 3rd package never succeded.
Another error message that I got is "Failed pull task from SSISDB, please check if SSISDB has exceeded its limit".
I hope anyone can help me with this issue. I have been searching the web and could not find anything on this subject.

What tier of Azure sql server have you provisioned for the SSISDB to run on? If its too small, it may be taking too much time starting and throw a timeout.
Personally, I've had no problems provisioning an S3 Azure Sql Server.
Hope this helped!
Martin

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-- Update 2 --
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Looking at the Service Blade in the Azure Portal I found an emerging issue listed.
Starting at 09:00 UTC, customers may experience errors using Azure
Data Factory in West Europe, using the Azure Portal UX. We are aware
of the issue and are investigating. Updates to follow in 60 minutes or
as events warrant. Workaround: Customers can manage Data Factory using
Azure Data Studio, Azure CLI or Powershell.
https://aka.ms/azuredatastudio
-- Update from Microsoft --
Summary of impact: Between approximately 06:30 UTC and 12:30 UTC on 13 Dec 2021, you were identified as a
customer using Data Factory V2 in West Europe who may have experienced intermittent errors when accessing
resources in this region.
Preliminary Root Cause: We determined a backend service, responsible for processing API requests became
unhealthy. This led to intermittent API failing calls for Azure Data Factory resources.
Mitigation: We restarted the backend service which mitigated the issue.

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