I'm working on a deep learning project and I'm using pipelines with an "Execute python script" to run my computations on a private training cluster (STANDARD_NC12), which is running on the Enterprise Edition.
It is running correctly, but after ten hours the run is canceled, without an error message or any indication of what happened.
Note that the job status is Canceled not Failed.
What could cause this? I didn't cancel the job.
a designer pipeline will be canceled if one module cannot finish within 10 hour. For your specific case, I'm not sure why it takes so long. I'd suggest you submit a feedback(the smile face icon on the top right corner) in the Studio portal, the feedback contains some basic trouble shooting info like subscription. Then prod team can follow up.
Related
I'm using Azure DevOps Pipelines with a self hosted build agent to deploy to App Services. We occasionally get "No space left on device" errors that result in deployment fails.
It seems somewhat random when we receive these errors, so we're having trouble figuring out what the cause is.
We scheduled a maintenance job to clean up records, but are still occasionally running in to the issue. The failures tend to happen more often in the mornings 8AM-10AM EST and after 4PM, but its random enough I'm not sure if that's relevant. I've also had a Saturday with pretty consistent fails. Eventually the deployments start working again with no intervention on our end.
Any insight in to what is going on or potential solutions would be greatly appreciated.
I and my team members are working on a machine learning project through the Azure ML portal.
We have created a specific experiment in our workspace in Azure ML and are submitting our Python script runs from our local or remote machines in this experiment.
Although I'm collaborating with my colleagues, most of the runs in this specific experiment are submitted by me.
Recently, I have faced a problem with experiment submissions.
The problem is that after some number of experiments created by me, I cannot add any other runs to this experiment, but my colleagues can!!!
Unfortunately, the Azure ML portal does not show any clear error message for this problem. It continues submitting the run till a timeout exception occurs!
As a temporary solution, I've just changed the name of the experiment and I could conquer this problem.
This solution helped me to submit my run on Azure ML but it didn’t satisfy me because we want to collect all related runs under a specific experiment. On the other hand creating multiple number of experiments for each run is overwhelming!
What I know is that there are some service limits for the number of runs in a workspace on this page. I am sure that the number of runs in our workspace has not reached to the 10 millions, because I can created new runs under new experiments dashboard. But I don’t know anything about the limitations on the number of runs in a specific experiment or even any limitations for the number of runs per users in a specific experiment.
I couldn't find any clear document explaining this fact.
Is there anyone who can help me for this issue?
I use Power Automate to refresh a PowerBI dashboard when I update its input files on Sharepoint.
Since the inputs are generated via another automated process, the updates follow each other very closely, which triggers the start of one Power Automate job per updated file.
This situation leads to failed jobs since they are all running at the same time. Even worse, the first job succeeds but the refresh then happens when not all files are updated yet. It is also a waste, since I would only need one to run.
To accomodate for that, I tried to introduce a delay in the job. This makes sure that when the first job runs, refreshing powerBI will work. Howerver, the subsequent runs all fail, so I would still like to find a way not to run them at all.
Can anyone guide me in the right direction ?
For this requirement, you can set the Share Point trigger can run only 1 instance at same time. Please refer to the steps below:
1. Click "..." button of the trigger and click "Settings".
2. Enable "Concurrency Control" limit and set Degree of Parallelism as 1.
Then your logic app can not run multiple instances at same time.
I have an Azure webjob created using the SDK that runs hourly. The job runs, and works fine, but when I look at the job in the portal it always shows Failed. I can run the job from the Debug Console and everything appears fine. When run from the console the job typically takes seconds to run, but when run on the schedule it usually shows 12-20 minutes, before it fails.
How can I get more details as to why this is failing? Do I need to be telling webjobs somehow the task is finished and it's waiting on me?
Thanks,
Russ
Webjob Failure
This error happens if the job uses TimerTrigger.
If the job is long-running use WEBJOBS_IDLE_TIMEOUT and SCM_COMMAND_IDLE_TIMEOUT in Azure app settings instead of web.config.
If the job is not long-running, it should have scheduled timers less than 2 minutes, which will probably work well for testing only.
Finally, the ultimate solution is to use Basic or Standard offering of AppPlan.
In that case you can ENABLE Always On to keep the container loaded all the time.
However, WEBJOBS_IDLE_TIMEOUT and SCM_COMMAND_IDLE_TIMEOUT must also be set as described above. Continuous WebJobs or of WebJobs triggered using a CRON (TimerTrigger) expression without Always On, will not run reliably.
For more details, you could refer to this article.
I've created a simple Azure WebJob that uses a QueueInput trigger. It deployed without any problems and I've schedule it via the management portal so that it 'Runs continuously'
Initial testing seemed fine, with the job triggering shortly after placing anything in the queue.
By chance I then left it about a day before placing anything else in the queue. This time the job hadn't triggered within a few minutes so I logged in to the portal to view the invocation logs - which showed that the job had just that moment been triggered.
That seemed too much of a coincidence so I left it another day before placing something in the queue. Again, the job didn't trigger. I left it overnight and by morning it still hadn't triggered.
When I logged in to the management portal this time I noticed that the job was marked as 'Aborted' on the WebJobs page. It was like that only for about 10 seconds before the status changed to 'Running'. And then the job immediately triggered from what was placed in the queue the night before, as expected.
As it's an alpha release I'm expecting glitches. Just wondering whether anyone else has had a similar experience.
For WebJobs SDK, your job must be running in order to listen for triggers (new queue messages, new blobs, etc). Azure Websites free tier has quotas and will put your job to sleep which means it's no longer listening on triggers. Using the site may cause it to come back to life and start listening to triggers again.
The SDK dashboard will show a warning icon next to functions if the hosting job is not running (it detects this via heartbeats).
Make sure that your website is configured with the "Always On" setting Enabled.
If your site contains continuously running jobs they may not perform reliably if this setting is disabled.
http://azure.microsoft.com/en-us/documentation/articles/web-sites-configure/
By default, web sites are unloaded if they have been idle for some period of time. This lets the system conserve resources. You can enable the Always On setting for a site in Standard mode if the site needs to be loaded all the time. Because continuous web jobs may not run reliably if Always On is disabled, you should enable Always On when you have continuous web jobs running on the site.