I tried to set up my Azure Machine Learning environment on Linux(Ubuntu) data science virtual machine on Azure with this command line:
az ml env setup
However, it shows an error as an error loading command module ml. Been googling about this issue but seems like no one has this issue before.
I can't even see the options by typing:
az ml -h
The only way to run this command it seems is from the:
File > Open Command Prompt
menu item within the desktop software called:
Azure Machine Learning Workbench
The ml option is not available in Azure Cloud Shell or Powershell desktop.
Related
I have install VS code and Node js. In VS code I have add extension for Azure Account. But when I am trying to open Azure Cloud Shell for PowerShell it is showing the below error.
FYI, I am able to access azure cloud shell from azure portal without any problem.
when I am trying to open Azure Cloud Shell for PowerShell it is showing the below error.
I installed Azure tools extension in visual studio code.
Fired this command in terminalAz login, I have already logged-in previously.
For the first time login we need to click on the link and give the code.
Then, I installed node.js extension in the editor and given the npm -v command in the terminal.
It given the latest version of node.
According to Microsoft's Azure documentation.
You have to make an Environment class, and then run a python script configured with this environment.
How do you run a notebook with a specified environment, and not a script?
For example: I want create a notebook in Azure ML and run it with a custom environment.
I am getting Run failed: Unable to establish SSH connection error when I trigger my Published Azure ML Pipeline using Azure Function App while the VM is closed. Normally The Azure ML Pipeline should be able to automatically turn the virtual machine on when I trigger it and close the VM when the process done. Otherwise, it doesn't make any sense.
Sometimes I don't get such an error and the pipeline just works perfectly.
Also, the Pipeline works without a problem when I manually start the VM from AzurePortal before trigger the pipeline.
The Published Pipeline uses Azure Data Science Virtual Machine - Ubuntu. I am using username and password to access the VM.
I totally agree that it would be awesome if ML Service could do this, but fairly certain it isn't supported.
Perhaps you use the function app and the Azure SDK to turnono the DSVM before the pipeline is triggered?
If you're interested in minimizing the time that the VM is running, I highly recommend looking at AMLCompute. Provided you can define the desired runtime environment using either Anacondoa or Docker, you can send the code along with the desired environment to AML Compute and it will automatically spin-up the VM(s) you require and spin them down after. You can also use you environment definition to create the same environment on the DSVM if need be.
My team uses AMLCompute heavily. For me, it solves the problem that I think you're asking.
Need to create azure devops windows self-hosted agents programmatically (Need to install Remotely for the existing VM).
I have PS script and it is working well if i run it (as admin) inside the virtual machine and agent is getting installed successfully. But i want to create this agent for the existing VM without logging in (Remotely i need to install the agent), because i will need to just add the ARM template in Azure devops pipeline and that should create the Agent for the existing VM.
As this needs to be installed remotely and securely, i shouldn't use custom script due to some restrictions.. It would be really great if we can achieve this installation remotely without custom script and using any other automated way.
Any information will be helpful, thanks.
I have found out a way using Run-Command. This is another helpful option to run the PS scripts remotely on a Virtual machine. In addition, this executes the script with elevated permissions which is really helpful in many scenarios.
Source: https://learn.microsoft.com/en-us/azure/virtual-machines/windows/run-command#powershell
This can be performed using via Portal, Powershell and CLI as well.
Is there any way to share a Azure notebook across multiple users who use different notebook VMs? It seems the VMs itself is not shareable across users.
Azure Machine Learning Notebook VM is a part of Azure Machine Learning service, whereas jupyter notebooks on Azure Machine Learning Studio are the part of the Notebook service that runs on Ubuntu 14.04.02 under Docker. With Jupyter in Azure ML Stuido you have the full Anaconda 64-bit distribution available to you.
Thus, if you are willing to share the Azure ML Studio notebook you will need to add a user to your workspace with owner rights.
Notebook VMs has own Jupyter environment and we don't need to use notebooks.azure.com. The former can be used in enterprise scenarios within the team to share the resources, and the latter is open, similar to google colab. When each user login to his notebook VM, there is a top level folder with his/her alias and under that all notebooks are stored. this is stored in an Azure storage and each user's notebook VM will mount same storage. Hence If I want to view other person \'s notebook, I need to navigate to his alias in the Jupyter nb in my nbvm
If you have a look at this example there is a clone button. So when, say, Microsoft DataScientist shares his code all the others may clone his notebook to their own workspace.
After they clone it the url is no longer
https://notebooks.azure.com/ms-ai/projects/Text-Lab/html/Text%20Lab%20-%20workflow%20and%20embedding.ipynb
but
https://notebooks.azure.com/another-user-workspace/projects/Text-Lab/html/Text%20Lab%20-%20workflow%20and%20embedding.ipynb
Does this solve your issue?