Machine learning model retraining on Azure Devops

mdelal 1 Reputation point
2022-10-11T04:59:02.207+00:00

I am building a pipeline Azure Devops. The model is in a .py file which connect to a database to extract training data and output a pickle file with the model.
I would like to trigger this script every time there is a database update.
I use a .yaml file pipeline where I build and run a docker container with the model inside.
I checked the possible way to trigger the .yaml pipeline and could not find a way to do that.
What is the best way to achieve this? Should it be on it's own .yaml pipeline?
I just started to use Azure devops and I am not sure what is the best practice in this case.

Thank you in advance.

Azure Machine Learning
Azure Machine Learning
An Azure machine learning service for building and deploying models.
2,611 questions
0 comments No comments
{count} votes

3 answers

Sort by: Most helpful
  1. JimmySalian-2011 41,926 Reputation points
    2022-10-11T07:47:26.17+00:00

    Hi,

    You can try the Microsoft learn modules, create-a-build-pipeline also try the lab-services Lab Services and this way you can understand the process and test the required deployment process.

    Some of the best practices - phase-rollout-with-rings

    Hope this helps.

    ==
    Please "Accept the answer" if the information helped you. This will help us and others in the community as well.

    1 person found this answer helpful.
    0 comments No comments

  2. mdelal 1 Reputation point
    2022-10-12T03:54:30.937+00:00

    @JimmySalian-2011 Thank you for the answer. I am sorry I am still a bit lost with this. Could you write your guidance here about this. I would like to trigger the script .py which is in a Docker container everytime there is a db update. Using Azure devops, what, where and how should be the trigger please?

    0 comments No comments

  3. mdelal 1 Reputation point
    2022-10-12T04:01:43.71+00:00
    0 comments No comments