I'm generating a machine learning modell using Azure Auto ML. Is there a way to update my published real-time endpoint without deleting it first?
Thanks in advance.
One approach with current integration between Azure ML and Azure DevOps is to setup a release pipeline in Azure DevOps which is triggered by the model registration in your Dev workspace model registry.
There is guidance and examples in this repo
https://github.com/Microsoft/MLOpsPython
And more general guidance for MLops at http://aka.ms/mlops
Please follow the below for retraining.
https://learn.microsoft.com/en-us/azure/architecture/reference-architectures/ai/mlops-python#retraining-pipeline
Related
I have an existing app service running on Azure that I previously published directly from Visual Studio. I am trying to get to grips with using DevOps and was wondering if it is possible to add a CI/CD pipeline to an existing app service.
I have seen a lot of tutorials on the web about how to create a pipeline for a new app service (many, of course, are out of date and do not actually relate to what one sees in the Azure portal!) So far, though, I have not come across anything about adding this to an existing app service.
Any advice or links to handy tutorials would be greatly appreciated!
I am hoping that the answer is not delete the existing service and start again from scratch!
If you are a beginner on Azure Devops, I will recommend to use the Azure Devops Starter project to create a pipeline, you can pick AppService as the deployment.
Once the pipelines are created on the Azure Devops , just open the pipeline and select the existing AppService where you want to deploy and also the source from where you want to pull the code. This makes easier rather than creating the stuffs from the scratch.
I read some articles with deployment examples and they were about deploying one model but not a whole deep learning system.
If I want to deploy my project including launch of multiple deep models built with different frameworks (Pytorch, tensorflow) then what's good option for that:
build Docker image with whole project and deploy it with ml
service (azure, aws lambda etc);
or deploy every single model with
chosen MLaaS and and elsewhere deploy the logic that makes requests
to the above models;
I would appreciate any reference/link on the subject.
Thanx.
We have public open source release of Many Models solution accelerator. The accelerator is now available on GitHub and open to everyone: Many Models: https://aka.ms/many-models.
• Check out a blog on Many Models from MTC AI Architect Sam here
Check this document using designer: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-model-designer? Basically you can register a trained model in Designer bring it out with SDK/CLI to deploy it.
One approach with current integration between Azure ML and Azure DevOps is to setup a release pipeline in Azure DevOps which is triggered by the model registration in your Dev workspace model registry which them deploys to your Prod workspace.
There is guidance and examples in this repo
https://github.com/Microsoft/MLOpsPython
And more general guidance for MLops at http://aka.ms/mlops
This also allows for putting integration tests into your release process or other steps like approval processes if needed using DevOps functionality.
So far our team is using Azure DevOps to manage our code and we have created some pipelines to deploy the code to Web App in Azure Global (East Asia).
And now we need to deploy the code to Web App in Azure China.
Azure China is not totally same as Azure Global, we still want to create some new pipeline to do the deployment to Azure China, I want to know whether it can be achieved.
I didnot try it out myself. But it seems possible. You can refer to the detailed steps as described in this documents. Obviously the documents is little out of date, it gave an example for VSTS project which is the older version of Azure devops. But you can follow the steps and give it a shot.
The official site here lists below channels if you require assistance:
Online submission
MSDN forum support (in Chinese)
WeChat support (ID: VNET_AzureSupport)
I have created Azure Data Factory with Copy Activity using C# and Azure SDK.
How can deploy it using CI/CD ?
Any URL or link will help
Data Factory continuous integration and delivery is now possible with directly through the web user interface using ARM Templates or even Git (Github or Azure DevOps).
Just click on "Set up Code Repository" and follow the steps.
Check the following link for more information, including a video demostration: https://aka.ms/azfr/401/02
One idea that I got from Microsoft was that using the same Azure SDK you could deserialize the objects and save down the JSON files following the official directory structure into your local GitHub/Git working directory
In other words you would have to mimic what the UI Save All/Save button does from the portal.
Then using Git bash, you can just commit and push to your working branch (i.e. develop) and from the UI you can just publish (this will create an adf_publish release branch with the ARM objects)
Official reference for CI using VSTS and the UI Publish feature: https://learn.microsoft.com/en-us/azure/data-factory/continuous-integration-deployment
Unfortunately, CI/CD for ADF is not very intuitive at first glance.
Check out this blog post where I'm describing what/how/why step by step:
Deployment of Azure Data Factory with Azure DevOps
Let me know if you have any questions or concerns and finally - if that works for you.
Good luck!
My resources on how to enable CI/CD using Azure DevOps and Data Factory comes from the Microsoft site below:
Continuous integration and delivery (CI/CD) in Azure Data Factory
I am still new to DevOps and CI/CD, but I do know that other departments had this set up and it looks to be working for them.
I am using Azure integration with tfs.visualstudio.com for automated deployment after every checkin. As part of my solution, i have a database project (VS 2012) which i want to deploy on sql azure instance after a successful build but before the unit tests are triggered. I am unable to figure out how is that possible with azure. Someone please help me out here.
One possible solution is described here:
http://www.windowsazure.com/en-us/develop/net/tutorials/web-site-with-sql-database/