I don't know where else to ask this question so would appreciate any help or feedback. I've been reading the SDK documentation for azure machine learning service (in particular azureml.core). There's a class called Pipeline that has methdods validate() and publish(). Here are the docs for this:
https://learn.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.pipeline.pipeline?view=azure-ml-py
When I call validate(), everything validates and I call publish but it seems to only create an API endpoint in the workspace, it doesn't register my pipeline under Pipelines and there's obviously nothing in the designer.
My question: I want to publish my pipeline so I just have to launch from the workspace with one click. I've built it already using the SDK (Python code). I don't want to work with an API. Is there any way to do this or would I have to rebuild the entire pipeline using the designer (drag and drop)?
Totally empathize with your confusion. Our team has been working with Azure ML pipelines for quite some time but PublishedPipelines still confused me initially because:
what the SDK calls a PublishedPipeline is called as a Pipeline Endpoint in the Studio UI, and
it is semi-related to Dataset and Model's .register() method, but fundamentally different.
TL;DR: all Pipeline.publish() does is create an endpoint that you can use to:
schedule and version Pipelines, and
re-run the pipeline from other services via a REST API call (e.g. via Azure Data Factory).
You can see PublishedPipelines in the Studio UI in two places:
Pipelines page :: Pipeline Endpoints tab
Endpoints page :: Pipeline Endpoints tab
Related
Is it possible to pull / clone bitbucket repository within Azure Logic Apps?
I am curious if it is possible to set up some backend tests within Azure Logic Apps. So to pull repo with tests first and then execute them within CLI. I see that there is bitbucket connector in Logic Apps but there is no option to pull the repo. Or should I check some custom connector to run commands from hand like "git clone" etc. - if yes which one?
Azure Logic Apps is a cloud platform where you can create and run automated workflows with little to no code. By using the visual designer and selecting from prebuilt operations, you can quickly build a workflow that integrates and manages your apps, data, services, and systems.
From: What is Azure Logic Apps?
The key concepts here are "little to no code" and "prebuilt operations". Building your code with a CLI and running its tests is not something Logic Apps is targeting. It would also make executing Logic Apps a LOT more complex on the Azure end, since it would mean installing any and all frameworks, tools, etc. that are needed for building the code/running the tests.
If you look at Bitbucket actions that are supported, you can kind of make out that they're all API calls.
What you're looking for is available for free with GitHub workflows
A workflow is a configurable automated process that will run one or more jobs. Workflows are defined by a YAML file checked in to your repository and will run when triggered by an event in your repository, or they can be triggered manually, or at a defined schedule.
or Azure Pipelines.
Azure Pipelines automatically builds and tests code projects. It supports all major languages and project types and combines continuous integration, continuous delivery, and continuous testing to build, test, and deliver your code to any destination.
Potentially interesting read: Build Bitbucket Cloud repositories.
I am working on a data pipeline on Azure Data Factory. Now, the ADF instance I am using is also being used by other developers working on different projects.
I want to deploy my pipeline on a different Azure tenant. However, I want it to be just my Pipeline that is deployed and not any of the others that belong to the other projects.
How can I achieve this? Of course, all of the Datasets, Linked Services and so on that relate to this Pipeline need to be included as well.
I thought the 'Download support files' option was the way to go, but from what I understand, that is used to provide Microsoft with more context when requesting support.
I am fine with a manual export and import for now. But, would it also be possible to version control just my Pipeline? Note that git has not been configured for the ADF instance I am currently using. I did not think it would be possible to just version control a single Pipeline.
You can use export templates at pipeline level
for detailed part :
https://techcommunity.microsoft.com/t5/azure-data-factory-blog/introducing-azure-data-factory-community-templates/ba-p/3650989
I've been setting up a pipeline for our project with Azure Pipeline using yaml. Currently adding review apps with Azure Kubernetes Service and was wondering how we should clean up after the PR is merged.
We are building docker images, pushing them to our registry, deploying them to a new dev space. Then it's all just left there.
After merge we're never going to bed those images again, not like we're going to deploy from a unapproved PR and there's dozens of them every day. We also would like to delete the review app and take down those extra deployments after we're done with them
I can't find anything in the documentation for this. Am I missing something?
I’ve been wondering the same thing, how does one clean-up all the “ephemeral” resources? Seeing the documentation says “ephemeral” I had hoped this functionality was built in.
Even though we trigger on master, I don’t believe there is enough information available in the pipeline to know which PR caused the commit to master, thus we cannot be guaranteed to tear down the correct review app.
I've been working on this today and think I've got it working.
I made a new pipeline that uses the kubectl task to delete the review app namespace, it also uses the azure cli task to run az acr purge to delete the images created for the PR, the tags of which are prefixed with the pr number so it can identify them.
I set this pipeline to not run with CI and not download the source.
Then I made an Azure Function that uses calls the Run Pipeline API to run it, passing the PR number as a variable to the pipeline.
Finally I used Service Hooks to invoke the Azure Function on PR Updated.
The only thing outstanding is the Environment Resource that is created automatically on the DevOps site does not get deleted. I cannot find an API for this so we might have to live with that.
By using browser dev tools and click the delete button in ADO I managed to find out how to delete environment resources using the Azure DevOps Rest API.
You can send:
DELETE <azure-dev-ops-base-url>/<organization>/_apis/distributedtask/environments/{environment-id}/providers/kubernetes/{resource-id}?api-version=6.0-preview.1
To find environment-id and resource-id use:
GET: <azure-dev-ops-base-url>/<organization>/_apis/distributedtask/environments?api-version=6.0-preview.1
GET: <azure-dev-ops-base-url>/<organization>/_apis/distributedtask/environments/{environment-id}?expands=resourceReferences&api-version=6.0-preview.1
Based on the following design I want to launch a Terraform file and an application code on Azure DevOps when an Azure Functions trigger the Pipeline.
Do you know any example to do a normal API REST Call to A. Dev Ops?
(using Python or JS)
Do you think it is a good strategy to generate an orchestration pipeline to make the workflow of the infrastructure and later on the application code?
In order to deploy the application
code, how can I modify it using the arguments coming from the API?
architecture design
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.