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Azure Pipelines Download None

Started byEsperanza Santrizos <santrizose@gmail.com>
First post2024-01-01 03:38 -0800
Last post2024-01-01 03:38 -0800
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  Azure Pipelines Download None Esperanza Santrizos <santrizose@gmail.com> - 2024-01-01 03:38 -0800

#83550 — Azure Pipelines Download None

FromEsperanza Santrizos <santrizose@gmail.com>
Date2024-01-01 03:38 -0800
SubjectAzure Pipelines Download None
Message-ID<9fa749f0-8a82-41f7-b706-60de7fafdcadn@googlegroups.com>
I'm new to CICD pipeline and studying it with an existing pipeline used by our company.In the main yaml script that runs the pipeline, I found trigger:none,I looked up a document and it says it disables CI triggers..but I'm not really sure what it means. it disables triggering pipeline but why do we need it and why do we need to disable it?


But I only focus on the logic part at this time, the trigger is not important in this case, of course I can "seriously" write a complete and detailed CI trigger, but it is not necessary, I only care about the logic part, trigger: none only spends me one second.



azure pipelines download none

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This is part of the MAIN Pipeline YAML as example. I have specified trigger: none and pr: none for all pipelines where this occurs.I've also tried the different combinations with the commented out triggers on the resources.


YAML pipelines are configured by default with a CI trigger on all branches, unless the Disable implied YAML CI trigger setting is enabled. The Disable implied YAML CI trigger setting can be configured at the organization level or at the project level. When the Disable implied YAML CI trigger setting is enabled, CI triggers for YAML pipelines are not enabled if the YAML pipeline doesn't have a trigger section. The default value for Disable implied YAML CI trigger is false.


However, whenever I go the proper route and create a new PR (on GitHub), I get two pipelines triggered: pr_pipeline and release_pipeline, both at the same time. release_pipeline shouldn't get triggered, obviously.


To better understand the problem I created a two brand new separate Azure DevOps projects and built two pipelines: one using the classic interface, the second using YAML. Also, I made the testing easier and I just read all the comments.


For each of the available scopes, shown in the table below, you can assign one of the permissions: read, write, or none. If you specify the access for any of these scopes, all of those that are not specified are set to none.


I am using Fortify SC SAST Assessment extension in Azure DevOps pipeline to trigger the SAST scan. However, as the framework of the source code is not supported, I had to specify the Build tool = none.






However, as I am scanning microservice, I need to specify the path or source code directory of the scanning in which Fortify SAST does not provide in this extension for the case when we choose Build tool = none.


Keep two YAML pipelines: one is triggered on every commit to the main branch and includes only Build and TEST, another one is triggered manually and includes all stages, here you can specify stages to run.Downside: maintenance of two pipelines.


Keep two pipelines: YAML + Classic. Set up Classic Web UI Release Pipeline to deploy to higher environments (in our case TEST and PROD). In this approach we keep Build and DEV stages in yaml definition and TEST and PROD in classic release. Classic pipelines documentation.Downside: definition is spread across different places, classic release definition is not in source control.


We are seeing a problem with a few of our projects where the pipeline completes all stages successfully, but none of the stages do anything. Indeed, they do not even fetch the repo or artifacts (as the modification time of the gitlab-runner home directory does not change).


This feature gives you more control over the pipelines you create and you can also avoid duplicating or refactoring your pipeline to fit according to the need. You will find a more realistic example based on my previous tutorial series inside this Github repository. Feel free to adapt this example to your projects needs. This is a really useful feature so it would be a shame to not use it!


Use the Azure DevOps Demo Generator to provision the project on your Azure DevOps organization.This URL will automatically select Azure Key Vault template in the demo generator. If you want to try other projects, use this URL instead -azuredevops generator


You need to authorize the pipeline to deploy to Azure. Azure pipelines can automatically create a service connection with a new service principal, but we want to use the one we created earlier. Click Manage, this will redirect to the Service connections page.


Delta Live Tables is a framework for building reliable, maintainable, and testable data processingpipelines. You define the transformations to perform on your data, and Delta Live Tables manages taskorchestration, cluster management, monitoring, data quality, and error handling.


Instead of defining your data pipelines using a series of separate Apache Spark tasks, Delta Live Tablesmanages how your data is transformed based on a target schema you define for each processing step. You canalso enforce data quality with Delta Live Tables expectations. Expectations allow you to define expecteddata quality and specify how to handle records that fail those expectations.


Owner: The owner of the resource. The owner controls where the resource goes when it is deployed. The owner alsocontrols the resources lifecycle. When the owner is deleted the resource will also be deleted. Owner is expected to be areference to a resources.azure.com/ResourceGroup resource


The problem is that any user may create a new branch off main and add malicious (or accidental) code to the azure-pipelines.yml. For example, if I create a new branch called malicious-change with azure-pipelines.yml changed to:


Because we unticked the allow access to all pipelines box, it will mean the owner (or someone with enough permissions) will be asked to approve the use of the variable group and Key Vault service connection the first time the pipeline is run:


The final improvement is to make use of the Azure DevOps Environments feature. This allows us to define an environment to target when using a deployment job of an Azure DevOps Multi-stage YAML pipeline. With the environment defined, we can assign approvals & checks to that, just like we did with the Service Connections and limit permissions to the environment to specific pipelines.

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