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Azure DevOps Pipelines: If Expressions and Conditions

Developer Support

February 16th, 2023 1 2

John Folberth continues his series on Azure DevOps Pipelines by taking a deep dive into If Expressions and Conditions.

At this stage in the series we’ve talked about tasks, jobs, stages, how to template them, and how to leverage environments in variables. This post will attempt to cover some basics around using if and conditions in your YAML Pipelines.  

If Expressions

If expressions  are simple and easy enough in YAML pipelines, they are a powerful tool. In my experience I have leveraged if expressions to:  

• Conditionally load templates  
• Dynamically load variables  
• Enable same pipeline for CI/CD  

The key to unlocking their power is the understanding that an if expression will evaluate at pipeline compilation. This means the pipeline has to leverage known values to apply the logic within. We should not use an if expression when relying on the output of another task/job, the status of another job, or a variable that is updated during pipeline execution.  

The other side of this, since the statement is evaluated at pipeline compilation time, is that we will not load any unnecessary templates into our pipelines. As opposed to conditions, which will we cover next, templates will not appear in the expanded pipeline YAML file. This leads to a cleaner and more secure experience since only what will be executed will appear in the pipeline logs.

Continues reading the full post here and check out the series on the Microsoft Health and Life Sciences Blog .  

Developer Support Cloud Solution Architects, Microsoft Customer Success

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Developer Team,

I want to customize News webpart using SharePoint Framework. I need to get hub associated sites News into webpart and display, i am using v2.1 getNewsFeed api. didn’t find any article related to it. Could some one help me how to expose?

try { var siteURL = this.props.context.pageContext.web.absoluteUrl;

this.props.context.spHttpClient .get( siteURL + // tokenresource + // `_api/v2.1/getNewsFeed?section=SharePointNewsFeedTargeted&$expand=analytics($expand=allTime),thumbnails&$skiptoken=${token}&$top=13`, `/_api/v2.1/getNewsFeed?section=SharePointNewsFeedTargeted&$expand=analytics($expand=allTime),thumbnails&$top=13`, SPHttpClient.configurations.v1, { headers: { ‘authorization’: `Bearer ${token}`, ‘sphome-apicontext’: `{“PortalUrl”:”${siteURL}”}` // ‘sphome-apicontext’: `{“PortalUrl”:”${tokenresource}”}` }} ) .then((responseObj: SPHttpClientResponse) => { responseObj.json().then((responseJSONObj) => { console.log(JSON.stringify(responseJSONObj)); }); }); } catch (ex) { console.warn(ex); }

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Conditional Variables in Azure DevOps Pipelines

Creating Azure DevOps Pipelines, have you used a condition to determine which variables to use? If not, I will detail in this blog post how you can do this!

What is a condition?

Conditions or statements that are used to determine an outcome; used widely in programming.

Some examples of conditions:-

• If today is Monday then true – if not, false!
• If branch is main, then run task
• If the sky is blue, echo “hello”

All various examples of conditions!

Now, lets look at using conditional variables with your Azure DevOps Pipelines!

Are they useful? Very! I have built alot of pipelines & do tend to use quite a few types of conditions, in this blog post I will detail conditional variables, but will add more blog posts later with other ways to use conditions – they can used in jobs, steps, stages etc too!

In my example, I am going to use a parameter to decide on which teamName I want to be displayed in my Bash@3 task, lets step it out

The parameter “environment”, will be asked at run-time

Now my variables, which are conditional depending on the parameter input, depending on the value of parameter.environment will decide which of the three teams: alpha, beta, charlie will be set to the variable.teamName

Notice the last value (lines 7-8)?

I have used notIn, rather than a third iteration of if – I tend to do this; to have a catch-all!

Now as mentioned, the variable is conditional – depending on the parameter.environment name, the stage will echo the required variable

Lets run the pipeline, as mentioned above – The parameter “environment”, will be asked at run-time

Reviewing the task output in Azure DevOps

We can see the variable it uses is beta, the conditional for parameter.environment preproduction!

Awesome! Hopefully this blog post has given you an insight into using Conditional Variables in Azure DevOps Pipelines

Full pipeline used below and can also be found in GitHub

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Azure DevOps Pipelines: Conditionals in YAML

In this week’s post, we are going to cover some ways to make tasks and jobs run conditionally. This will include options such as Pipeline variables to jobs that are dependent on other jobs. This post will be using a sample Azure DevOps project built over the last few weeks of posts. If you want to see the build-up check out the following posts.

Sample YAML

The following YAML is based on the YAML from the previous posts, see links above, expanded with examples of using some ways of conditionally running some task or job. This is the full file for reference and the rest of the post will call out specific parts of the file as needed.

Job Dependencies

The more complex pipelines get the more likely the pipeline will end up with a job that can’t run until other jobs have completed. The YAML above defines three different jobs, WebApp1, WebApp2, and DependentJob. I’m sure you have guessed by now that the third job is the one that has a dependency. To make a job dependent on other jobs we use the dependsOn element and list the jobs that must complete before the job in question can run. The following is the YAML for the sample DependentJob with the dependsOn section highlighted.

With the above setup, DependentJob will only run if both the WebApp1 and WebApp2 jobs complete successfully.

Conditions are a way to control if a Job or Task is run. The following example is at the job level, but the same concept works at the task level. Notice the highlighted condition .

The above condition will cause the WebApp2 job to be skipped if the BuildWebApp2 variable isn’t true. For more details on how to use conditions see the Conditions docs .

Creating a Pipeline Variable

The rest of the post is going to walk through creating a Pipeline variable and then running some sample builds to show how depends on and the conditions defined in the YAML above affect the Pipeline results.

We are starting from an existing pipeline that is already being edited. To add (or edit) variables click the Variables button in the top right of the screen.

The Variables pop out will show. If we had existing variables they show here. Click the New variable button to add a new variable.

We are adding a variable that will control the build of WebApp2 called BuildWebApp2 that defaults to the value of true . Also, make sure and check the Let user override this value when running this pipeline checkbox to allow us to edit this variable when doing a run of the pipeline. Then click the OK button.

Back on the Variables dialog click the Save button.

Edit Variables When Starting a Pipeline

Now that our Pipeline has a variable when running the Pipeline under Advanced options you will see the Variables section showing that our Pipeline has 1 variable defined. Click Variables to view/edit the variables that will be used for this run of the Pipeline.

From the Variables section, you will see a list of the defined variables as well as an option to add new variables that will exist only for this run of the Pipeline. Click on the BuildWebApp2 variable to edit the value that will be used for this run of the Pipeline.

From the Update variable dialog, you can change the value of the variable. When done click the Update button.

Pipeline Results from Sample YAML

The following is what our sample Pipeline looks like when queued with the BuildWebApp2 variable set to false. As you can see the job will be skipped.

Next is the completed results of the Pipeline run. You can see that the Build Dependent Job was skipped as well since both Build WebApp1 and Build WebApp2 must complete successfully before it will run.

Changing the BuildWebApp2 variable back to true and running the Pipeline again results in all the jobs running successfully.

Wrapping Up

Hopefully, this has helped introduce you to some of the ways you can control your Pipelines. As with everything else Azure DevOps related things are changing a lot and new options are popping up all the time. For example, while writing this post the team just announced Runtime Parameters which look like a much better option than variables for values that frequently vary between Pipeline runs.

Also published on Medium .

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I'm Andrew Hoefling, and I work for FileOnQ as a Lead Software Engineer building mobile technologies for Government, Financial and First Responders using Xamarin. 

Conditional Insertion in Azure Pipelines

Using Conditional Insertion in Azure Pipelines allows a build to insert tasks depending on parameters. This differs than a conditional task becaues it can remove or add the task to the build task list. This means you can completely customize the build tasks and only show the ones that the build is interested in.

Conditional Tasks != Conditional Insertion

When defining project builds for Azure Pipelines it is common to have tasks run if a certain criteria is true. This technique is called conditions and it can be applied to any task. Some options available in a condition are:

• Prevent task from running
• Run task even if build failed
• Allow task to run if a criteria is true

In all cases with Conditions the build task still shows up in the build history. When building large yaml builds this can create a lot of noise that will make it difficult to debug the problem.

Standard Condition Example

What is Conditional Insertion?

Conditional Insertion uses a similar expression syntax as a standard Task Expression, with one major exception. If the statement evaluates to false the task is not added to the build task list. This means the task will only show up if the expression evaluates to true.

The syntax is a little tricky to get right

Conditional Insertion uses the  ${{ }} notation and is a little confusing at first glance. It is adding code flow to yaml which combines a couple different paradigms: configuration files and code. It is best to think of conditional insertion as an if statement inside of your build task list.

• Azure DevOps Conditional Insertion Docs

The most basic example provided by the microsoft docs is changing a variable based on a conditional insertion. See the code snippet below:

Breaking this syntax down the actual expression is

Let's analyze the different components that make up a conditional insertion statement

Open and Closing braces

• Closing colon

Anytime you attempt to access parameters or the code flow of Azure Pipelines yaml files you use the ${{ }} . Conditional Insertions are no different with one major exception

Boolean Expression

To implement the Conditional Insertion you will need to add an if statement into the code block. The rules can match identically to the Condtion that you have used in the past. The major difference is you need to explicitly list out the if command and then your boolean expression.

Closing Colon

This is the most important part of Conditional Insertion without it your yaml files will fail with little explanation. After the opening and closing braces ${{ }} you will need to include colon : which tells the build system to only insert the next statement if the expression evaluates as true.

Let's compare 2 different conditional statements:

Valid Expression

  Invalid Expression  - missing trailing colon

Add Condtional Task

Let's look at how we can apply this concept to a build script to conditionally add tasks. Then we can look at the build output to demonstrate when a task is added to the build task list and when it is not. Before we learned using the ${{ }} code block we can conditionaly insert statements into a yaml file. This same concept can be applied to tasks with a few changes and proper indenting.

Consider the following yaml file that has 2 tasks that run a script to print a message to the console.

Let's add a parameter to the script that will determine if the 2nd task will execute or not.

Before we add the Conditional Insertion you need to be aware that of a couple rules

• All task statements start with a  -
• All statements following the Conditional Insertion is indented 2 spaces

Putting all of this together we can update our 2nd task as follows

Now putting the entire script together

Troubleshooting

Creating builds with yaml is powerful and confusing, you are bound to run into an error that has no explanation. Below are some tips that may help you get through issues you run into.

Missing Dash

If you are using Conditional Insertion for a task you must have a - leading the statement otherwise the build will not work. The steps definition in your build expects an array of items the - syntax tells the build system that you are evaluating a new item in the array.

Missing Trailing Colon

All Conditional Insertion statements must end with a colon : . The colol tells the build system that the next line will be inserted if the expression evaluates to true.

Invalid Spacing

The infamous spacing of yaml files has caused hours upon hours of frustration for developers. Conditional Insertion adds potential problems with spacing. All statements after the expression must have an additional 2 spaces.

You should have the knowledge to add statements conditionally to your build yaml file using Conditional Insertion. This can be applied to parameters, variables, steps and more. If you want to see a working example, checkout my code sample on GitHub

• https://github.com/ahoefling/Conditional-Insertion

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Azure DevOps: Conditional variable value in pipeline

Azure DevOps pipeline have tons of feature, one of the less known is the ability to declare variable conditionally.

Let’s examine a simple situation, in Azure DevOps you do not have a way to change pipeline priority, thus, if you need to have an agent always ready for high-priority builds, you can resort using more agent Pools . Basically you have N license for pipeline, so you can create N-1 agents in the default Pool and create another pool, lets call it Fast, where you have an agent installed in a High Performance machine . When you need to have a pipeline run that has high priority you can schedule to run in Fast Pool and the game is done.

Doing this is super simple thanks to Pipeline parameters, but I have another interesting scenario. I have many builds of internal libraries used by teams, then when someone publish a stable version for a library, we want this library to be complied and pushed to internal Nuget as soon as possible

Time needed to publish internal library in stable version should be low.

When you have many internal libraries, it is normal to

• Create a branch on library repository
• Implement a new feature with all UnitTest
• Ask for a Pull Request
• Close everything on main/master and use the new feature in some software

Since these are internal utility, you usually add a new feature because you have a project that needs that feature. Sometimes the feature is a simple extension method or a really simple new helper function and you really do not want to wait 1 hour because you push main/master in a moment where you have high amount of build.

The solution I want is being able to automatically schedule pipeline execution **on Fast Pool if I’m compiling main/master branch”. This flow seems to me the most natural one, lets the stable version of the code have use high priority queue, while all other checks still run on default queue where developers does not care to wait for a result.

Parameters allow the user to choose a value during manual trigger, but when the pipeline is triggered automatically by a push, default value is used , so in the above situation all runs due to push are executed into the default pipeline.

What I want is being able to choose the pool to be used based on branch name

Actually I’m used to define a variable for each parameter, so I can access everything with the usual $(VariableName) notation.

This allows for a really simple solution, because you can set variable values with conditions, thanks to powerful syntax of Azure DevOps pipelines . Here is the final code.

The syntax could seems strange, but thanks to the ${{ if instruction I’m able to use condition directly in the yaml file . This allows me to tell the engine that, if the parameter Pool is fast or if the Build.SourceBranch is the master branch I want the value of the variable Pool to be equal to fast . Condition are evaluated before the pipeline is actually executed, and basically allows you to set part of the YAML file with condition.

YAML condition in Azure DevOps pipeline are evaluated before scheduling the run, so they are allowed to select the pool.

This is important because the engine, first of all evaluates all the conditional YAML part, then when everything was determined, it proceed to analyze YAML content, and schedule the execution on the right pool.

To diagnose what is happening, after the build is completed you can download all log in zipped format, because it contains the initializeLog.txt file that contains log of the initialization . That file is really useful because, as you can see from Figure 1, it contains all checks and condition and expansions that are done before actually executing the pipeline.

Figure 1: Check initialization of the pipeline

Then do not forget to look at the azure-pipelines-expanded.yaml files that contains the result yaml file after all expansions and conditions were evaluated . These two files are invaluable to diagnose problem when you use some advanced configuration like conditional variables.

In the end the result is obtained, each time that a run is triggered from the master branch, it will be scheduled automatically on Fast pool.

Gian Maria.

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Azure DevOps Experimentation - YAML Conditionals, Parameters, and Triggers

Snippets of common questions and issues from Azure Pipeline workshops and support calls. Today's snippet includes conditionals, parameters, and triggers.

If you are an avid user of the YAML-based Azure Pipelines, you will be aware that the language can be very pedantic when it comes to too many or too few spaces. In fact, we have been mulling over a broken pipeline for (what felt like) hours, only to realise that we were misaligned by one space. Fortunately, both the YAML editor in both Azure DevOps and Visual Studio Code, as well as the Validate features are continuously improving.

Let us park the spaces topic and focus on conditionals, parameters, and triggers, using this simple sample code.

Experimentation Sample Code

You can configure a trigger to fire manually , never , or as changes are made to selected branches, tags, and folders.

• If you remove the trigger all together, the pipeline will be triggered if any change is made to any folder or branch .
• If you want to have a manually triggered pipeline, you must configure - none , as in today's sample code.

See Triggers for details.

You can use parameters in templates and pipelines, as visualised on our YAML Generic Blueprint-based Pipeline Quick Reference and documented in detail in the YAML Schema .

• Parameter key:value pairs are evaluated at queue time.
• You can define a pipeline parameter, as in the sample code above.
• When you run the sample pipeline, you can select from the available values, as shown:

See Parameters for details.

You can add static values, reference variable groups, or insert variable templates into your pipeline.

• Variable key:value pairs are evaluated at run time.
• Echo 1 is boring, but we must say hello!

Output: keyFinal .

Output: Bingo!

See Variables for details.

Conditionals

Lastly, conditions can be used to determine whether tasks should execute or if code or entire template are injected into the pipeline at queue time.

• # Lower demonstrates how to include tasks if certain conditions are met. In our sample, we check if the selected parameters.branch is equal to 'release'. If yes, Bingo!
• Note how we convert the parameter to lowercase before doing the comparison, so that any combination of casing for release will meet the condition.
• Release only demonstrates how to include tasks if and only if the origin source branch matches refs/heads/release or starts with refs/heads/release/ .

We make extensive use of conditions in our blueprints and re-usable toolkit templates.

See Expressions for details.

We are done for today.

Hope these snippets are adding value and looking forward to your candid feedback. See you in the next experiment.

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Conditionally Deploying YAML Pipelines In Azure Devops By Branch

Apologies for the absolute word soup of a title above, but I wasn’t sure how else to describe it! So instead, let me explain the problem I’ve been trying to solve lately.

Like many organizations using Azure Devops, we are slowly switching our pipelines to use YAML instead of the GUI editor. As part of this, I’ve been investigating the best way to conditionally deploy our CI build to environments. Notably, I want our CI build to run for every check in, on every branch, but only move to the “release” stage if we are building the develop branch and/or the main trunk. As we’ll find out later, there also needs to be an override mechanism for this because while it’s a general rule, it’s also something that may need to be flexed at times.

YAML pipelines documentation can be a bit shaky at times, so most of this came from trial and error, but here’s what I found to solve the problem of conditionally deploying Azure Pipelines based on a branch.

Using Environments

Your first option is to use Environments inside Azure Devops. You can add an “Approval and Check” to an environment, and then select Branch Control.

You can then specify a comma seperated list of branches that are allowed to pass this environment gate, and be deployed to the environment :

But here’s the problem I had with this approach. Environment gates such as the above are not in source control. Meaning that it’s hard to roll out across multiple projects at once (Compared to copy and pasting a YAML file). Now that’s a small issue, but the next one is a big one for me.

These checks based on a branch actually *fail* the build, they don’t “skip” it. So for example, if a branch does not match the correct pattern, you will see this :

This can be incredibly frustrating on some screens because it’s unclear whether your build/release pipeline actually failed, or it just failed the “check”. There is also no way to override this check on an adhoc basis. Maybe that’s something you desire, but there are rare cases where I actually need to deploy a feature branch to an environment to test something, and going through the GUI to disable branch control, release, then add it back just doesn’t make sense.

Using Pipeline Variables

A more explicit way I found to control this was to use variables inside the YAML itself. For example, every project of mine currently has the following variables utilized :

Now anywhere in my pipeline, I can use either variables.isPullRequest or variables.isDevelopment and make conditional deployments based on these. For example, I can edit my YAML to read like so for releasing to my development environment :

This basically says, the previous steps must have succeeded *and* we must be using the development branch. When these conditions are not met, instead of a failure we see :

This is so much nicer than a failure and actually makes more sense given the context we are adding these gates. I don’t want the CI build to “fail”, I just want it to skip being released.

Adding Overrides

Remember how earlier I said that on occasion, we may want to deploy a feature branch even though it’s not in develop? Well we can actually add an override variable that when set, will push through the release.

First we must go to our YAML pipeline in Azure Devops , and edit it. Up the top right, you should see a button labelled Variables. Click it and add a new variable called “forceRelease” like so :

Unfortunately, we have to do this via the GUI for every build we wish to add this variable. At this time, there is no way to add it in the YAML and have Azure Devops recognize it (But there is hope for the future!).

In our YAML, we don’t need to declare the variable ourselves, instead it’s just available for use immediately. We can just modify our Development stage to look like so :

Now we are saying, if the branch is development or the variable forceRelease is set to true, then push through the release. If we try and kick off a build, we can now set the runtime variable at build time to push things through, no matter the branch.

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Using conditions to control job execution

Prevent a job from running unless your conditions are met.

Note: A job that is skipped will report its status as "Success". It will not prevent a pull request from merging, even if it is a required check.

You can use the jobs.<job_id>.if conditional to prevent a job from running unless a condition is met. You can use any supported context and expression to create a conditional. For more information on which contexts are supported in this key, see " Contexts ."

Note: The jobs.<job_id>.if condition is evaluated before jobs.<job_id>.strategy.matrix is applied.

When you use expressions in an if conditional, you can, optionally, omit the ${{ }} expression syntax because GitHub Actions automatically evaluates the if conditional as an expression. However, this exception does not apply everywhere.

You must always use the ${{ }} expression syntax or escape with '' , "" , or () when the expression starts with ! , since ! is reserved notation in YAML format. For example:

For more information, see " Expressions ."

Example: Only run job for specific repository

This example uses if to control when the production-deploy job can run. It will only run if the repository is named octo-repo-prod and is within the octo-org organization. Otherwise, the job will be marked as skipped .

On a skipped job, you should see "This check was skipped."

Note: In some parts of the workflow you cannot use environment variables. Instead you can use contexts to access the value of an environment variable. For more information, see " Variables ."

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Conditional insertion in YAML templates with variables at build time Azure DevOps

Is there a way to use varaiables defined in the pipeline(dashboard) to use conditional insertion on a YAML template for steps:

I mean i have this steps:

This should run when the variable is not being declared

This should run when the variable is declared

I know that it exist the Runtime parameters , but i don't want to use them every time that i run the pipeline (manually).I want that some pipelines run some steps, when i have declared the variable, and some other pipelines don't run some steps when the variable is not being declared.

I also know that it exist the condition inside every step like

But i want to use conditional insertion to run in some cases, many steps like in the examples above. Not in just one step

• azure-devops
• multistage-pipeline

I want that some pipelines run some steps, when i have declared the variable, and some other pipelines don't run some steps when the variable is not being declared.

Why not use the Runtime parameters ? With the Runtime parameters used we can simply achieve your requirement.

Whatever, to achieve that by using the variables we can try to Specify condition for the Yaml templates:

Create Yaml templates :

And the azure-pipelines.yml for your reference :

Thus, It will run windows job if you declared the variable when run pipeline. Otherwise it will run the Linux job in this example.

• I think runtime parameters are used , when you just want to skip a job or a sequence of steps that are not working but you need to run the pipeline. Example a pipeline that have an Integraion a Migration Job and a Deploy Job , Sometimes you need to deliver as quick as possible the Deploy so manually you skipp the integration job with Runtime parameters . But what about pipelines that you want to run with ci/cd where you simply don't have that job Integration but in other pipelines similar you have it –  Zahid Commented Jul 20, 2020 at 14:46
• Thanks for the clarification. So, you mean that we can only specify the parameters when run the pipeline manually, but for CI/CD, no way to specify them, right? However, according to your description, even with using the variable we still have to declare the variable manually. It's still not available for CI/CD. Please correct me if any misunderstanding. –  Andy Li-MSFT Commented Jul 21, 2020 at 2:03

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steps.checkout definition

• 3 contributors

Use checkout to configure how the pipeline checks out source code.

Definitions that reference this definition: steps

checkout string. Required as first property. Configures checkout for the specified repository. Specify self , none , repository name , or repository resource . For more information, see Check out multiple repositories in your pipeline .

If no checkout step is present, it defaults to self for jobs.job.step.checkout and none for jobs.deployment.steps.checkout .

checkout string. Required as first property. Whether or not to check out the repository containing this pipeline definition. Specify self or none .

clean string. If true, run git clean -ffdx followed by git reset --hard HEAD before fetching. true | false.

fetchDepth string. Depth of Git graph to fetch.

fetchTags string. Set to 'true' to sync tags when fetching the repo, or 'false' to not sync tags. See remarks for the default behavior.

lfs string. Set to 'true' to download Git-LFS files. Default is not to download them.

persistCredentials string. Set to 'true' to leave the OAuth token in the Git config after the initial fetch. The default is not to leave it.

submodules string. Set to 'true' for a single level of submodules or 'recursive' to get submodules of submodules. Default is not to fetch submodules.

path string. Where to put the repository. The root directory is $(Pipeline.Workspace).

condition string. Evaluate this condition expression to determine whether to run this task.

continueOnError boolean . Continue running even on failure?

displayName string. Human-readable name for the task.

target target . Environment in which to run this task.

enabled boolean . Run this task when the job runs?

env string dictionary. Variables to map into the process's environment.

name string. ID of the step. Acceptable values: [-_A-Za-z0-9]*.

timeoutInMinutes string. Time to wait for this task to complete before the server kills it.

Pipelines may be configured with a job level timeout. If the job level timeout interval elapses before your step completes, the running job (including your step) is terminated, even if the step is configured with a longer timeoutInMinutes interval. For more information, see Timeouts .

retryCountOnTaskFailure string. Number of retries if the task fails.

Shallow fetch

Clean property.

New pipelines created after the September 2022 Azure DevOps sprint 209 update have Shallow fetch enabled by default and configured with a depth of 1. Previously the default was not to shallow fetch. To check your pipeline, view the Shallow fetch setting in the pipeline settings UI .

To disable shallow fetch, you can perform one of the following two options.

• Disable the Shallow fetch option in the pipeline settings UI .
• Explicitly set fetchDepth: 0 in your checkout step.

To configure the fetch depth for a pipeline, you can either set the fetchDepth property in the checkout step, or configure the Shallow fetch setting in the pipeline settings UI .

If you explicitly set fetchDepth in your checkout step, that setting takes priority over the setting configured in the pipeline settings UI. Setting fetchDepth: 0 fetches all history and overrides the Shallow fetch setting.

If the clean property is unset, then its default value is configured by the clean setting in the UI settings for YAML pipelines, which is set to true by default. In addition to the cleaning option available using checkout , you can also configure cleaning in a workspace. For more information about workspaces and clean options, see the workspace topic in Jobs .

The checkout step uses the --tags option when fetching the contents of a Git repository. This causes the server to fetch all tags as well as all objects that are pointed to by those tags. This increases the time to run the task in a pipeline, particularly if you have a large repository with a number of tags. Furthermore, the checkout step syncs tags even when you enable the shallow fetch option, thereby possibly defeating its purpose. To reduce the amount of data fetched or pulled from a Git repository, Microsoft has added a new option to checkout to control the behavior of syncing tags. This option is available both in classic and YAML pipelines.

Whether to synchronize tags when checking out a repository can be configured in YAML by setting the fetchTags property, and in the UI by configuring the Sync tags setting.

To configure the setting in YAML, set the fetchTags property.

To configure the setting in the pipeline UI, edit your YAML pipeline, and choose More actions , Triggers , YAML , Get sources , and check or uncheck the Sync tags checkbox. For more information, see Sync tags .

Default behavior

• For existing pipelines created before the release of Azure DevOps sprint 209 , released in September 2022, the default for syncing tags remains the same as the existing behavior before the Sync tags options was added, which is true .
• For new pipelines created after Azure DevOps sprint release 209, the default for syncing tags is false .

A Sync tags setting of true in the UI takes precedence over a fetchTags: false statement in the YAML. If Sync tags is set to true in the UI, tags are synced even if fetchTags is set to false in the YAML.

To avoid syncing sources at all:

If you're running the agent in the Local Service account and want to modify the current repository by using git operations or loading git submodules, give the proper permissions to the Project Collection Build Service Accounts user.

To check out multiple repositories in your pipeline, use multiple checkout steps:

For more information, see Check out multiple repositories in your pipeline .

• Supported source repositories

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