Update references from VSTS to Azure DevOps

kraigb · kraigb · commit 1ea6a01c966c · 2018-10-26T08:37:50.000-07:00
diff --git a/docs/python/learn-django-in-visual-studio-step-06-polls-django-web-project-template.md b/docs/python/learn-django-in-visual-studio-step-06-polls-django-web-project-template.md
@@ -371,4 +371,4 @@ Running a web app on your development computer is just one step in making the ap
 
 - Change the app from SQLite to a production-level data store such as PostgreSQL, MySQL, and SQL Server (all of which can be hosted on Azure). As described on [When to use SQLite](https://www.sqlite.org/whentouse.html) (sqlite.org), SQLite works fine for low to medium traffic sites with fewer than 100K hits/day, but is not recommended for higher volumes. It's also limited to a single computer, so it cannot be used in any multi-server scenario such as load-balancing and geo-replication. For information on Django's support for other databases, see [Database setup](https://docs.djangoproject.com/en/2.0/intro/tutorial02/#database-setup). You can also use the [Azure SDK for Python](azure-sdk-for-python.md) to work with Azure storage services like tables and blobs.
 
-- Set up a continuous integration/continuous deployment pipeline on a service like Visual Studio Team Services (VSTS). In addition to working with source control (on VSTS, GitHub, or elsewhere), you can have VSTS automatically run your unit tests as a pre-requisite for release, and also configure the pipeline to deploy to a staging server for additional tests before deploying to production. VSTS, furthermore, integrates with monitoring solutions like App Insights and closes the whole cycle with agile planning tools. For more information, see [Create a CI/CD pipeline for Python with the Azure DevOps project](/azure/devops-project/azure-devops-project-python?view=vsts).
+- Set up a continuous integration/continuous deployment pipeline on a service like Azure DevOps. In addition to working with source control (via Azure Repos or GitHub, or elsewhere), you can configure an Azure DevOps Project to automatically run your unit tests as a pre-requisite for release, and also configure the pipeline to deploy to a staging server for additional tests before deploying to production. Azure DevOps, furthermore, integrates with monitoring solutions like App Insights and closes the whole cycle with agile planning tools. For more information, see [Create a CI/CD pipeline for Python with the Azure DevOps project](/azure/devops-project/azure-devops-project-python?view=vsts) and also the general [Azure DevOps documentation](/azure/devops/?view=vsts).
diff --git a/docs/python/learn-flask-visual-studio-step-05-polls-flask-web-project-template.md b/docs/python/learn-flask-visual-studio-step-05-polls-flask-web-project-template.md
@@ -351,4 +351,4 @@ Running a web app on your development computer is just one step in making the ap
 
 - Add a repository implementation that uses another production-level data store such as PostgreSQL, MySQL, and SQL Server (all of which can be hosted on Azure). You can also use the [Azure SDK for Python](azure-sdk-for-python.md) to work with Azure storage services like tables and blobs as well as Cosmos DB.
 
-- Set up a continuous integration/continuous deployment pipeline on a service like Visual Studio Team Services (VSTS). In addition to working with source control (on VSTS, GitHub, or elsewhere), you can have VSTS automatically run your unit tests as a pre-requisite for release, and also configure the pipeline to deploy to a staging server for additional tests before deploying to production. VSTS, furthermore, integrates with monitoring solutions like App Insights and closes the whole cycle with agile planning tools. For more information, see [Create a CI/CD pipeline for Python with the Azure DevOps project](/azure/devops-project/azure-devops-project-python?view=vsts).
+- Set up a continuous integration/continuous deployment pipeline on a service like Azure DevOps. In addition to working with source control (via Azure Repos or GitHub, or elsewhere), you can configure an Azure DevOps Project to automatically run your unit tests as a pre-requisite for release, and also configure the pipeline to deploy to a staging server for additional tests before deploying to production. Azure DevOps, furthermore, integrates with monitoring solutions like App Insights and closes the whole cycle with agile planning tools. For more information, see [Create a CI/CD pipeline for Python with the Azure DevOps project](/azure/devops-project/azure-devops-project-python?view=vsts) and also the general [Azure DevOps documentation](/azure/devops/?view=vsts).

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`@@ -371,4 +371,4 @@ Running a web app on your development computer is just one step in making the ap`
`371`	`371`
`372`	`372`	- Change the app from SQLite to a production-level data store such as PostgreSQL, MySQL, and SQL Server (all of which can be hosted on Azure). As described on [When to use SQLite](https://www.sqlite.org/whentouse.html) (sqlite.org), SQLite works fine for low to medium traffic sites with fewer than 100K hits/day, but is not recommended for higher volumes. It's also limited to a single computer, so it cannot be used in any multi-server scenario such as load-balancing and geo-replication. For information on Django's support for other databases, see [Database setup](https://docs.djangoproject.com/en/2.0/intro/tutorial02/#database-setup). You can also use the [Azure SDK for Python](azure-sdk-for-python.md) to work with Azure storage services like tables and blobs.
`373`	`373`
`374`		-- Set up a continuous integration/continuous deployment pipeline on a service like Visual Studio Team Services (VSTS). In addition to working with source control (on VSTS, GitHub, or elsewhere), you can have VSTS automatically run your unit tests as a pre-requisite for release, and also configure the pipeline to deploy to a staging server for additional tests before deploying to production. VSTS, furthermore, integrates with monitoring solutions like App Insights and closes the whole cycle with agile planning tools. For more information, see [Create a CI/CD pipeline for Python with the Azure DevOps project](/azure/devops-project/azure-devops-project-python?view=vsts).
	`374`	+- Set up a continuous integration/continuous deployment pipeline on a service like Azure DevOps. In addition to working with source control (via Azure Repos or GitHub, or elsewhere), you can configure an Azure DevOps Project to automatically run your unit tests as a pre-requisite for release, and also configure the pipeline to deploy to a staging server for additional tests before deploying to production. Azure DevOps, furthermore, integrates with monitoring solutions like App Insights and closes the whole cycle with agile planning tools. For more information, see [Create a CI/CD pipeline for Python with the Azure DevOps project](/azure/devops-project/azure-devops-project-python?view=vsts) and also the general [Azure DevOps documentation](/azure/devops/?view=vsts).
Original file line number	Diff line number	Diff line change
`@@ -351,4 +351,4 @@ Running a web app on your development computer is just one step in making the ap`
`351`	`351`
`352`	`352`	`- Add a repository implementation that uses another production-level data store such as PostgreSQL, MySQL, and SQL Server (all of which can be hosted on Azure). You can also use the [Azure SDK for Python](azure-sdk-for-python.md) to work with Azure storage services like tables and blobs as well as Cosmos DB.`
`353`	`353`
`354`		-- Set up a continuous integration/continuous deployment pipeline on a service like Visual Studio Team Services (VSTS). In addition to working with source control (on VSTS, GitHub, or elsewhere), you can have VSTS automatically run your unit tests as a pre-requisite for release, and also configure the pipeline to deploy to a staging server for additional tests before deploying to production. VSTS, furthermore, integrates with monitoring solutions like App Insights and closes the whole cycle with agile planning tools. For more information, see [Create a CI/CD pipeline for Python with the Azure DevOps project](/azure/devops-project/azure-devops-project-python?view=vsts).
	`354`	+- Set up a continuous integration/continuous deployment pipeline on a service like Azure DevOps. In addition to working with source control (via Azure Repos or GitHub, or elsewhere), you can configure an Azure DevOps Project to automatically run your unit tests as a pre-requisite for release, and also configure the pipeline to deploy to a staging server for additional tests before deploying to production. Azure DevOps, furthermore, integrates with monitoring solutions like App Insights and closes the whole cycle with agile planning tools. For more information, see [Create a CI/CD pipeline for Python with the Azure DevOps project](/azure/devops-project/azure-devops-project-python?view=vsts) and also the general [Azure DevOps documentation](/azure/devops/?view=vsts).