Merge pull request #230768 from pritamso/Broken-link-fix-kromerm

Broken link fix

Author: prmerger-automator[bot]

articles/data-factory/apply-dataops.md

@@ -32,7 +32,7 @@ Specifically, once you bring your own GitHub or Azure DevOps repository into dat
 
 ### "Code" in Azure Data Factory
 
-All artifacts in Azure Data Factory, whether they're pipelines, linked services, triggers, etc. have corresponding “code” representations in JSON behind the visual UI integration. These artifacts act in compliance with [Azure Resource Manager templates](/azure-resource-manager/templates/overview.md) standards. You can find the code by clicking on the bracket icon on the top right of the canvas. Sample JSON “code” would look like this:
+All artifacts in Azure Data Factory, whether they're pipelines, linked services, triggers, etc. have corresponding “code” representations in JSON behind the visual UI integration. These artifacts act in compliance with [Azure Resource Manager templates](/azure/azure-resource-manager/templates/overview) standards. You can find the code by clicking on the bracket icon on the top right of the canvas. Sample JSON “code” would look like this:
 
 :::image type="content" source="media/apply-dataops/view-json-button.png" alt-text="Screenshot showing the View JSON button on the pipeline UI.":::
 
@@ -82,7 +82,7 @@ CI/CD is a paradigm of code development where changes are inspected and tested a
 
 Continuous integration (CI) is the practice of automatically testing and validating every time a developer makes a change to your codebase. Continuous delivery (CD) means that after Continuous Integration tests succeed, the changes are brought to the next stage continuously.
 
-As discussed briefly previously, “code” in Azure Data Factory takes the form of [Azure Resource Manager template](/azure-resource-manager/templates/overview.md) JSON. Hence, the changes going through the continuous integration and delivery (CI/CD) process comprise additions, deletions, and edits to JSON blobs.
+As discussed briefly previously, “code” in Azure Data Factory takes the form of [Azure Resource Manager template](/azure/azure-resource-manager/templates/overview) JSON. Hence, the changes going through the continuous integration and delivery (CI/CD) process comprise additions, deletions, and edits to JSON blobs.
 
 #### Pipeline runs in Azure Data Factory
 
@@ -140,7 +140,7 @@ Here are the few points to consider regarding stopping triggers:
 
 We recommend that you follow these best practices for pull requests. 
 
-- Each developer should work on their own individual branches, and at the end of day, create pull requests to the main branch of the repository. See tutorials on pull requests in [GitHub](https://docs.github.com/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request) and [DevOps](/devops/repos/git/pull-requests.md?view=azure-devops&tabs=browser&preserve-view=true).
+- Each developer should work on their own individual branches, and at the end of day, create pull requests to the main branch of the repository. See tutorials on pull requests in [GitHub](https://docs.github.com/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request) and [DevOps](/azure/devops/repos/git/pull-requests).
 - When gate keepers approve the pull requests and merge the changes into the main branch, the CI/CD process can start. There are two suggested methods to promote changes throughout environments: [automated](#automated-deployment-of-changes) and [manual](#manual-deployment-of-changes).
 - Once you're ready to kick off CI/CD pipelines, you can do so generally using [Azure Pipeline Release](continuous-integration-delivery-improvements.md) or make deployments of specific individual pipelines using this [open source utility from Azure Player](https://github.com/Azure-Player/azure.datafactory.tools).
 

articles/data-factory/apply-finops.md

@@ -115,19 +115,19 @@ This section discusses cost optimization with Microsoft cost management, the Azu
 
 ### Microsoft cost management
 
-Microsoft Azure provides tools that help you to track, optimize, and control your Azure spending. If your data factory spending is a top priority, the recommendation is to create a separate resource group in Azure for each data factory. This way, it's easy to build budgets, track your spending, and apply cost controls using [Microsoft Cost Management](/cost-management-billing/costs/cost-mgt-best-practices.md).
+Microsoft Azure provides tools that help you to track, optimize, and control your Azure spending. If your data factory spending is a top priority, the recommendation is to create a separate resource group in Azure for each data factory. This way, it's easy to build budgets, track your spending, and apply cost controls using [Microsoft Cost Management](/azure/cost-management-billing/costs/cost-mgt-best-practices).
 
 :::image type="content" source="media/apply-finops/microsoft-cost-management.png" lightbox="media/apply-finops/microsoft-cost-management.png" alt-text="Screenshot showing the Microsoft cost management page in Azure.":::
 
 Today organizations are working harder than ever to control spending and do more with less. You can use the Azure budgets feature to set spending limits on your Azure Data Factory v2 usage and the overall Azure resource group that you're using for data factory.
 
 :::image type="content" source="media/apply-finops/azure-budgets.png" alt-text="Screenshot of the Azure budgets page showing how to set budgets for a service.":::
 
-From the [create budget window](/cost-management-billing/costs/tutorial-acm-create-budgets.md), use filters to choose either the Azure Data Factory service or a resource group.
+From the [create budget window](/azure/cost-management-billing/costs/tutorial-acm-create-budgets), use filters to choose either the Azure Data Factory service or a resource group.
 
 ### Azure Advisor
 
-Another valuable tool for optimizing your Azure budget is Azure Advisor. With Azure Advisor, you can receive recommendations for reducing your overall Azure spending. This includes utilization of [Azure Data Factory's reserved instance pricing for reducing costs of mapping data flows](/advisor/advisor-reference-cost-recommendations.md#consider-data-factory-reserved-instance-to-save-over-your-on-demand-costs). You can also pay for Azure Data Factory charges with your [Azure pre-payment credit](plan-manage-costs.md#using-azure-prepayment-with-azure-data-factory).
+Another valuable tool for optimizing your Azure budget is Azure Advisor. With Azure Advisor, you can receive recommendations for reducing your overall Azure spending. This includes utilization of [Azure Data Factory's reserved instance pricing for reducing costs of mapping data flows](/azure/advisor/advisor-reference-cost-recommendations#consider-data-factory-reserved-instance-to-save-over-your-on-demand-costs). You can also pay for Azure Data Factory charges with your [Azure pre-payment credit](plan-manage-costs.md#using-azure-prepayment-with-azure-data-factory).
 
 :::image type="content" source="media/apply-finops/azure-advisor.png" lightbox="media/apply-finops/azure-advisor.png" alt-text="Screenshot showing the Azure Advisor window that can provide recommendations including cost reduction optimizations.":::
 
@@ -163,4 +163,4 @@ Another mechanism for tracking attributing costs for your data factory resource
 
 - [Plan to manage costs for Azure Data Factory](plan-manage-costs.md)
 - [Understanding Azure Data Factory pricing through examples](pricing-concepts.md)
-- [Azure pricing calculator](https://azure.microsoft.com/pricing/calculator/)
+- [Azure pricing calculator](https://azure.microsoft.com/pricing/calculator/)