Merge pull request #58164 from DennisLee-DennisLee/v-dele-1387770-2

1387770: Changed second 10 files of broken internal links.

Author: ktoliver

articles/azure-functions/functions-monitoring.md

@@ -188,7 +188,7 @@ If you write logs in your function code, their category is "Function".
 
 ### Log levels
 
-The Azure functions logger also includes a *log level* with every log. [LogLevel](https://docs.microsoft.com/aspnet/core/api/microsoft.extensions.logging.loglevel#Microsoft_Extensions_Logging_LogLevel) is an enumeration, and the integer code indicates relative importance:
+The Azure functions logger also includes a *log level* with every log. [LogLevel](/dotnet/api/microsoft.extensions.logging.loglevel) is an enumeration, and the integer code indicates relative importance:
 
 |LogLevel    |Code|
 |------------|---|

articles/container-registry/container-registry-tasks-multi-step.md

@@ -3,21 +3,20 @@ title: Automate image build, test, and patch with Azure Container Registry multi
 description: An introduction to multi-step tasks, a feature of ACR Tasks in Azure Container Registry that provides task-based workflows for building, testing, and patching container images in the cloud.
 services: container-registry
 author: dlepow
-
 ms.service: container-registry
 ms.topic: article
-ms.date: 10/29/2018
+ms.date: 11/15/2018
 ms.author: danlep
 ---
 
 # Run multi-step build, test, and patch tasks in ACR Tasks
 
-Multi-step tasks extend the single image build-and-push capability of ACR Tasks with multi-step, multi-container-based workflows. Use multi-step tasks to build and push several images, in series or in parallel, and run those images as commands within a single task run. Each step defines a container image build or push operation, and can also define the execution of a container. Each step in a multi-step task uses a container as its execution environment.
+Multi-step tasks extend the single image build-and-push capability of ACR Tasks with multi-step, multi-container-based workflows. Use multi-step tasks to build and push several images, in series or in parallel. Then run those images as commands within a single task run. Each step defines a container image build or push operation, and can also define the execution of a container. Each step in a multi-step task uses a container as its execution environment.
 
 > [!IMPORTANT]
 > If you previously created tasks during the preview with the `az acr build-task` command, those tasks need to be re-created using the [az acr task][az-acr-task] command.
 
-For example, you can run a task with steps that automate the following:
+For example, you can run a task with steps that automate the following logic:
 
 1. Build a web application image
 1. Run the web application container
@@ -33,11 +32,11 @@ All steps are performed within Azure, offloading the work to Azure's compute res
 
 ## Common task scenarios
 
-Multi-step tasks enable scenarios like the following:
+Multi-step tasks enable scenarios like the following logic:
 
 * Build, tag, and push one or more container images, in series or in parallel.
 * Run and capture unit test and code coverage results.
-* Run and capture functional tests. ACR Tasks supports running multiple containers, executing a series of requests between them.
+* Run and capture functional tests. ACR Tasks supports running more than one container, executing a series of requests between them.
 * Perform task-based execution, including pre/post steps of a container image build.
 * Deploy one or more containers with your favorite deployment engine to your target environment.
 
@@ -172,5 +171,5 @@ You can find multi-step task reference and examples here:
 
 <!-- LINKS - Internal -->
 [az-acr-task-create]: /cli/azure/acr/task#az-acr-task-create
-[az-acr-run]: /cli/azure/acr/run#az-acr-run
-[az-acr-task]: /cli/azure/acr#az-acr-task
+[az-acr-run]: /cli/azure/acr#az-acr-run
+[az-acr-task]: /cli/azure/acr/task

articles/cosmos-db/faq.md

@@ -1,91 +1,89 @@
 ---
-title: Monitoring and debugging with metrics in Azure Cosmos DB | Microsoft Docs
+title: Monitor and debug with metrics in Azure Cosmos DB | Microsoft Docs
 description: Use metrics in Azure Cosmos DB to debug common issues and monitor the database.
 keywords: metrics
 services: cosmos-db
 author: kanshiG
 manager: kfile
 editor: ''
-
 ms.service: cosmos-db
 ms.devlang: na
 ms.topic: conceptual
-ms.date: 09/25/2017
+ms.date: 11/15/2018
 ms.author: govindk
-
 ---
+# Monitor and debug with metrics in Azure Cosmos DB
 
-# Monitoring and debugging with metrics in Azure Cosmos DB
-
-Azure Cosmos DB provides metrics for throughput, storage, consistency, availability, and latency. The [Azure portal](https://portal.azure.com) provides an aggregated view of these metrics; for more granular metrics, both the client SDK and the [diagnostic logs](./logging.md) are available.
+Azure Cosmos DB provides metrics for throughput, storage, consistency, availability, and latency. The [Azure portal](https://portal.azure.com) provides an aggregated view of these metrics. For more granular metrics, both the client SDK and the [diagnostic logs](./logging.md) are available.
 
-This article walks through common use cases and how Azure Cosmos DB metrics can be used to analyze and debug these issues. Metrics are collected every five minutes and are retained for seven days.
+This article walks through common use cases and how Azure Cosmos DB metrics can be used to analyze and debug these issues. Metrics are collected every five minutes and are kept for seven days.
 
-## Understanding how many requests are succeeding or causing errors
+## Understand how many requests are succeeding or causing errors
 
-To get started, head to the [Azure portal](https://portal.azure.com) and navigate to the **Metrics** blade. In the blade, find the **Number of requests exceeded capacity per 1 minute** chart. This chart shows a minute by minute total requests segmented by the status code. For more information about HTTP status codes, see [HTTP Status Codes for Azure Cosmos DB](https://docs.microsoft.com/rest/api/cosmos-db/http-status-codes-for-cosmosdb).
+To get started, head to the [Azure portal](https://portal.azure.com) and navigate to the **Metrics** blade. In the blade, find the **Number of requests exceeded capacity per 1 minute** chart. This chart shows a minute by minute total requests segmented by the status code. For more information about HTTP status codes, see [HTTP status codes for Azure Cosmos DB](https://docs.microsoft.com/rest/api/cosmos-db/http-status-codes-for-cosmosdb).
 
-The most common error status code is 429 (rate limiting/throttling), which means that requests to Azure Cosmos DB are exceeding the provisioned throughput. The most common solution to this is to [scale up the RUs](./set-throughput.md) for the given collection.
+The most common error status code is 429 (rate limiting/throttling). This error means that requests to Azure Cosmos DB are more than the provisioned throughput. The most common solution to this problem is to [scale up the RUs](./set-throughput.md) for the given collection.
 
 ![Number of requests per minute](media/use-metrics/metrics-12.png)
 
-## Determining the throughput distribution across partitions
+## Determine the throughput distribution across partitions
 
-Having a good cardinality of your partition keys is essential for any scalable application. To determine the throughput distribution of any partitioned container broken down by partitions, navigate to the **Metrics blade** in the [Azure portal](https://portal.azure.com). In the **Throughput** tab, the storage breakdown is shown in the **Max consumed RU/second by each physical partition** chart. The following graphic illustrates an example of a poor distribution of data as evidenced by the skewed partition on the far left. 
+Having a good cardinality of your partition keys is essential for any scalable application. To determine the throughput distribution of any partitioned container broken down by partitions, navigate to the **Metrics blade** in the [Azure portal](https://portal.azure.com). In the **Throughput** tab, the storage breakdown is shown in the **Max consumed RU/second by each physical partition** chart. The following graphic illustrates an example of a poor distribution of data as shown by the skewed partition on the far left.
 
 ![Single partition seeing heavy usage at 3:05 PM](media/use-metrics/metrics-17.png)
 
 An uneven throughput distribution may cause *hot* partitions, which can result in throttled requests and may require repartitioning. For more information about partitioning in Azure Cosmos DB, see [Partition and scale in Azure Cosmos DB](./partition-data.md).
 
-## Determining the storage distribution across partitions
+## Determine the storage distribution across partitions
 
-Having a good cardinality of your partition is essential for any scalable application. To determine the throughput distribution of any partitioned container broken down by partitions, head to the Metrics blade in the [Azure portal](https://portal.azure.com). In the Throughput tab, the storage breakdown is shown in the Max consumed RU/second by each physical partition chart. The following graphic illustrates a poor distribution of data as evidenced by the skewed partition on the far left. 
+Having a good cardinality of your partition is essential for any scalable application. To determine the throughput distribution of any partitioned container broken down by partitions, head to the Metrics blade in the [Azure portal](https://portal.azure.com). In the Throughput tab, the storage breakdown is shown in the Max consumed RU/second by each physical partition chart. The following graphic illustrates a poor distribution of data as shown by the skewed partition on the far left.
 
 ![Example of poor data distribution](media/use-metrics/metrics-07.png)
 
-You can root cause which partition key is skewing the distribution by clicking on the partition in the chart. 
+You can root cause which partition key is skewing the distribution by clicking on the partition in the chart.
 
 ![Partition key is skewing the distribution](media/use-metrics/metrics-05.png)
 
 After identifying which partition key is causing the skew in distribution, you may have to repartition your container with a more distributed partition key. For more information about partitioning in Azure Cosmos DB, see [Partition and scale in Azure Cosmos DB](./partition-data.md).
 
-## Comparing data size against index size
+## Compare data size against index size
 
-In Azure Cosmos DB, the total consumed storage is the combination of both the Data size and Index size. Typically, the index size is a fraction of the data size. In the Metrics blade in the [Azure portal](https://portal.azure.com), the Storage tab showcases the breakdown of storage consumption based on data and index. 
+In Azure Cosmos DB, the total consumed storage is the combination of both the Data size and Index size. Typically, the index size is a fraction of the data size. In the Metrics blade in the [Azure portal](https://portal.azure.com), the Storage tab showcases the breakdown of storage consumption based on data and index.
 
 ```csharp
 // Measure the document size usage (which includes the index size)  
-ResourceResponse<DocumentCollection> collectionInfo = await client.ReadDocumentCollectionAsync(UriFactory.CreateDocumentCollectionUri("db", "coll")); 
+ResourceResponse<DocumentCollection> collectionInfo = await client.ReadDocumentCollectionAsync(UriFactory.CreateDocumentCollectionUri("db", "coll"));
  Console.WriteLine("Document size quota: {0}, usage: {1}", collectionInfo.DocumentQuota, collectionInfo.DocumentUsage);
-``` 
-If you would like to conserve index space, you can adjust the [indexing policy](./indexing-policies.md).
+```
+
+If you would like to conserve index space, you can adjust the [indexing policy](index-policy.md).
 
-## Debugging why queries are running slow
+## Debug why queries are running slow
 
-In the SQL API SDKs, Azure Cosmos DB provides query execution statistics. 
+In the SQL API SDKs, Azure Cosmos DB provides query execution statistics.
 
 ```csharp
 IDocumentQuery<dynamic> query = client.CreateDocumentQuery(
- UriFactory.CreateDocumentCollectionUri(DatabaseName, CollectionName), 
- "SELECT * FROM c WHERE c.city = 'Seattle'", 
- new FeedOptions 
- { 
- PopulateQueryMetrics = true, 
- MaxItemCount = -1, 
- MaxDegreeOfParallelism = -1, 
- EnableCrossPartitionQuery = true 
+ UriFactory.CreateDocumentCollectionUri(DatabaseName, CollectionName),
+ "SELECT * FROM c WHERE c.city = 'Seattle'",
+ new FeedOptions
+ {
+ PopulateQueryMetrics = true,
+ MaxItemCount = -1,
+ MaxDegreeOfParallelism = -1,
+ EnableCrossPartitionQuery = true
  }).AsDocumentQuery();
 FeedResponse<dynamic> result = await query.ExecuteNextAsync();
 
-// Returns metrics by partition key range Id 
+// Returns metrics by partition key range Id
 IReadOnlyDictionary<string, QueryMetrics> metrics = result.QueryMetrics;
 ```
 
-*QueryMetrics* provides details on how long each component of the query took to execution. The most common root cause for long running queries are scans (the query was unable to leverage the indexes), which can be resolved with a better filter condition.
+*QueryMetrics* provides details on how long each component of the query took to execution. The most common root cause for long running queries is scans, meaning the query was unable to leverage the indexes. This problem can be resolved with a better filter condition.
 
 ## Next steps
 
-Now that you've learned how to monitor and debug issues using the metrics provided in the Azure portal, you may want to learn more about improving database performance by reading the following articles:
+You've now learned how to monitor and debug issues using the metrics provided in the Azure portal. You may want to learn more about improving database performance by reading the following articles:
 
 * [Performance and scale testing with Azure Cosmos DB](performance-testing.md)
 * [Performance tips for Azure Cosmos DB](performance-tips.md)

articles/cosmos-db/import-data.md

@@ -433,7 +433,7 @@ Typically, you set the parameters before you fit a model.
 
 The following code samples show you how to train the model using the default pipeline and model parameters. 
 
-To see what parameters are included for "text_word_ngrams", use [get_step_param_names_by_name](https://docs.microsoft.com/python/api/tatk.core.base_text_model.basetextmodel). This function returns the parameters such as lowercase, input_col, output_col and so on. 
+To see what parameters are included for "text_word_ngrams", use [get_step_param_names_by_name](/python/api/msft-tatk/tatk.core.base_text_model.basetextmodel#get-step-param-names-by-name). This function returns the parameters such as lowercase, input_col, output_col and so on. 
 
 ```python
 text_classifier.get_step_param_names_by_name("text_word_ngrams")
@@ -622,7 +622,7 @@ Apply the trained text classifier on the test dataset to generate class predicti
 </div>
 
 ## Evaluate model performance
-The [evaluation module](https://docs.microsoft.com/python/api/tatk.evaluation) evaluates the accuracy of the trained text classifier on the test dataset. The evaluate function generates a confusion matrix and provides a macro-F1 score.
+The [evaluation module](/python/api/msft-tatk/tatk.evaluation) evaluates the accuracy of the trained text classifier on the test dataset. The evaluate function generates a confusion matrix and provides a macro-F1 score.
 
 ```python
  text_classifier.evaluate(df_test)          

articles/cosmos-db/use-metrics.md

@@ -1,49 +1,47 @@
 ---
-title: Managing ‘Azure Marketplace’ and ‘AppSource’ Publisher Profile
-description: Managing ‘Azure Marketplace’ and ‘AppSource’ Publisher Profile
+title: Manage ‘Azure Marketplace’ and ‘AppSource’ publisher profile
+description: Managing ‘Azure Marketplace’ and ‘AppSource’ publisher profile
 services: Azure, Marketplace, Cloud Partner Portal, 
 documentationcenter:
 author: qianw211
 manager: pbutlerm  
 editor:
-
 ms.assetid: 
 ms.service: marketplace
 ms.workload: 
 ms.tgt_pltfrm: 
 ms.devlang: 
 ms.topic: conceptual
-ms.date: 09/13/2018
+ms.date: 11/15/2018
 ms.author: pbutlerm
 ---
 
-
-Managing 'Azure Marketplace' and 'AppSource' Publisher Profile
-==============================================================
+# Manage 'Azure Marketplace' and 'AppSource' publisher profile
 
 This document is a walk-through on viewing and managing users to your
 registered publisher profile.
 
-By this time, you have completed the steps to become an Azure
+By this time, you've completed the steps to become an Azure
 Marketplace and AppSource publisher. The publisher profile is registered
 on the **[Cloud Partner Portal](https://cloudpartner.azure.com/)**
 following approval of your partner request. Your publisher profile will
 apply to all the offers and SKUs published from the account used during
 partner registration.
 
-If you haven't registered your company as a cloud partner [click
-here](https://cloudpartner.azure.com/#documentation/getting-started-with-the-cloud-partner-portal).
+If you haven't registered your company as a cloud partner, see [Get started with the cloud partner portal](https://cloudpartner.azure.com/#documentation/getting-started-with-the-cloud-partner-portal).
 
 **Publisher Profile**: Your publisher profile distinguishes your company
 on the Azure Marketplace and AppSource. It consists of your publisher
 ID, display name, and owner email(s). A well-managed profile will
 increase your visibility and help marketplace users easily identify and
 select an appropriate offer.
 
-> [!NOTE] 
-> Your publisher ID and registered owner email is not editable once you publish your first offer. However you can view your profile and edit the publisher display name from the Cloud Partner Portal.
+> [!NOTE]
+> Your publisher ID and registered owner email isn't editable once you publish your first offer. However you can view your profile and edit the publisher display name from the Cloud Partner Portal.
+
+<!-- Dummy comment added to suppress MD linter warning -->
 
-> [!NOTE] 
+> [!NOTE]
 > Add users (contributors and owners) to your publishing profile from the Users section on the left navigation pane from the Users Section of the cloud partner portal`
 
 **To view and manage your publisher profile**, from the top-right menu
@@ -58,16 +56,14 @@ Details - publisher profile details](./media/cloud-partner-portal-how-to-manage-
 **Link your Dev Center Account**: You can also link your existing Dev
 Center account with your publisher profile on the Cloud Partner Portal.
 First sign in to the portal with the same email address used to register
-your Dev Center account. Once linked, your Dev Center account status,
-Dev Center account owner email, and Dev Center account name will show up
-on your publisher profile page.
+your Dev Center account. Then your publisher profile page displays your Dev Center account status, Dev Center account owner email, and Dev Center account name.
 
 >[!NOTE]
->Dev Center Account registration is mandatory for publishing paid market place SKU’s.
+>Dev Center Account registration is mandatory for publishing paid market place SKUs.
 
-If you do not have a [Developer Center Account](https://docs.microsoft.com/azure/marketplace-publishing/marketplace-publishing-accounts-creation-registration.md), 
-you can create one and add the registered email address as one of the
-owners on the Cloud Partner Portal for your offer. An owner can only add
+If you don't have a [Developer Center Account](~/articles/marketplace-publishing/marketplace-publishing-accounts-creation-registration.md),
+you can create an account. Then add the registered email address as an
+owner on the Cloud Partner Portal for your offer. An owner can only add
 the registered email address to your publishing profile from the
 **User** section. Then, sign in to the portal using the same email
 address, and link your Dev Center account.