Merge pull request #268209 from HeidiSteen/heidist-fix

v-ccolin · web-flow · commit 41d3217f2a16 · 2024-03-06T09:58:08.000Z
[azure search] Bulk edit "postman"
diff --git a/articles/search/cognitive-search-create-custom-skill-example.md b/articles/search/cognitive-search-create-custom-skill-example.md
@@ -314,7 +314,7 @@ Of course, you may rename the file from `Function1.cs` to `BingEntitySearch.cs`.
 
 ## Test the function from Visual Studio
 
-Press **F5** to run the program and test function behaviors. In this case, we'll use the function below to look up two entities. Use Postman or Fiddler to issue a call like the one shown below:
+Press **F5** to run the program and test function behaviors. In this case, we'll use the function below to look up two entities. Use a REST client to issue a call like the one shown below:
 
 ```http
 POST https://localhost:7071/api/EntitySearch
diff --git a/articles/search/cognitive-search-quickstart-blob.md b/articles/search/cognitive-search-quickstart-blob.md
@@ -191,7 +191,7 @@ If you used a free service, remember that you're limited to three indexes, index
 
 ## Next steps
 
-You can create skillsets using the portal, .NET SDK, or REST API. To further your knowledge, try the REST API using Postman and more sample data.
+You can create skillsets using the portal, .NET SDK, or REST API. To further your knowledge, try the REST API using a REST client and more sample data.
 
 > [!div class="nextstepaction"]
 > [Tutorial: Extract text and structure from JSON blobs using REST APIs ](cognitive-search-tutorial-blob.md)
diff --git a/articles/search/cognitive-search-working-with-skillsets.md b/articles/search/cognitive-search-working-with-skillsets.md
@@ -181,7 +181,7 @@ In this example, source fields from a CSV file include customer reviews about ho
 In the hotel reviews example, a "document" within the enrichment process represents a single hotel review.
 
 > [!TIP]
-> You can create a search index and knowledge store for this data in [Azure portal](knowledge-store-create-portal.md) or through [Postman and the REST APIs](knowledge-store-create-rest.md). You can also use [Debug Sessions](cognitive-search-debug-session.md) for insights into skillset composition, dependencies, and effects on an enrichment tree. Images in this article are pulled from Debug Sessions.
+> You can create a search index and knowledge store for this data in [Azure portal](knowledge-store-create-portal.md) or [REST APIs](knowledge-store-create-rest.md). You can also use [Debug Sessions](cognitive-search-debug-session.md) for insights into skillset composition, dependencies, and effects on an enrichment tree. Images in this article are pulled from Debug Sessions.
 
 Conceptually, the initial enrichment tree looks as follows:
 
diff --git a/articles/search/hybrid-search-how-to-query.md b/articles/search/hybrid-search-how-to-query.md
@@ -42,7 +42,7 @@ A hybrid query combines full text search and vector search, where the `"search"`
 
 Hybrid queries are useful because they add support for all query capabilities, including orderby and [semantic ranking](semantic-how-to-query-request.md). For example, in addition to the vector query, you could search over people or product names or titles, scenarios for which similarity search isn't a good fit.
 
-The following example is from the [Postman collection of REST APIs](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python) that demonstrate hybrid query configurations.
+The following example shows a hybrid query configurations.
 
 ```http
 POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2023-11-01
diff --git a/articles/search/knowledge-store-connect-power-bi.md b/articles/search/knowledge-store-connect-power-bi.md
@@ -18,7 +18,7 @@ In this article, learn how to connect to and query a knowledge store using Power
 
 A knowledge store that's composed of tables in Azure Storage work best in Power BI. If the tables contain projections from the same skillset and projection group, you can easily "join" them to build table visualizations that include fields from related tables.
 
-Follow the steps in this article using sample data and a knowledge store as [created in this portal quickstart](knowledge-store-create-portal.md) or through [Postman and REST APIs](knowledge-store-create-rest.md). 
+Follow the steps in this article using sample data and a knowledge store as [created in this portal quickstart](knowledge-store-create-portal.md) or through [REST APIs](knowledge-store-create-rest.md). 
 
 ## Connect to Azure Storage
 
diff --git a/articles/search/knowledge-store-create-portal.md b/articles/search/knowledge-store-create-portal.md
@@ -178,4 +178,4 @@ If you're using a free service, remember that you're limited to three indexes, i
 Now that you've been introduced to a knowledge store, take a closer look at each step by switching over to the REST API walkthrough. Tasks that the wizard handled internally are explained in the REST walkthrough.
 
 > [!div class="nextstepaction"]
-> [Create a knowledge store using REST and Postman](knowledge-store-create-rest.md)
+> [Create a knowledge store using REST](knowledge-store-create-rest.md)
diff --git a/articles/search/query-lucene-syntax.md b/articles/search/query-lucene-syntax.md
@@ -186,7 +186,7 @@ In some circumstances, you may want to search for a special character, like an '
 
 Analyzers that tokenize special characters include the whitespace analyzer, which takes into consideration any character sequences separated by whitespaces as tokens (so the `❤` string would be considered a token). Also, a language analyzer like the Microsoft English analyzer ("en.microsoft"), would take the "€" string as a token. You can [test an analyzer](/rest/api/searchservice/test-analyzer) to see what tokens it generates for a given query.
 
-When using Unicode characters, make sure symbols are properly escaped in the query url (for instance for `❤` would use the escape sequence `%E2%9D%A4+`). Postman does this translation automatically.  
+When using Unicode characters, make sure symbols are properly escaped in the query url (for instance for `❤` would use the escape sequence `%E2%9D%A4+`). Some REST clients do this translation automatically.  
 
 ## Precedence (grouping)
 
diff --git a/articles/search/search-capacity-planning.md b/articles/search/search-capacity-planning.md
@@ -74,7 +74,7 @@ One approach for estimating capacity is to start with the Free tier. Remember th
 
 + [Create a free service](search-create-service-portal.md).
 + Prepare a small, representative dataset.
-+ Create an index and load your data. If the dataset can be hosted in an Azure data source supported by indexers, you can use the [Import data wizard in the portal](search-get-started-portal.md) to both create and load the index. Otherwise, you could use [REST and Postman](search-get-started-rest.md) to create the index and push the data. The push model requires data to be in the form of JSON documents, where fields in the document correspond to fields in the index.
++ Create an index and load your data. If the dataset can be hosted in an Azure data source supported by indexers, you can use the [Import data wizard in the portal](search-get-started-portal.md) to both create and load the index. Otherwise, you could use [REST APIs](search-get-started-rest.md) to create the index and push the data. The push model requires data to be in the form of JSON documents, where fields in the document correspond to fields in the index.
 + Collect information about the index, such as size. Features and attributes affect storage. For example, adding suggesters (search-as-you-type queries) will increase storage requirements. 
 
   Using the same data set, you might try creating multiple versions of an index, with different attributes on each field, to see how storage requirements vary. For more information, see ["Storage implications" in Create a basic index](search-what-is-an-index.md#index-size).
diff --git a/articles/search/search-explorer.md b/articles/search/search-explorer.md
@@ -201,7 +201,7 @@ If you're using a free service, remember that you're limited to three indexes, i
 
 ## Next steps
 
-To learn more about query structures and syntax, use Postman or an equivalent tool to create query expressions that use more parts of the API. The [Search POST REST API](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2023-10-01-preview&preserve-view=true) is especially helpful for learning and exploration.
+To learn more about query structures and syntax, use a REST client to create query expressions that use more parts of the API. The [Search POST REST API](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2023-10-01-preview&preserve-view=true) is especially helpful for learning and exploration.
 
 > [!div class="nextstepaction"]
-> [Create a basic query in Postman](search-get-started-rest.md)
+> [Create a basic query in REST](search-get-started-rest.md)
diff --git a/articles/search/search-howto-connecting-azure-sql-database-to-azure-search-using-indexers.md b/articles/search/search-howto-connecting-azure-sql-database-to-azure-search-using-indexers.md
@@ -38,7 +38,7 @@ This article also provides:
 
 + Read permissions. Azure AI Search supports SQL Server authentication, where the user name and password are provided on the connection string. Alternatively, you can [set up a managed identity and use Azure roles](search-howto-managed-identities-sql.md).
 
-To work through the examples in this article, you'll need a REST client, such as [Postman](search-get-started-rest.md). 
+To work through the examples in this article, you need a [REST client](search-get-started-rest.md). 
 
 Other approaches for creating an Azure SQL indexer include Azure SDKs or [Import data wizard](search-get-started-portal.md) in the Azure portal. If you're using Azure portal, make sure that access to all public networks is enabled in the Azure SQL firewall and that the client has access via an inbound rule.
 
diff --git a/articles/search/search-howto-index-cosmosdb-gremlin.md b/articles/search/search-howto-index-cosmosdb-gremlin.md
@@ -35,7 +35,7 @@ Because terminology can be confusing, it's worth noting that [Azure Cosmos DB in
 
 + Read permissions. A "full access" connection string includes a key that grants access to the content, but if you're using Azure roles, make sure the [search service managed identity](search-howto-managed-identities-data-sources.md) has **Cosmos DB Account Reader Role** permissions.
 
-+ A REST client, such as [Postman](search-get-started-rest.md), to send REST calls that create the data source, index, and indexer. 
++ A [REST client](search-get-started-rest.md) to create the data source, index, and indexer. 
 
 ## Define the data source
 
diff --git a/articles/search/search-howto-index-cosmosdb-mongodb.md b/articles/search/search-howto-index-cosmosdb-mongodb.md
@@ -32,7 +32,7 @@ Because terminology can be confusing, it's worth noting that [Azure Cosmos DB in
 
 + Read permissions. A "full access" connection string includes a key that grants access to the content, but if you're using Azure roles, make sure the [search service managed identity](search-howto-managed-identities-data-sources.md) has **Cosmos DB Account Reader Role** permissions.
 
-+ A REST client, such as [Postman](search-get-started-rest.md), to send REST calls that create the data source, index, and indexer. 
++ A [REST client](search-get-started-rest.md) to create the data source, index, and indexer. 
 
 ## Limitations
 
diff --git a/articles/search/search-howto-index-cosmosdb.md b/articles/search/search-howto-index-cosmosdb.md
@@ -29,7 +29,7 @@ Because terminology can be confusing, it's worth noting that [Azure Cosmos DB in
 
 + Read permissions. A "full access" connection string includes a key that grants access to the content, but if you're using Azure RBAC (Microsoft Entra ID), make sure the [search service managed identity](search-howto-managed-identities-data-sources.md) is assigned both **Cosmos DB Account Reader Role** and [**Cosmos DB Built-in Data Reader Role**](../cosmos-db/how-to-setup-rbac.md#built-in-role-definitions).
 
-+ A REST client, such as [Postman](search-get-started-rest.md), to send REST calls that create the data source, index, and indexer. 
++ A [REST client](search-get-started-rest.md) to create the data source, index, and indexer. 
 
 ## Define the data source
 
diff --git a/articles/search/search-howto-index-mysql.md b/articles/search/search-howto-index-mysql.md
@@ -36,7 +36,7 @@ When configured to include a high water mark and soft deletion, the indexer take
 
 - Read permissions. A *full access* connection string includes a key that grants access to the content, but if you're using Azure roles, make sure the [search service managed identity](search-howto-managed-identities-data-sources.md) has **Reader** permissions on MySQL.
 
-- A REST client, such as [Postman](search-get-started-rest.md), to send REST calls that create the data source, index, and indexer.
+- A [REST client](search-get-started-rest.md) to create the data source, index, and indexer.
 
   You can also use the [Azure SDK for .NET](/dotnet/api/azure.search.documents.indexes.models.searchindexerdatasourcetype.mysql). You can't use the portal for indexer creation, but you can manage indexers and data sources once they're created.
 
diff --git a/articles/search/search-howto-indexing-azure-blob-storage.md b/articles/search/search-howto-indexing-azure-blob-storage.md
@@ -33,7 +33,7 @@ Blob indexers are frequently used for both [AI enrichment](cognitive-search-conc
 
   By default, both search and storage accept requests from public IP addresses. If network security isn't an immediate concern, you can index blob data using just the connection string and read permissions. When you're ready to add network protections, see [Indexer access to content protected by Azure network security features](search-indexer-securing-resources.md) for guidance about data access.
 
-+ Use a REST client, such as [Postman app](https://www.postman.com/downloads/), if you want to formulate REST calls similar to the ones shown in this article.
++ Use a [REST client](search-get-started-rest.md) to formulate REST calls similar to the ones shown in this article.
 
 <a name="SupportedFormats"></a>
 
diff --git a/articles/search/search-howto-reindex.md b/articles/search/search-howto-reindex.md
@@ -81,7 +81,7 @@ If indexing workloads introduce unacceptable levels of query latency, conduct [p
 
 You can begin querying an index as soon as the first document is loaded. If you know a document's ID, the [Lookup Document REST API](/rest/api/searchservice/lookup-document) returns the specific document. For broader testing, you should wait until the index is fully loaded, and then use queries to verify the context you expect to see.
 
-You can use [Search Explorer](search-explorer.md) or a Web testing tool like [Postman](search-get-started-rest.md) to check for updated content.
+You can use [Search Explorer](search-explorer.md) or a [REST client](search-get-started-rest.md) to check for updated content.
 
 If you added or renamed a field, use [$select](search-query-odata-select.md) to return that field: `search=*&$select=document-id,my-new-field,some-old-field&$count=true`
 
diff --git a/articles/search/search-more-like-this.md b/articles/search/search-more-like-this.md
@@ -64,7 +64,7 @@ GET /indexes/hotels-sample-index/docs?moreLikeThis=20&searchFields=Description&$
 
 ## Next steps
 
-You can use any web testing tool to experiment with this feature.  We recommend using Postman for this exercise.
+You can use any REST client for this exercise.
 
 > [!div class="nextstepaction"]
-> [Explore Azure AI Search REST APIs using Postman](search-get-started-rest.md)
+> [Quickstart: Azure AI Search using REST](search-get-started-rest.md)
diff --git a/articles/search/search-performance-analysis.md b/articles/search/search-performance-analysis.md
@@ -79,7 +79,7 @@ AzureDiagnostics
 
 ## Measure individual queries
 
-In some cases, it can be useful to test individual queries to see how they're performing. To do this, it's important to be able to see how long the search service takes to complete the work, as well as how long it takes to make the round-trip request from the client and back to the client. The diagnostics logs could be used to look up individual operations, but it might be easier to do this all from a client tool, such as Postman.
+In some cases, it can be useful to test individual queries to see how they're performing. To do this, it's important to be able to see how long the search service takes to complete the work, as well as how long it takes to make the round-trip request from the client and back to the client. The diagnostics logs could be used to look up individual operations, but it might be easier to do this all from a REST client.
 
 In the example below, a REST-based search query was executed. Azure AI Search includes in every response the number of milliseconds it takes to complete the query, visible in the Headers tab, in "elapsed-time". Next to Status at the top of the response, you'll find the round-trip duration, in this case, 418 milliseconds (ms). In the results section, the “Headers” tab was chosen. Using these two values, highlighted with a red box in the image below, we see the search service took 21 ms to complete the search query and the entire client round-trip request took 125 ms. By subtracting these two numbers we can determine that it took 104-ms additional time to transmit the search query to the search service and to transfer the search results back to the client.
 
diff --git a/articles/search/search-security-manage-encryption-keys.md b/articles/search/search-security-manage-encryption-keys.md
@@ -72,7 +72,7 @@ The following tools and services are used in this scenario.
 You should have a search client that can create the encrypted object. Into this code, you reference a key vault key and Active Directory registration information. This code could be a working app, or prototype code such as the [C# code sample DotNetHowToEncryptionUsingCMK](https://github.com/Azure-Samples/search-dotnet-getting-started/tree/master/DotNetHowToEncryptionUsingCMK).
 
 > [!TIP]
-> You can use [Postman](search-get-started-rest.md) or [Azure PowerShell](search-get-started-powershell.md) to call REST APIs that create indexes and synonym maps that include an encryption key parameter. You can also use Azure SDKs. Portal support for adding a key to indexes or synonym maps isn't supported.
+> You can use a [REST client](search-get-started-rest.md) or [Azure PowerShell](search-get-started-powershell.md) to create indexes and synonym maps that include an encryption key parameter. You can also use Azure SDKs. Portal support for adding a key to indexes or synonym maps isn't supported.
 
 ## Key Vault tips
 
diff --git a/articles/search/speller-how-to-add.md b/articles/search/speller-how-to-add.md
@@ -28,7 +28,7 @@ You can improve recall by spell-correcting words in a query before they reach th
 
 + [A query request](/rest/api/searchservice/preview-api/search-documents) that has `speller=lexicon` and `queryLanguage` set to a [supported language](#supported-languages). Spell check works on strings passed in the `search` parameter. It's not supported for filters, fuzzy search, wildcard search, regular expressions, or vector queries.
 
-Use a search client that supports preview APIs on the query request. For REST, you can use [Postman](search-get-started-rest.md), another web client, or code that you've modified to make REST calls to the preview APIs. You can also use beta releases of the Azure SDKs.
+Use a search client that supports preview APIs on the query request. You can use a [REST client](search-get-started-rest.md) or code that you've modified to make REST calls to the preview APIs. You can also use beta releases of the Azure SDKs.
 
 | Client library | Versions |
 |----------|----------|
diff --git a/articles/search/vector-search-how-to-query.md b/articles/search/vector-search-how-to-query.md
@@ -30,7 +30,7 @@ This article uses REST examples. For code samples in other languages, see the [a
 
 + [A vector store on Azure AI Search](vector-search-how-to-create-index.md).
 
-+ Visual Studio Code with a [REST client](https://marketplace.visualstudio.com/items?itemName=humao.rest-client) and sample data if you want to run these examples on your own. See [Quickstart: Create a search index in Azure AI Search using REST](search-get-started-rest.md) for help with getting started.
++ Visual Studio Code with a [REST client](https://marketplace.visualstudio.com/items?itemName=humao.rest-client) and sample data if you want to run these examples on your own. See [Quickstart: Azure AI Search using REST](search-get-started-rest.md) for help with getting started.
 
 > [!TIP]
 > To quickly determine whether your index has vectors, look for fields of type `Collection(Edm.Single)`, with a `dimensions` attribute, and a `vectorSearchProfile` assignment.
