Merge pull request #109 from HeidiSteen/heidist-regions-2

Crosslink fixes

Author: prmerger-automator[bot]

articles/search/search-capacity-planning.md

@@ -156,7 +156,7 @@ Storage needs are determined by the size of the indexes you expect to build. The
 
 We recommend estimating on a billable tier, Basic or above. The Free tier runs on physical resources shared by multiple customers and is subject to factors beyond your control. Only the dedicated resources of a billable search service can accommodate larger sampling and processing times for more realistic estimates of index quantity, size, and query volumes during development. 
 
-1. [Review service limits at each tier](./search-limits-quotas-capacity.md#service-limits) to determine whether lower tiers can support the number of indexes you need. Consider whether you need multiple copies of an index for active development, testing, and production. 
+1. [Review service limits at each tier](search-limits-quotas-capacity.md#service-limits) to determine whether lower tiers can support the number of indexes you need. Consider whether you need multiple copies of an index for active development, testing, and production. 
 
    A search service is subject to object limits (maximum number of indexes, indexers, skillsets, etc.) and storage limits. Whichever limit is reached first is the effective limit. 
 

articles/search/search-performance-tips.md

@@ -103,7 +103,7 @@ The tier of your search service and the number of replicas/partitions also have
 
 ### Tip: Create a new high capacity search service
 
-Basic and standard services created [in supported regions]([supported regions](search-limits-quotas-capacity.md#service-limits) after April 3, 2024 have more storage per partition than older services. Before upgrading to a higher tier and a higher billable rate, revisit the [tier service limits](search-limits-quotas-capacity.md#service-limits) to see if the same tier on a newer service gives you the necessary storage.
+Basic and standard services created [in supported regions](search-limits-quotas-capacity.md#service-limits) after April 3, 2024 have more storage per partition than older services. Before upgrading to a higher tier and a higher billable rate, revisit the [tier service limits](search-limits-quotas-capacity.md#service-limits) to see if the same tier on a newer service gives you the necessary storage.
 
 ### Tip: Upgrade to a Standard S2 tier
 

articles/search/search-region-support.md

@@ -23,7 +23,7 @@ This article identifies the cloud regions in which Azure AI Search is available.
 |---------|--------------|
 | [Extra capacity](search-limits-quotas-capacity.md#service-limits) | Higher capacity partitions became available in selected regions starting in April 2024 with a second wave following in May 2024. Currently, there are just a few regions that *don't* offer higher capacity partitions. If you're using an older search service, create a new search service to benefit from more capacity at the same billing rate. To check existing capacity, [find your search service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices) and select the **Properties** tab in the middle of the Overview page. To check search service age, follow [these instructions](vector-search-index-size.md#how-to-check-service-creation-date). Regional support for extra capacity is noted in the footnotes of this article.|
 | [Availability zones](search-reliability.md#availability-zone-support) | Divides a region's data centers into distinct physical location groups, providing high-availability within the same geo. Regional support is noted in this article. |
-| [Azure AI enrichment](cognitive-search-concept-intro.md) | Refers to skills that make internal calls to Azure AI for enrichment and transformation during indexing. Integration requires that Azure AI Search coexists with an [Azure AI multi-service account](/azure/ai-services/multi-service-resource) in the same physical region. |
+| [Azure AI enrichment](cognitive-search-concept-intro.md) | Refers to skills that make internal calls to Azure AI for enrichment and transformation during indexing. Integration requires that Azure AI Search coexists with an [Azure AI multi-service account](/azure/ai-services/multi-service-resource) in the same physical region. Regional support is noted in this article. |
 | [Azure OpenAI integration](vector-search-integrated-vectorization.md)  | Refers to skills and vectorizers that make internal calls to deployed embedding and chat models on Azure OpenAI. Check [Azure OpenAI model region availability](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability) for the most current list of regions for each embedding and chat model. Specific Azure OpenAI models are in fewer regions, so be sure to check for joint regional availability before installing.|
 | [Azure AI Studio integration](vector-search-integrated-vectorization-ai-studio.md) | Refers to skills and vectorizers that make internal calls to the models hosted in the model catalog. Check [Azure AI Studio region availability](/azure/ai-studio/reference/region-support) for the most current list of regions. |
 | [Azure AI Vision 4.0 multimodal APIs for image vectorization](search-get-started-portal-image-search.md) | Refers to skills and vectorizers that call the multimodal embedding API. Check the [Azure AI Vision region list](/azure/ai-services/computer-vision/overview-image-analysis#region-availability) for joint regional availability. |

articles/search/search-sku-manage-costs.md

@@ -72,7 +72,7 @@ Cost management is built into the Azure infrastructure. Review [Billing and cost
 
 Follow these guidelines to minimize costs of an Azure AI Search solution.
 
-1. If possible, create a search service [in a region that has more storage per partition]([supported regions](search-limits-quotas-capacity.md#service-limits). If you're using multiple Azure resources in your solution, create them in the same region, or in as few regions as possible, to minimize or eliminate bandwidth charges.
+1. If possible, create a search service [in a region that has more storage per partition](search-limits-quotas-capacity.md#service-limits). If you're using multiple Azure resources in your solution, create them in the same region, or in as few regions as possible, to minimize or eliminate bandwidth charges.
 
 1. [Scale up](search-capacity-planning.md) for resource-intensive operations like indexing, and then readjust downwards for regular query workloads. If there are predictable patterns to your workloads, you might be able to synchronize scale up to coincide with the expected volume (you would need to write code to automate this).
 

articles/search/whats-new.md

@@ -53,7 +53,7 @@ ms.custom:
 
 | Item                         | Type |  Description |
 |-----------------------------|------|--------------|
-| [Higher capacity and more vector quota at every tier (same billing rate)](search-limits-quotas-capacity.md#service-limits) | Infrastructure | Partition sizes are now even larger for Standard 2 (S2), Standard 3 (S3), and Standard 3 High Density (S3 HD) for all services created after April 3, 2024. If you create a new service now, you get the larger partitions. If you created a new service between April 3 and May 17, you get the larger partitions automatically. <br><br>Storage Optimized tiers (L1 and L2) also have more capacity. L1 and L2 customers must create a new service to benefit from the higher capacity. There's no in-place upgrade at this time. <br><br>Extra capacity is now available in [more regions](search-limits-quotas-capacity.md#service-limits): Germany North​, Germany West Central​, South Africa North​, Switzerland West​, and Azure Government (Texas, Arizona, and Virginia).|
+| [Higher capacity and more vector quota at every tier (same billing rate)](search-limits-quotas-capacity.md#service-limits) | Infrastructure | For most regions, partition sizes are now even larger for Standard 2 (S2), Standard 3 (S3), and Standard 3 High Density (S3 HD) for services created after April 3, 2024. To get the larger partitions, create a new service in a [region that provides newer infrastructure](search-region-support.md). <br><br>Storage Optimized tiers (L1 and L2) also have more capacity. L1 and L2 customers must create a new service to benefit from the higher capacity. There's no in-place upgrade at this time. <br><br>Extra capacity is now available in [more regions](search-limits-quotas-capacity.md#service-limits): Germany North​, Germany West Central​, South Africa North​, Switzerland West​, and Azure Government (Texas, Arizona, and Virginia).|
 | [OneLake integration (preview)](search-how-to-index-onelake-files.md) | Feature | New indexer for OneLake files and OneLake shortcuts. If you use Microsoft Fabric and OneLake for data access to Amazon Web Services (AWS) and Google data sources, use this indexer to import external data into a search index. This indexer is available through the Azure portal, the [2024-05-01-preview REST API](/rest/api/searchservice/data-sources/create-or-update?view=rest-searchservice-2024-05-01-preview&preserve-view=true), and Azure SDK beta packages. |
 | [Vector relevance](vector-search-how-to-query.md) <br>[hybrid query relevance](hybrid-search-how-to-query.md) | Feature | Four enhancements improve vector and hybrid search relevance. <br><br>First, you can now set thresholds on vector search results to exclude low-scoring results. <br><br>Second, changes in the query architecture apply scoring profiles at the end of the query pipeline for every query type. Document boosting is a common scoring profile, and it now works as expected on vector and hybrid queries.<br><br>Third, you can set `MaxTextRecallSize` and `countAndFacetMode` in hybrid queries to control the quantity of BM25-ranked search results that flow into the hybrid ranking model. <br><br>Fourth, for vector and hybrid search, you can weight a vector query to have boost or diminish its importance in a multiquery request. |
 | [Binary vectors support](/rest/api/searchservice/supported-data-types) | Feature | `Collection(Edm.Byte)` is a new supported data type. This data type opens up integration with the [Cohere v3 binary embedding models](https://cohere.com/blog/int8-binary-embeddings) and custom binary quantization. Narrow data types lower the cost of large vector datasets. See [Index binary data for vector search](vector-search-how-to-index-binary-data.md) for more information.|