Merge pull request #271194 from HeidiSteen/heidist-april3

[azure search] updated portal screenshots

Author: v-dirichards

articles/search/media/search-create-service-portal/select-pricing-tier.png

@@ -138,6 +138,8 @@ Basic and Standard are the most common choices for production workloads, but man
 
 :::image type="content" source="media/search-create-service-portal/select-pricing-tier.png" lightbox="media/search-create-service-portal/select-pricing-tier.png" alt-text="Screenshot of Select a pricing tier page." border="true":::
 
+Search services created after April 3, 2024 have larger partitions and higher vector quotas.
+
 Remember, a pricing tier can't be changed once the service is created. If you need a higher or lower tier, you should re-create the service.
 
 ## Create your service

articles/search/media/search-sku-tier/tiers.png

@@ -41,7 +41,7 @@ sections:
       - question: |
           How do I integrate search into my solution?
         answer: |
-          Client code should call the client libraries or REST APIs to connect to a search index, formulate queries, and handle responses. You can also write code that builds and refreshes an index, or runs indexers programmatically or by script.
+          Client code should call the Azure SDK client libraries or REST APIs to connect to a search index, formulate queries, and handle responses. You can also write code that builds and refreshes an index, or runs indexers programmatically or by script.
 
       - question: |
           Is there functional parity across the various APIs?
@@ -70,7 +70,9 @@ sections:
       - question: |
           What does "indexing" mean in Azure AI Search?
         answer: |
-          It refers to the ingestion, parsing, and storing of textual content and tokens that populate a search index. Indexing creates inverted indexes and other physical data structures that support information retrieval. It creates vector indexes if the schema includes vector fields.
+          It refers to the ingestion, parsing, and storing of textual content and tokens that populate a search index. Indexing creates inverted indexes and other physical data structures that support information retrieval. 
+          
+          It creates vector indexes if the schema includes vector fields.
 
       - question: |
           Can I move, backup, and restore indexes?
@@ -113,7 +115,7 @@ sections:
       - question: |
           Can Azure AI Search vectorize my content or queries?
         answer: |
-          Integrated vectorization is now in public preview.
+          Built-in integrated vectorization is now in public preview. 
 
       - question: |
           Does my search service support vector search?

articles/search/search-create-service-portal.md

@@ -10,7 +10,7 @@ ms.service: cognitive-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 12/12/2023
+ms.date: 04/04/2024
 ---
 # Features of Azure AI Search
 
@@ -41,6 +41,7 @@ There's feature parity in all Azure public, private, and sovereign clouds, but s
 | Vector filters | [Apply filters before or after query execution](vector-search-filters.md) for greater precision during information retrieval. |
 | Hybrid information retrieval | Search for concepts and keywords in a single [hybrid query request](hybrid-search-how-to-query.md). </p>[**Hybrid search**](hybrid-search-overview.md) consolidates vector and text search, with optional semantic ranking and relevance tuning for best results.|
 | Integrated data chunking and vectorization (preview) | Native data chunking through [Text Split skill](cognitive-search-skill-textsplit.md) and native vectorization through [vectorizers](vector-search-how-to-configure-vectorizer.md)  and the [AzureOpenAIEmbeddingModel skill](cognitive-search-skill-azure-openai-embedding.md). </p>[**Integrated vectorization** (preview)](vector-search-integrated-vectorization.md) provides an end-to-end indexing pipeline from source files to queries.|
+| Integrated vector compression and quantization | Use [built-in scalar quantization](vector-search-how-to-configure-compression-storage.md) to reduce vector index size in memory and on disk. You can also forego storage of vectors you don't need, or assign narrow data types to vector fields for reduced storage requirements. |
 | **Import and vectorize data** (preview)| A [new wizard](search-get-started-portal-import-vectors.md) in the Azure portal that creates a full indexing pipeline that includes data chunking and vectorization. The wizard creates all of the objects and configuration settings. |
 
 ## AI enrichment and knowledge mining

articles/search/search-faq-frequently-asked-questions.yml

@@ -8,7 +8,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: cognitive-search
 ms.topic: conceptual
-ms.date: 11/21/2023
+ms.date: 04/04/2024
 ms.custom:
   - ignite-2023
 ---
@@ -28,7 +28,7 @@ In a few instances, the tier you choose determines the availability of [premium
 Pricing - or the estimated monthly cost of running the service - are shown in the portal's **Select Pricing Tier** page. You should check [service pricing](https://azure.microsoft.com/pricing/details/search/) to learn about estimated costs.
 
 > [!NOTE]
-> Looking for information about "Azure SKUs"? Start with [Azure pricing](https://azure.microsoft.com/pricing/) and then scroll down for links to per-service pricing pages.
+> Search services created after April 3, 2024 have larger partitions and higher vector quotas at almost every tier. For more information, see [service limits](search-limits-quotas-capacity.md#after-april-3-2024).
 
 ## Tier descriptions
 
@@ -77,7 +77,7 @@ Tiers determine the  maximum storage of the service itself, as well as the maxim
 
 ## Partition size and speed
 
-Tier pricing includes details about per-partition storage that ranges from 2 GB for Basic, up to 2 TB for Storage Optimized (L2) tiers. Other hardware characteristics, such as speed of operations, latency, and transfer rates, aren't published, but tiers that are designed for specific solution architectures are built on hardware that has the features to support those scenarios. For more information about partitions, see [Estimate and manage capacity](search-capacity-planning.md) and [Reliability in Azure AI Search](search-reliability.md).
+Tier pricing includes details about per-partition storage that ranges from 15 GB for Basic, up to 2 TB for Storage Optimized (L2) tiers. Other hardware characteristics, such as speed of operations, latency, and transfer rates, aren't published, but tiers that are designed for specific solution architectures are built on hardware that has the features to support those scenarios. For more information about partitions, see [Estimate and manage capacity](search-capacity-planning.md) and [Reliability in Azure AI Search](search-reliability.md).
 
 ## Billing rates
 

articles/search/search-features-list.md

@@ -1,6 +1,6 @@
 ---
 title: What's new in Azure AI Search
-description: Announcements of new and enhanced features, including a service rename of Azure Search to Azure AI Search.
+description: Announcements of new and enhanced features, including a service rename of Azure Cognitive Search to Azure AI Search.
 
 manager: nitinme
 author: HeidiSteen