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Update search-limits-quotas-capacity.md
Updated with new support for shared private links in higher tiers.
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articles/search/search-limits-quotas-capacity.md

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ms.author: heidist
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ms.service: azure-ai-search
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ms.topic: conceptual
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ms.date: 10/17/2024
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ms.date: 10/22/2024
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ms.custom:
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- references_regions
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| Private endpoint indexer support | No | Yes | Yes | Yes | Yes | No | Yes | Yes |
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| Private endpoint support for indexers with a skillset<sup>1</sup> | No | No | No | Yes | Yes | No | Yes | Yes |
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| Private endpoint support for indexers with a skillset and integrated vectorization <sup>2</sup> | No | Yes | Yes | Yes | Yes | No | Yes | Yes |
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| Maximum private endpoints | N/A | 10 or 30 | 100 | 400 | 400 | N/A | 20 | 20 |
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| Maximum distinct resource types<sup>2</sup> | N/A | 4 | 7 | 15 | 15 | N/A | 4 | 4 |
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| Maximum distinct resource types<sup>3</sup> | N/A | 4 | 7 | 15 | 15 | N/A | 4 | 4 |
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<sup>1</sup> AI enrichment and image analysis are computationally intensive and consume disproportionate amounts of available processing power. For this reason, private connections are disabled on lower tiers to ensure the performance and stability of the search service itself.
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<sup>2</sup> The number of distinct resource types are computed as the number of unique `groupId` values used across all shared private link resources for a given search service, irrespective of the status of the resource.
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<sup>2</sup> High-capacity services created after April 3, 2024 in the regions listed under [Partition Storage](search-limits-quotas-capacity.md#partition-storage-gb) and running [integrated vectorization](vector-search-integrated-vectorization.md) workloads at indexing time support shared private links in paid tiers. The system must detect at least a skill that is embedding data.
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<sup>3</sup> The number of distinct resource types are computed as the number of unique `groupId` values used across all shared private link resources for a given search service, irrespective of the status of the resource.
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## Synonym limits
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