Hello @Ramesh, Kasetti (623) thanks for the questions. below are my answers with Azure docs you can refer to.
Can Azure Cognitive Search be used to store vector embeddings?
-Yes, Azure Cognitive Search can be used to store vector embeddings, which are numerical representations of text or images that capture their semantic meaning.
Docs: https://docs.microsoft.com/en-us/azure/search/cognitive-search-concept-intro
-If so, where are the embeddings stored?
Embeddings are stored in regular field definitions within the search index. You specify a field as EDmV2Vector type to store vectors. This field can then be used in semantic search scenarios.
Docs: https://docs.microsoft.com/en-us/azure/search/search-howto-vector-search
-If the user can't move Azure Cognitive Search to a new pricing tier, how can they migrate their indexes to a new instance on a different pricing tier?
To migrate an index to a different Azure Cognitive Search pricing tier, you need to provision a new search service on your desired tier first. You can't directly change the tier of an existing service. Then use the Index Migration tool to copy the index schema and data to the new service.
Docs: https://docs.microsoft.com/en-us/azure/search/search-howto-migrate-index
-Can Azure OpenAI service allow private link service connections?
Currently, the Azure OpenAI service does not support integrating private endpoints. It can only be accessed through public endpoints. However, you can restrict the public endpoint to your private VNet using firewall rules. This provides some security, but full private link support does not exist yet.
Hope that helps. Let me know if you have further questions
-Grace