fixed links to backup and restore samples

Author: HeidiSteen

articles/search/resource-tools.md

@@ -7,7 +7,7 @@ manager: nitinme
 ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: conceptual
-ms.date: 10/08/2024
+ms.date: 02/25/2025
 ---
 
 # Productivity tools and accelerators - Azure AI Search
@@ -20,7 +20,7 @@ Productivity tools are built by engineers at Microsoft, but aren't part of the A
 |-----------|------------ |-------------|
 | [Azure AI Search Lab](https://github.com/jelledruyts/azure-ai-search-lab) | Learning and experimentation lab to try out AI-enabled search scenarios in Azure. It provides a web application front-end which uses Azure AI Search and Azure OpenAI to execute searches with a variety of options - ranging from simple keyword search, to semantic ranking, vector and hybrid search, and using generative AI to answer search queries. | [https://github.com/jelledruyts/azure-ai-search-lab](https://github.com/jelledruyts/azure-ai-search-lab)  |
 | [Back up and Restore (C#)](https://github.com/Azure-Samples/azure-search-dotnet-utilities/blob/main/index-backup-restore) | Download the retrievable fields of an index to your local device and then upload the index and its content to a new search service. | [https://github.com/Azure-Samples/azure-search-dotnet-utilities/blob/main/index-backup-restore](https://github.com/Azure-Samples/azure-search-dotnet-utilities/blob/main/index-backup-restore) |
-| [Back up and Restore (Python)](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore) | Download the retrievable fields of an index to your local device and then upload the index and its content to a new search service. | [https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore) |
+| [Back up and Restore (Python)](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/utilities/index-backup-restore) | Download the retrievable fields of an index to your local device and then upload the index and its content to a new search service. | [https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/utilities/index-backup-restore](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/utilities/index-backup-restore) |
 | [Performance testing solution](https://github.com/Azure-Samples/azure-search-performance-testing/blob/main/README.md) | This solution helps you load test Azure AI Search. It uses Apache JMeter as an open source load and performance testing tool and Terraform to dynamically provision and destroy the required infrastructure on Azure. | [https://github.com/Azure-Samples/azure-search-performance-testing](https://github.com/Azure-Samples/azure-search-performance-testing) |
 | [Visual Studio Code extension](https://github.com/microsoft/vscode-azurecognitivesearch) | Although the extension is no longer available in the Visual Studio Code Marketplace, the code is open source. You can clone and modify the tool for your own use. | [https://github.com/microsoft/vscode-azurecognitivesearch](https://github.com/microsoft/vscode-azurecognitivesearch) |
 

articles/search/samples-python.md

@@ -58,7 +58,8 @@ The following samples are also published by the Azure AI Search team, but aren't
 
 | Repository | Description |
 |------------|-------------|
-| [azure-search-backup-and-restore.ipynb](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore) | Uses the **azure.search.documents** library in the Azure SDK for Python to make a local copy of the retrievable fields of a search index, and then push those fields to a new search index. |
+| [index-backup-and-restore.ipynb](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/utilities/index-backup-restore) | Uses the **azure.search.documents** library in the Azure SDK for Python to make a local copy of the retrievable fields of a search index, and then push those fields to a new search index. |
+| [resumable-index-backup-restore](https://github.com/Azure/azure-search-vector-samples/blob/main/demo-python/code/utilities/resumable-index-backup-restore/backup-and-restore.ipynb) | This sample accommodates larger indexes exceeding 100,000 documents.|
 
 > [!TIP]
 > Try the [Samples browser](/samples/browse/?languages=python&products=azure-cognitive-search) to search for Microsoft code samples in GitHub, filtered by product, service, and language.

articles/search/search-howto-reindex.md

@@ -228,13 +228,13 @@ Some modifications require an index drop and rebuild, replacing a current index
 | Assign an analyzer to a field | [Analyzers](search-analyzers.md) are defined in an index, assigned to fields, and then invoked during indexing to inform how tokens are created. You can add a new analyzer definition to an index at any time, but you can only *assign* an analyzer when the field is created. This is true for both the **analyzer** and **indexAnalyzer** properties. The **searchAnalyzer** property is an exception (you can assign this property to an existing field). |
 | Update or delete an analyzer definition in an index | You can't delete or change an existing analyzer configuration (analyzer, tokenizer, token filter, or char filter) in the index unless you rebuild the entire index. |
 | Add a field to a suggester | If a field already exists and you want to add it to a [Suggesters](index-add-suggesters.md) construct, rebuild the index. |
-| Switch tiers | In-place upgrades aren't supported. If you require more capacity, create a new service and rebuild your indexes from scratch. To help automate this process, you can use the **index-backup-restore** sample code in this [Azure AI Search .NET sample repo](https://github.com/Azure-Samples/azure-search-dotnet-utilities). This app backs up your index to a series of JSON files, and then recreate the index in a search service you specify.|
+| Switch tiers | In-place upgrades aren't supported. If you require more capacity, create a new service and rebuild your indexes from scratch. To help automate this process, you can use a code sample that backs up your index to a series of JSON files. You can then recreate the index in a search service you specify.|
 
 The order of operations is:
 
 1. [Get an index definition](/rest/api/searchservice/indexes/get) in case you need it for future reference, or to use as the basis for a new version.
 
-1. Consider using a backup and restore solution to preserve a copy of index content. There are solutions in [C#](https://github.com/liamca/azure-search-backup-restore/blob/master/README.md) and in [Python](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/index-backup-restore). We recommend the Python version because it's more up to date.
+1. Consider using a backup and restore solution to preserve a copy of index content. There are solutions in [C#](https://github.com/liamca/azure-search-backup-restore/blob/master/README.md) and in [Python](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/utilities/index-backup-restore). We recommend the Python version because it's more up to date.
 
    If you have capacity on your search service, keep the existing index while creating and testing the new one.
 

articles/search/search-reliability.md

@@ -189,7 +189,7 @@ If you don't use indexers, you would use your application code to push objects a
 
 ## Back up and restore alternatives
 
-A business continuity strategy for the data layer usually includes a restore-from-backup step. Because Azure AI Search isn't a primary data storage solution, Microsoft doesn't provide a formal mechanism for self-service backup and restore. However, you can use the **index-backup-restore** sample code in this [Azure AI Search .NET sample repo](https://github.com/Azure-Samples/azure-search-dotnet-utilities) to back up your index definition and snapshot to a series of JSON files, and then use these files to restore the index, if needed. This tool can also move indexes between service tiers.
+A business continuity strategy for the data layer usually includes a restore-from-backup step. Because Azure AI Search isn't a primary data storage solution, Microsoft doesn't provide a formal mechanism for self-service backup and restore. However, you can use the **index-backup-restore** sample code in this [Azure AI Search .NET sample repo](https://github.com/Azure-Samples/azure-search-dotnet-utilities)  or in this [Python sample repository](https://github.com/Azure/azure-search-vector-samples/blob/main/demo-python/code/utilities/index-backup-restore/azure-search-backup-and-restore.ipynb) to back up your index definition and snapshot to a series of JSON files, and then use these files to restore the index, if needed. This tool can also move indexes between service tiers.
 
 Otherwise, your application code used for creating and populating an index is the de facto restore option if you delete an index by mistake. To rebuild an index, you would delete it (assuming it exists), recreate the index in the service, and reload by retrieving data from your primary data store.
 

articles/search/search-sku-tier.md

@@ -113,7 +113,7 @@ There's no built-in support to upgrade or downgrade tiers. If you want to switch
 
 + Delete the old search service once you're sure it's no longer needed.
 
-For large indexes that you don't want to rebuild from scratch, consider using the [backup and restore sample](https://github.com/Azure-Samples/azure-search-dotnet-utilities/blob/main/index-backup-restore/README.md) to move them.
+For large indexes that you don't want to rebuild from scratch, consider using one of the backup and restore samples to move them:[backup and restore sample (C#)](https://github.com/Azure-Samples/azure-search-dotnet-utilities/blob/main/index-backup-restore/README.md), [backup and restore sample (Python)](https://github.com/Azure/azure-search-vector-samples/blob/main/demo-python/code/utilities/index-backup-restore/azure-search-backup-and-restore.ipynb), [larget index backup and restore (Python)](https://github.com/Azure/azure-search-vector-samples/blob/main/demo-python/code/utilities/resumable-index-backup-restore/backup-and-restore.ipynb).
 
 ## Next steps