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articles/cosmos-db/mongodb/vcore/background-indexing.md

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ms.service: cosmos-db
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ms.subservice: mongodb-vcore
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ms.topic: conceptual
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ms.date: 06/27/2024
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ms.date: 07/01/2024
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---
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# Background indexing (Preview)
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Background indexing is a technique that enables a database system to perform indexing operations on a collection without blocking other queries or updates. Azure Cosmos DB for Mongo vcore accepts the background indexing request and asynchronously performs it in background.
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Background indexing can be enabled using the property `enableIndexBuildBackground` set to `true`. All indexes would be created in background except the unique indexes, post enabling the property.
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If working with smaller tiers or workloads with higher I/O needs, it's recommended to predefine indexes on empty collections and avoid relying on background indexing.
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> [!NOTE]

articles/cosmos-db/mongodb/vcore/how-to-scale-cluster.md

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title: Scale or configure a cluster
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titleSuffix: Azure Cosmos DB for MongoDB vCore
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description: Scale an Azure Cosmos DB for MongoDB vCore cluster by changing the tier and disk size or change the configuration by enabling high availability.
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author: gahl-levy
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ms.author: gahllevy
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ms.reviewer: sidandrews
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author: avijitgupta
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ms.author: avijitgupta
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ms.reviewer: gahllevy
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ms.service: cosmos-db
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ms.subservice: mongodb-vcore
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ms.topic: how-to
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ms.date: 06/20/2024
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ms.date: 07/01/2024
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# Scaling and configuring Your Azure Cosmos DB for MongoDB vCore cluster
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[!INCLUDE[MongoDB vCore](~/reusable-content/ce-skilling/azure/includes/cosmos-db/includes/appliesto-mongodb-vcore.md)]
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Azure Cosmos DB for MongoDB vCore provides seamless scalability and high availability. This document serves as a quick guide for developers who want to learn how to scale and configure their clusters. When changes are made, they're performed live to the cluster without downtime.
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Azure Cosmos DB for MongoDB vCore provides seamless scalability and high availability. This document serves as a quick guide for developers who want to learn how to scale and configure their clusters. Changes to the cluster are performed live without downtime.
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## Prerequisites
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1. Sign in to the [Azure portal](https://portal.azure.com).
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1. Navigate to the existing Azure Cosmos DB for MongoDB vCore cluster page.
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2. Navigate to the existing Azure Cosmos DB for MongoDB vCore cluster page.
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1. From the Azure Cosmos DB for MongoDB vCore cluster page, select the **Scale** navigation menu option.
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3. From the Azure Cosmos DB for MongoDB vCore cluster page, select the **Scale** navigation menu option.
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:::image type="content" source="media/how-to-scale-cluster/select-scale-option.png" lightbox="media/how-to-scale-cluster/select-scale-option.png" alt-text="Screenshot of the Scale option on the page for an Azure Cosmos DB for MongoDB vCore cluster.":::
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> [!NOTE]
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> This change is performed live to the cluster without downtime.
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>
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> Upgrade or downgrade from burstable tiers to memory optimized tier isn't supported at the moment.
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1. Select **Save** to persist your change.
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2. Select **Save** to persist your change.
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## Increase disk size
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> [!NOTE]
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> This change is performed live to the cluster without downtime. Also, storage size can only be increased, not decreased.
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1. Select **Save** to persist your change.
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2. Select **Save** to persist your change.
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## Enable or disable high availability
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:::image type="content" source="media/how-to-scale-cluster/configure-high-availability.png" alt-text="Screenshot of the high availability checkbox in the Scale page of a cluster.":::
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1. Select **Save** to persist your change.
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2. Select **Save** to persist your change.
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## Next steps
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articles/cosmos-db/mongodb/vcore/indexing.md

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ms.service: cosmos-db
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ms.subservice: mongodb-vcore
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ms.topic: conceptual
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ms.date: 07/01/2024
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# Manage indexing in Azure Cosmos DB for MongoDB vcore
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## Compound indexes
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Compound indexes are required if your query needs the ability to **query or sort** data from two or more fields in each document in a collection.
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Compound indexes improve database performance by allowing efficient **querying and sorting** based on multiple fields within documents. This optimization reduces the need to scan entire collections, speeding up data retrieval and organization.
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The following command creates a compound index on the fields `author` and `launchDate` in opposite sort order.
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