Merge pull request #278180 from alexbuckgit/alexbuckgit/docutune-autopr-20240613-184702-7018515-ignore-build

[BULK] - DocuTune v1.4.1 - Standardize formatting of abbreviations (part 3)

Author: JamesJBarnett

articles/container-instances/confidential-containers-attestation-concepts.md

@@ -19,11 +19,11 @@ In Confidential Containers on ACI you can use an attestation token to verify tha
 
 - Is running on confidential computing hardware. In this case AMD SEV-SNP.
 - Is running on an Azure compliant utility VM.
-- Is enforcing the expected confidential computing enforcement policy (cce) that was generated using [tooling](https://github.com/Azure/azure-cli-extensions/blob/main/src/confcom/azext_confcom/README.md).
+- Is enforcing the expected confidential computing enforcement (CCE) policy that was generated using [tooling](https://github.com/Azure/azure-cli-extensions/blob/main/src/confcom/azext_confcom/README.md).
 
 ## Full attestation 
 
-Expanding upon this concept of attestation. Full attestation captures all the components that are part of the Trusted Execution Environment that is remotely verifiable. To achieve full attestation, in Confidential Containers, we have introduced the notion of a cce policy, which defines a set of rules, which is enforced in the utility VM. The security policy is encoded in the attestation report as an SHA-256 digest stored in the HostData attribute, as provided to the AMD SEV-SNP hardware by the host operating system during the VM boot-up. This means that the security policy enforced by the utility VM is immutable throughout the lifetime of the utility VM.
+Expanding upon this concept of attestation. Full attestation captures all the components that are part of the Trusted Execution Environment that is remotely verifiable. To achieve full attestation, in Confidential Containers, we have introduced the notion of a CCE policy, which defines a set of rules, which is enforced in the utility VM. The security policy is encoded in the attestation report as an SHA-256 digest stored in the HostData attribute, as provided to the AMD SEV-SNP hardware by the host operating system during the VM boot-up. This means that the security policy enforced by the utility VM is immutable throughout the lifetime of the utility VM.
 
 The exhaustive list of attributes that are part of the SEV-SNP attestation can be found [here](https://www.amd.com/system/files/TechDocs/56860.pdf).
 
@@ -33,7 +33,7 @@ Some important fields to consider in an attestation token returned by [Microsoft
 |:---------------------------:|:----------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------:|
 | x-ms-attestation-type       | sevsnpvm                                                         | String value that describes the attestation type. For example, in this scenario sevsnp hardware |
 | x-ms-compliance-status      | azure-compliant-uvm                                              | Compliance status of the utility VM that runs the container group.                              |
-| x-ms-sevsnpvm-hostdata      | 670fff86714a650a49b58fadc1e90fedae0eb32dd51e34931c1e7a1839c08f6f | Hash of the cce policy that was generated using tooling during deployment.                      |
+| x-ms-sevsnpvm-hostdata      | 670fff86714a650a49b58fadc1e90fedae0eb32dd51e34931c1e7a1839c08f6f | Hash of the CCE policy that was generated using tooling during deployment.                      |
 | x-ms-sevsnpvm-is-debuggable | false                                                            | Flag to indicate whether the underlying hardware is running in debug mode                       |
 
 ## Sample attestation token generated by MAA

articles/container-instances/container-instances-orchestrator-relationship.md

@@ -51,7 +51,7 @@ Rather than scaling out the number of virtual machines in your cluster, then dep
 
 ## Sample implementation: virtual nodes for Azure Kubernetes Service (AKS)
 
-To rapidly scale application workloads in an [Azure Kubernetes Service](../aks/intro-kubernetes.md) (AKS) cluster, you can use *virtual nodes* created dynamically in Azure Container Instances. Virtual nodes enable network communication between pods that run in ACI and the AKS cluster. 
+To rapidly scale application workloads in an [Azure Kubernetes Service (AKS)](../aks/intro-kubernetes.md) cluster, you can use *virtual nodes* created dynamically in Azure Container Instances. Virtual nodes enable network communication between pods that run in ACI and the AKS cluster. 
 
 Virtual nodes currently support Linux container instances. Get started with virtual nodes using the [Azure CLI](../aks/virtual-nodes-cli.md) or [Azure portal](../aks/virtual-nodes-portal.md).
 

articles/container-registry/container-registry-geo-replication.md

@@ -34,7 +34,7 @@ A geo-replicated registry provides the following benefits:
     | Microsoft.ContainerRegistry/registries/replications/write | Delete a replication |
 
 ## Example use case
-Contoso runs a public presence website located across the US, Canada, and Europe. To serve these markets with local and network-close content, Contoso runs [Azure Kubernetes Service](../aks/index.yml) (AKS) clusters in West US, East US, Canada Central, and West Europe. The website application, deployed as a Docker image, utilizes the same code and image across all regions. Content local to that region is retrieved from a database, which is provisioned uniquely in each region. Each regional deployment has its unique configuration for resources like the local database.
+Contoso runs a public presence website located across the US, Canada, and Europe. To serve these markets with local and network-close content, Contoso runs [Azure Kubernetes Service (AKS)](../aks/index.yml) clusters in West US, East US, Canada Central, and West Europe. The website application, deployed as a Docker image, utilizes the same code and image across all regions. Content local to that region is retrieved from a database, which is provisioned uniquely in each region. Each regional deployment has its unique configuration for resources like the local database.
 
 The development team is located in Seattle, WA, and utilizes the West US data center.
 

articles/cosmos-db/cassandra/consistency-mapping.md

@@ -135,7 +135,7 @@ Apache Cassandra would only provide eventual consistency for reads across other
 
 ### Metrics
 
-If your Azure Cosmos DB account is configured with a consistency level other than the strong consistency, review the *Probabilistically Bounded Staleness* (PBS) metric. The metric captures the probability that your clients may get strong and consistent reads for your workloads. This metric is exposed in the Azure portal. To find more information about the PBS metric, see [Monitor Probabilistically Bounded Staleness (PBS) metric](../how-to-manage-consistency.md#monitor-probabilistically-bounded-staleness-pbs-metric).
+If your Azure Cosmos DB account is configured with a consistency level other than the strong consistency, review the *Probabilistically Bounded Staleness (PBS)* metric. The metric captures the probability that your clients may get strong and consistent reads for your workloads. This metric is exposed in the Azure portal. To find more information about the PBS metric, see [Monitor Probabilistically Bounded Staleness (PBS) metric](../how-to-manage-consistency.md#monitor-probabilistically-bounded-staleness-pbs-metric).
 
 Probabilistically bounded staleness shows how eventual is your eventual consistency. This metric provides an insight into how often you can get a stronger consistency than the consistency level that you've currently configured on your Azure Cosmos DB account. In other words, you can see the probability (measured in milliseconds) of getting consistent reads for a combination of write and read regions.
 

articles/cosmos-db/consistency-levels.md

@@ -143,7 +143,7 @@ In practice, you may often get stronger consistency guarantees. Consistency guar
 
 If there are no write operations on the database, a read operation with **eventual**, **session**, or **consistent prefix** consistency levels is likely to yield the same results as a read operation with strong consistency level.
 
-If your account is configured with a consistency level other than the strong consistency, you can find out the probability that your clients may get strong and consistent reads for your workloads. You can figure out this probability by looking at the *Probabilistically Bounded Staleness* (PBS) metric. This metric is exposed in the Azure portal, to learn more, see [Monitor Probabilistically Bounded Staleness (PBS) metric](how-to-manage-consistency.md#monitor-probabilistically-bounded-staleness-pbs-metric).
+If your account is configured with a consistency level other than the strong consistency, you can find out the probability that your clients may get strong and consistent reads for your workloads. You can figure out this probability by looking at the *Probabilistically Bounded Staleness (PBS)* metric. This metric is exposed in the Azure portal, to learn more, see [Monitor Probabilistically Bounded Staleness (PBS) metric](how-to-manage-consistency.md#monitor-probabilistically-bounded-staleness-pbs-metric).
 
 Probabilistically bounded staleness shows how eventual is your eventual consistency. This metric provides an insight into how often you can get a stronger consistency than the consistency level that you've currently configured on your Azure Cosmos DB account. In other words, you can see the probability (measured in milliseconds) of getting consistent reads for a combination of write and read regions.
 

articles/cosmos-db/mongodb/consistency-mapping.md

@@ -34,7 +34,7 @@ The following table illustrates how the native MongoDB write/read concerns are m
 
 :::image type="content" source="../media/consistency-levels-across-apis/consistency-model-mapping-mongodb.png" alt-text="MongoDB consistency model mapping" lightbox= "../media/consistency-levels-across-apis/consistency-model-mapping-mongodb.png":::
 
-If your Azure Cosmos DB account is configured with a consistency level other than the strong consistency, you can find out the probability that your clients may get strong and consistent reads for your workloads by looking at the *Probabilistically Bounded Staleness* (PBS) metric. This metric is exposed in the Azure portal, to learn more, see [Monitor Probabilistically Bounded Staleness (PBS) metric](../how-to-manage-consistency.md#monitor-probabilistically-bounded-staleness-pbs-metric).
+If your Azure Cosmos DB account is configured with a consistency level other than the strong consistency, you can find out the probability that your clients may get strong and consistent reads for your workloads by looking at the *Probabilistically Bounded Staleness (PBS)* metric. This metric is exposed in the Azure portal, to learn more, see [Monitor Probabilistically Bounded Staleness (PBS) metric](../how-to-manage-consistency.md#monitor-probabilistically-bounded-staleness-pbs-metric).
 
 Probabilistic bounded staleness shows how eventual is your eventual consistency. This metric provides an insight into how often you can get a stronger consistency than the consistency level that you have currently configured on your Azure Cosmos DB account. In other words, you can see the probability (measured in milliseconds) of getting strongly consistent reads for a combination of write and read regions.
 

articles/cosmos-db/mongodb/pre-migration-steps.md

@@ -85,7 +85,7 @@ Go through the spreadsheet and verify each collection against the [supported fea
 > [!NOTE]
 > Database Migration Assistant is a legacy utility meant to assist you with the pre-migration steps. We recommend you to use the [Azure Cosmos DB Migration for MongoDB extension](#azure-cosmos-db-migration-for-mongodb-extension) for all pre-migration steps.
 
-You may use the [Database Migration Assistant](programmatic-database-migration-assistant-legacy.md) (DMA) utility to assist you with pre-migration steps.
+You may use the [Database Migration Assistant (DMA)](programmatic-database-migration-assistant-legacy.md) utility to assist you with pre-migration steps.
 
 ## Pre-migration mapping
 

articles/cosmos-db/mongodb/programmatic-database-migration-assistant-legacy.md

@@ -19,7 +19,7 @@ ms.date: 04/20/2023
 
 ### Programmatic discovery using the Database Migration Assistant
 
-You may use the [Database Migration Assistant](https://github.com/AzureCosmosDB/Cosmos-DB-Migration-Assistant-for-API-for-MongoDB) (DMA) to assist you with the discovery stage and create the data estate migration sheet programmatically.
+You may use the [Database Migration Assistant (DMA)](https://github.com/AzureCosmosDB/Cosmos-DB-Migration-Assistant-for-API-for-MongoDB) to assist you with the discovery stage and create the data estate migration sheet programmatically.
 
 It's easy to [setup and run DMA](https://github.com/AzureCosmosDB/Cosmos-DB-Migration-Assistant-for-API-for-MongoDB#how-to-run-the-dma) through an Azure Data Studio client. It can be run from any machine connected to your source MongoDB environment.
 
@@ -46,7 +46,7 @@ Here's a sample database-level migration spreadsheet created by DMA:
 
 ### Programmatic assessment using the Database Migration Assistant
 
-[Database Migration Assistant](https://github.com/AzureCosmosDB/Cosmos-DB-Migration-Assistant-for-API-for-MongoDB) (DMA) also assists you with the assessment stage of pre-migration planning.
+[Database Migration Assistant (DMA)](https://github.com/AzureCosmosDB/Cosmos-DB-Migration-Assistant-for-API-for-MongoDB) also assists you with the assessment stage of pre-migration planning.
 
 Refer to the section [Programmatic discovery using the Database Migration Assistant](#programmatic-discovery-using-the-database-migration-assistant) to know how to setup and run DMA.
 
@@ -56,4 +56,3 @@ The results are printed as an output in the DMA notebook and saved to a CSV file
 
 > [!NOTE]
 > Database Migration Assistant does not perform an end-to-end assessment. It is a preliminary utility meant to assist you with the pre-migration steps.
-

articles/cosmos-db/postgresql/product-updates.md

@@ -72,7 +72,7 @@ Updates that change cluster internals, such as installing a [new minor PostgreSQ
 	* See all supported PostgreSQL versions [here](./reference-versions.md#postgresql-versions).
 	* [Upgrade to PostgreSQL 16](./howto-upgrade.md)
 * General availability: [Citus 12.1 with new features and PostgreSQL 16 support](https://www.citusdata.com/updates/v12-1).
-* General availability: Data encryption at rest using [Customer Managed Keys](./concepts-customer-managed-keys.md) (CMK) is now supported for all available regions.
+* General availability: Data encryption at rest using [Customer Managed Keys (CMK)](./concepts-customer-managed-keys.md) is now supported for all available regions.
    * See [this guide](./how-to-customer-managed-keys.md) for the steps to enable data encryption using customer managed keys. 
 * Preview: Geo-redundant backup and restore
     * Learn more about [backup and restore Azure Cosmos DB for PostgreSQL](./concepts-backup.md)

articles/data-factory/configure-azure-ssis-integration-runtime-performance.md

@@ -152,10 +152,10 @@ Here are the guidelines for setting the right value for the **AzureSSISMaxParall
 
 -   Choose a more powerful database such as s3 if the logging level is set to verbose. According our unofficial in-house testing, s3 pricing tier can support SSIS package execution with 2 nodes, 128 parallel counts and verbose logging level.
 
-You can also adjust the database pricing tier based on [database transaction unit](/azure/azure-sql/database/service-tiers-dtu) (DTU) usage information available on the Azure portal.
+You can also adjust the database pricing tier based on [database transaction unit (DTU)](/azure/azure-sql/database/service-tiers-dtu) usage information available on the Azure portal.
 
 ## Design for high performance
 Designing an SSIS package to run on Azure is different from designing a package for on-premises execution. Instead of combining multiple independent tasks in the same package, separate them into several packages for more efficient execution in the Azure-SSIS IR. Create a package execution for each package, so that they don’t have to wait for each other to finish. This approach benefits from the scalability of the Azure-SSIS integration runtime and improves the overall throughput.
 
 ## Related content
-Learn more about the Azure-SSIS Integration Runtime. See [Azure-SSIS Integration Runtime](concepts-integration-runtime.md#azure-ssis-integration-runtime).
+Learn more about the Azure-SSIS Integration Runtime. See [Azure-SSIS Integration Runtime](concepts-integration-runtime.md#azure-ssis-integration-runtime).