Merge pull request #49603 from JulianePadrao/updates-configure-databases-for-optimal-performance

JamesJBarnett · web-flow · commit 719367fb05a0 · 2025-03-20T19:16:44.000-07:00
Updates to configure-databases-for-optimal-performance
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/1-introduction.yml b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/1-introduction.yml
@@ -6,8 +6,8 @@ metadata:
   prefetch-feature-rollout: true
   title: Introduction
   description: "Introduction"
-  ms.date: 05/05/2022
-  author: wwlpublish
+  ms.date: 03/20/2025
+  author: JulianePadrao
   ms.author: jupadrao
   ms.topic: unit
 azureSandbox: false
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/2-explore-database-maintenance-checks.yml b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/2-explore-database-maintenance-checks.yml
@@ -6,8 +6,8 @@ metadata:
   prefetch-feature-rollout: true
   title: Explore database maintenance checks
   description: "Explore database maintenance checks"
-  ms.date: 05/05/2022
-  author: wwlpublish
+  ms.date: 03/20/2025
+  author: JulianePadrao
   ms.author: jupadrao
   ms.topic: unit
 azureSandbox: false
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/3-describe-database-scoped-configuration-options.yml b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/3-describe-database-scoped-configuration-options.yml
@@ -6,8 +6,8 @@ metadata:
   prefetch-feature-rollout: true
   title: Describe database scoped configuration options
   description: "Describe database scoped configuration options"
-  ms.date: 05/05/2022
-  author: wwlpublish
+  ms.date: 03/20/2025
+  author: JulianePadrao
   ms.author: jupadrao
   ms.topic: unit
 azureSandbox: false
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/4-describe-automatic-tuning.yml b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/4-describe-automatic-tuning.yml
@@ -6,8 +6,8 @@ metadata:
   prefetch-feature-rollout: true
   title: Describe automatic tuning
   description: "Describe automatic tuning"
-  ms.date: 05/05/2022
-  author: wwlpublish
+  ms.date: 03/20/2025
+  author: JulianePadrao
   ms.author: jupadrao
   ms.topic: unit
 azureSandbox: false
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/5-describe-intelligent-query-processing.yml b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/5-describe-intelligent-query-processing.yml
@@ -6,8 +6,8 @@ metadata:
   prefetch-feature-rollout: true
   title: Describe intelligent query processing
   description: "Describe intelligent query processing"
-  ms.date: 05/05/2022
-  author: wwlpublish
+  ms.date: 03/20/2025
+  author: JulianePadrao
   ms.author: jupadrao
   ms.topic: unit
 azureSandbox: false
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/6-exercise-detect-correct-fragmentation-issues.yml b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/6-exercise-detect-correct-fragmentation-issues.yml
@@ -6,8 +6,8 @@ metadata:
   prefetch-feature-rollout: true
   title: 'Exercise: Detect and correct fragmentation issues'
   description: "Exercise: Detect and correct fragmentation issues"
-  ms.date: 05/05/2022
-  author: wwlpublish
+  ms.date: 03/20/2025
+  author: JulianePadrao
   ms.author: jupadrao
   ms.topic: unit
 azureSandbox: false
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/7-knowledge-check.yml b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/7-knowledge-check.yml
@@ -6,8 +6,8 @@ metadata:
   prefetch-feature-rollout: true
   title: Knowledge check
   description: "Knowledge check"
-  ms.date: 05/05/2022
-  author: wwlpublish
+  ms.date: 03/20/2025
+  author: JulianePadrao
   ms.author: jupadrao
   ms.topic: unit
 azureSandbox: false
@@ -22,43 +22,43 @@ quiz:
     choices:
     - content: "Azure SQL Managed Instance"
       isCorrect: false
-      explanation: "That's incorrect. Azure SQL Managed instance doesn't support automatic index management."
+      explanation: "Incorrect. Azure SQL Managed instance doesn't support automatic index management."
     - content: "Azure SQL Database"
       isCorrect: true
-      explanation: "That's correct. SQL Database supports automatic indexing creation and removal."
+      explanation: "Correct. SQL Database supports automatic indexing creation and removal."
     - content: "SQL Server in an Azure VM"
       isCorrect: false
-      explanation: "That's incorrect. SQL Server in a VM doesn't currently support automatic index management."
+      explanation: "Incorrect. SQL Server in a VM doesn't currently support automatic index management."
   - content: "Which statistics option allows statistics to be updated while a query executes against the object the statistics are based on?"
     choices:
     - content: "Auto Create Incremental Statistics"
       isCorrect: false
-      explanation: "That's incorrect. With this option, update of statistics will be blocked by query execution."
+      explanation: "Incorrect. With this option, update of statistics will be blocked by query execution."
     - content: "Auto Create Statistics"
       isCorrect: false
-      explanation: "That's incorrect. With this option, update of statistics will be blocked by query execution."
+      explanation: "Incorrect. With this option, update of statistics will be blocked by query execution."
     - content: "Auto Update Statistics Asynchronously"
       isCorrect: true
-      explanation: "That's correct. The 'Auto Update Statistics Asynchronously' option allows for statistics to be updated during query execution."
+      explanation: "Correct. The 'Auto Update Statistics Asynchronously' option allows for statistics to be updated during query execution."
   - content: "Which DMV shows the status of a plan updated by automatic tuning?"
     choices:
     - content: "sys.dm_db_tuning_recommendations"
       isCorrect: true
-      explanation: "That's correct. This DMV shows the recommendations and the status."
+      explanation: "Correct. This DMV shows the recommendations and the status."
     - content: "sys.dm_db_automatic_tuning_options"
       isCorrect: false
-      explanation: "That's incorrect. This catalog view shows the configuration of the feature."
+      explanation: "Incorrect. This catalog view shows the configuration of the feature."
     - content: "sys.query_store_query"
       isCorrect: false
-      explanation: "That's incorrect. This DMV will just show the history of query executions."
+      explanation: "Incorrect. This DMV will just show the history of query executions."
   - content: "Which component of resource governor allows you to configure limits on system resources?"
     choices:
     - content: "Workload groups"
       isCorrect: false
-      explanation: "That's incorrect. Workload groups or just an organization role, and don't get assigned resources."
+      explanation: "Incorrect. Workload groups or just an organization role, and don't get assigned resources."
     - content: "Classifier functions"
       isCorrect: false
-      explanation: "That's incorrect. Classifier functions assign connections to workload groups."
+      explanation: "Incorrect. Classifier functions assign connections to workload groups."
     - content: "Resource pools"
       isCorrect: true
-      explanation: "That's correct. Resource pools are where resources are assigned in resource governor."
+      explanation: "Correct. Resource pools are where resources are assigned in resource governor."
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/8-summary.yml b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/8-summary.yml
@@ -6,8 +6,8 @@ metadata:
   prefetch-feature-rollout: true
   title: Summary
   description: "Summary"
-  ms.date: 05/05/2022
-  author: wwlpublish
+  ms.date: 03/20/2025
+  author: JulianePadrao
   ms.author: jupadrao
   ms.topic: unit
 azureSandbox: false
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/1-introduction.md b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/1-introduction.md
@@ -1,15 +1,12 @@
 In recent versions of SQL Server, Microsoft has moved more configuration options to the database level, giving you more granularity in how your databases behave. Along with those options, they have introduced intelligent query processing features that allow the query optimizer to make better choices.
 
-Even when your database is in the cloud, on-going performance-related maintenance tasks are critical to the overall success of your applications. Whether it's a SQL Server instance in an Azure Virtual Machine or Azure SQL Database, you need to ensure your statistics are current, and your indexes are well organized.
+Even when your database is in the cloud, ongoing performance-related maintenance tasks are critical to the overall success of your applications. Whether it's a SQL Server instance in an Azure Virtual Machine or Azure SQL Database, you need to ensure your statistics are current, and your indexes are well organized.
 
 ## Learning objectives
 
 In this module, you will:
 
 - Understand database scoped configuration options
-
 - Understand maintenance tasks related to indexing and statistics
-
 - Understand the features of Intelligent Query Processing
-
 - Explore the automatic tuning feature in Azure
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/2-explore-database-maintenance-checks.md b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/2-explore-database-maintenance-checks.md
@@ -2,7 +2,7 @@ The query optimizer utilizes statistical information from the indexes to attempt
 
 Within Azure SQL maintenance tasks such as backups and integrity checks are handled for you, and while you may be able to get away with automatic updates keeping your statistics up-to-date, sometimes it's not enough.
 
-Having healthy indexes and statistics will ensure that any given plan will perform at optimal efficiency. Index maintenance should be performed regularly as data in your databases changes over time. You could change your index maintenance strategy based on the frequency of modifications to your data.
+Having healthy indexes and statistics ensure that any given plan will perform at optimal efficiency. Index maintenance should be performed regularly as data in your databases changes over time. You could change your index maintenance strategy based on the frequency of modifications to your data.
 
 ## Rebuild and reorganize
 
@@ -12,7 +12,7 @@ As data is inserted, updated, and deleted from indexes the logical ordering in t
 
 A reorganization of an index is an online operation that will defrag the leaf level of the index (both clustered and nonclustered). This defragmentation process will physically reorder the leaf-level pages to match the logical order of the nodes from left to right. During this process, the index pages are also compacted based on the configured fillfactor value.
 
-A rebuild can be either online or offline depending on the command executed or the edition of SQL Server being utilized. An offline rebuild process will drop and re-create the index itself. If you can do so online, a new index will be built in parallel to the existing index. Once the new index has been built, the existing one will be dropped and then the new one will be renamed to match the old index name. Keep in mind that the online version will require more space as the new index is built in parallel to the existing index.
+A rebuild can be either online or offline depending on the command executed or the edition of SQL Server being utilized. An offline rebuild process will drop and re-create the index itself. If you can do so online, a new index is built in parallel to the existing index. Once the new index has been built, the existing one is dropped and then the new one will be renamed to match the old index name. Keep in mind that the online version requires more space as the new index is built in parallel to the existing index.
 
 The common guidance for index maintenance is:
 
@@ -38,7 +38,7 @@ Statistics contain information about the distribution of data values within a co
 
 Cardinality estimates are then used by the query optimizer to generate the execution plan. Cardinality estimates also help the optimizer determine what type of operation (for example, index seek or scan) to use to retrieve the data requested.
 
-To see the list of user defined statistics with the last updated date, run the query below:
+To see the list of user defined statistics with the last updated date, run the following query:
 
 ```sql
 SELECT sp.stats_id, 
@@ -57,7 +57,7 @@ When you have `AUTO_CREATE_STATISTICS` option to `ON`, the query optimizer creat
 
 These methods provide high-quality query plans for most queries. At times, you may need to create more statistics using `CREATE STATISTICS` statement to improve specific query plans.
 
-It's recommended to keep the `AUTO_CREATE_STATISTICS` option enabled as it will allow the query optimizer to create statistics for query predicate columns automatically.
+It's recommended to keep the `AUTO_CREATE_STATISTICS` option enabled as it allows the query optimizer to create statistics for query predicate columns automatically.
 
 Whenever you encounter the following situations, consider creating statistics:
 
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/3-describe-database-scoped-configuration-options.md b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/3-describe-database-scoped-configuration-options.md
@@ -1,4 +1,4 @@
-SQL Server has always had configuration options that were set at the database level. For example, the recovery model has always been a database setting, but as more complex features have been introduced to the database, more options have been added. Many of these options are tied to the compatibility level of the database, which is itself a database level configuration option. Database configuration options break down into two groups, with a minor difference:
+SQL Server has always offered configuration options at the database level. For example, the recovery model has traditionally been a database setting. As more complex features have been introduced, extra options have been added. Many of these options are linked to the database's compatibility level, which is also a database-level configuration setting. These configuration options can be categorized into two groups, with a minor distinction.
 
 - Options configured by the `ALTER DATABASE SCOPED CONFIGURATION` syntax in T-SQL
 
@@ -34,4 +34,4 @@ Each database has its own compatibility level, which controls the behavior of th
 
 You can manage this setting when upgrading SQL Server to ensure that your queries have similar execution plans to the older version.
 
-Microsoft will support running on an older compatibility level for an extended period. You should upgrade to a newer compatibility level if possible, as many of the new features in Intelligent Query Processing are only available in compatibility level 140 or 150.
+Microsoft supports running on an older compatibility level for an extended period. You should upgrade to a newer compatibility level if possible, as many of the new features in Intelligent Query Processing are only available in compatibility level 140 or 150.
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/4-describe-automatic-tuning.md b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/4-describe-automatic-tuning.md
@@ -20,9 +20,9 @@ In the example above, you can see a check mark on **Plan ID 1**, which means tha
 
 The plan will revert back to the last known good plan after 15 executions of the query.
 
-When plan forcing occurs automatically, the database engine will apply the last known good plan and will also continue to monitor query execution plan performance. If the forced plan doesn't perform better than the previous plan, it will be then unforced and force a new plan to be compiled. If the forced plan continues to outperform the previously bad plan, it will remain forced until such time as a recompile occurs.
+When plan forcing happens automatically, the database engine applies the last known good plan and keeps an eye on query execution performance. If the forced plan doesn't perform better than the previous one, it's unforced, and a new plan is compiled. However, if the forced plan continues to outperform the previous bad plan, it stays in place until a recompile occurs.
 
-You can enable automatic plan correction via a T-SQL query, as shown below. The Query Store must be enabled and must be in Read-Write mode for the command to succeed. If either of those two criteria aren't met, the ALTER statement will fail.
+You can enable automatic plan correction via a T-SQL query. The Query Store must be enabled and must be in Read-Write mode for the command to succeed. If either of those two criteria aren't met, the ALTER statement fails.
 
 ```SQL
 ALTER DATABASE [WideWorldImporters] SET AUTOMATIC_TUNING (FORCE_LAST_GOOD_PLAN = ON);
@@ -32,11 +32,11 @@ You can examine the automatic tuning recommendations through a dynamic managemen
 
 ## Automatic index management
 
-Azure SQL Database can perform automatic index tuning. Over time, the database will learn about existing workloads and provide recommendations on adding or removing indexes in order to provide better performance. Like forcing improved query plans, the database can be configured to allow for automatic index creation or removal depending on existing index performance, as shown below:
+Azure SQL Database has the capability to perform automatic index tuning. Over time, it learns from existing workloads and provides recommendations for adding or removing indexes to enhance performance. Similar to forcing improved query plans, the database can be configured to automatically create or remove indexes based on their performance, as shown in the following image.
 
 :::image type="content" source="../media/module-44-optimize-resources-final-26.png" alt-text="Screenshot of Automatic tuning Options for Azure SQL Database.":::
 
-When enabled, the **Performance Recommendations** page will identify indexes that can be created or dropped depending on query performance. Remember this feature isn't available for on-premises databases and only available for Azure SQL Database.
+When enabled, the **Performance Recommendations** page identifies indexes that can be created or dropped depending on query performance. Remember this feature isn't available for on-premises databases and only available for Azure SQL Database.
 
 Alternatively, use the following query to see the automatic tuning features enabled in your database:
 
@@ -50,6 +50,6 @@ FROM sys.database_automatic_tuning_options
 
 Creating new indexes can consume resources, and the timing of the index creations is critical to ensure no negative effect is felt on your workloads.
 
-Azure SQL Database will monitor the resources required to implement new indexes to avoid causing performance degradation. The tuning action is postponed until the available resources are available, for example if resources are required for existing workloads and not available for creating an index.
+Azure SQL Database monitors the resources required to implement new indexes to avoid causing performance degradation. The tuning action is postponed until the available resources are available, for example if resources are required for existing workloads and not available for creating an index.
 
-Monitoring ensures any action taken won't harm performance. If an index is dropped and query performance noticeably degrades, the recently dropped index will be automatically recreated.
+Monitoring ensures any action taken won't harm performance. If an index is dropped and query performance noticeably degrades, the recently dropped index is automatically recreated.
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/5-describe-intelligent-query-processing.md b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/5-describe-intelligent-query-processing.md
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/6-exercise-detect-correct-fragmentation-issues.md b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/6-exercise-detect-correct-fragmentation-issues.md
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/8-summary.md b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/includes/8-summary.md
diff --git a/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/index.yml b/learn-pr/wwl-data-ai/configure-databases-for-optimal-performance/index.yml
