On Premium and Business Critical service tiers, this option will never drop unused indexes, but will drop duplicate indexes, if any.įORCE LAST GOOD PLAN (automatic plan correction) This option may be automatically disabled when queries with index hints are present in the workload, or when the workload performs partition switching. Unique indexes, including indexes supporting primary key and unique constraints, are never dropped. Index recommendations are not provided for tables where the clustered index or heap is larger than 10 GB.ĭrops unused (over the last 90 days) and duplicate indexes. If index creation fails, it will be retried during a future period of low utilization. Once the system identifies a period of low utilization and starts to create an index, it will not pause or cancel this operation even if resource utilization unexpectedly increases. If index addition is estimated to increase space utilization to over 90% toward maximum data size, index recommendation is not generated. When recommending a new index, the system considers space available in the database. Identifies indexes that may improve performance of your workload, creates indexes, and automatically verifies that performance of queries has improved. Single database and pooled database support The automatic tuning options available in Azure SQL Database and Azure SQL Managed Instance are: Automatic tuning option You enable automatic tuning for Azure SQL Managed Instance by using the ALTER DATABASE T-SQL statement.You enable automatic tuning for Azure SQL Database in the Azure portal or by using the ALTER DATABASE T-SQL statement.For additional technical information on the built-in intelligence mechanism, see SQL Server automatic tuning. Through the tuning history recorded, there exists a clear trace of tuning improvements made to each database in Azure SQL Database.Īzure SQL automatic tuning shares its core logic with the SQL Server automatic tuning feature in the database engine. If there is no improvement, or in the unlikely case performance regresses, changes made by automatic tuning are promptly reverted. Automated tuning operations applied are verified automatically to ensure there is a notable positive improvement to workload performance. Automatic tuning is designed to give user workloads the highest resource priority.Īutomatic tuning mechanisms are mature and have been perfected on several million databases running on Azure. In such case, "Disabled by the system" message will be shown in Azure portal and in sys.database_automatic_tuning_options DMV. The system can also temporarily disable automatic tuning operations to protect workload performance. Automated tuning recommendations are applied only at the times of a low utilization of CPU, Data IO, and Log IO. The system has been designed with care not to interfere with user workloads. Tuning operations applied to databases are fully safe for performance of your most intense workloads. Positive impact to DevOps resources and the total cost of ownership.Scale out capability on hundreds of thousands of databases.Tuning action Transact-SQL (T-SQL) scripts for manual deployments.Automated verification of performance gains.Automated performance tuning of databases.The longer a database runs with automatic tuning on, the better it performs.Īzure SQL Database and Azure SQL Managed Instance automatic tuning might be one of the most impactful features that you can enable to provide stable and peak performing database workloads. Automatic tuning learns horizontally from all databases on Azure through AI, and dynamically improves its tuning actions. This is achieved through dynamically adapting a database to changing workloads and applying tuning recommendations. Azure SQL Database and Azure SQL Managed Instance automatic tuning provides peak performance and stable workloads through continuous performance tuning based on AI and machine learning.Īutomatic tuning is a fully managed intelligent performance service that uses built-in intelligence to continuously monitor queries executed on a database and automatically improve their performance.
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