| title | description | services | ms.service | ms.subservice | ms.custom | ms.devlang | ms.topic | author | ms.author | ms.reviewer | manager | ms.date |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Monitoring & performance tuning - Azure SQL Database | Microsoft Docs |
Tips for performance tuning in Azure SQL Database through evaluation and improvement. |
sql-database |
sql-database |
performance |
conceptual |
danimir |
v-daljep |
carlrab |
craigg |
10/23/2018 |
Azure SQL Database is automatically managed and flexible data service where you can easily monitor usage, add or remove resources (CPU, memory, I/O), find recommendations that can improve performance of your database, or let database adapt to your workload and automatically optimize performance.
Monitoring the performance of a SQL database in Azure starts with monitoring the resource utilization relative to the level of database performance you choose. Azure SQL Database enables you to identify opportunities to improve and optimize query performance without changing resources by reviewing performance tuning recommendations. Missing indexes and poorly optimized queries are common reasons for poor database performance. You can apply these tuning recommendations to improve performance of your workload. You can also let Azure SQL database to automatically optimize performance of your queries by applying all identified recommendations and verifying that they improve database performance.
You have the following options for monitoring and troubleshooting database performance:
- In the Azure portal, click SQL databases, select the database, and then use the Monitoring chart to look for resources approaching their maximum. DTU consumption is shown by default. Click Edit to change the time range and values shown.
- Use Query Performance Insight to identify the queries that spend the most of resources.
- Use SQL Database Advisor to view recommendations for creating and dropping indexes, parameterizing queries, and fixing schema issues.
- Use Azure SQL Intelligent Insights for automatic monitoring of your database performance. Once a performance issue is detected, a diagnostic log is generated with details and Root Cause Analysis (RCA) of the issue. Performance improvement recommendation is provided when possible.
- Enable automatic tuning and let Azure SQL database automatically fix identified performance issues.
- Use dynamic management views (DMVs), extended events, and the Query Store for more detailed troubleshooting of performance issues.
Tip
See performance guidance to find techniques that you can use to improve performance of Azure SQL Database after identifying the performance issue using one or more of the above methods.
In the Azure portal, you can monitor a single database�s utilization by selecting your database and clicking the Monitoring chart. This brings up a Metric window that you can change by clicking the Edit chart button. Add the following metrics:
- CPU percentage
- DTU percentage
- Data IO percentage
- Database size percentage
Once you've added these metrics, you can continue to view them in the Monitoring chart with more information on the Metric window. All four metrics show the average utilization percentage relative to the DTU of your database. See the DTU-based purchasing model and vCore-based purchasing model articles for more information about service tiers.
You can also configure alerts on the performance metrics. Click the Add alert button in the Metric window. Follow the wizard to configure your alert. You have the option to alert if the metrics exceed a certain threshold or if the metric falls below a certain threshold.
For example, if you expect the workload on your database to grow, you can choose to configure an email alert whenever your database reaches 80% on any of the performance metrics. You can use this as an early warning to figure out when you might have to switch to the next highest compute size.
The performance metrics can also help you determine if you are able to downgrade to a lower compute size. Assume you are using a Standard S2 database and all performance metrics show that the database on average does not use more than 10% at any given time. It is likely that the database will work well in Standard S1. However, be aware of workloads that spike or fluctuate before making the decision to move to a lower compute size.
To diagnose and resolve performance issues, begin by understanding the state of each active query and the conditions that cause performance issues relevant to each workload state. To improve Azure SQL Database performance, understand that each active query request from your application is either in a running or a waiting state. When troubleshooting a performance issue in Azure SQL Database, keep the following chart in mind as you read through this article to diagnose and resolve performance issues.
For a workload with performance issues, the performance issue may be due to CPU contention (a running-related condition) or individual queries are waiting on something (a waiting-related condition).
As a general guideline, if your CPU utilization is consistently at or above 80%, you have a running-related performance issue. If you have a running-related issue, it may be caused by insufficient CPU resources or it may be related to one of the following conditions:
- Too many running queries
- Too many compiling queries
- One or more executing queries are using a sub-optimal query plan
If you determine that you have a running-related performance issue, your goal is to identify the precise issue using one or more methods. The most common methods for identifying running-related issues are:
-
Use the Azure portal to monitor CPU percentage utilization.
-
Use the following dynamic management views:
- sys.dm_db_resource_stats returns CPU, I/O, and memory consumption for an Azure SQL Database database. One row exists for every 15 seconds, even if there is no activity in the database. Historical data is maintained for one hour.
- sys.resource_stats returns CPU usage and storage data for an Azure SQL Database. The data is collected and aggregated within five-minute intervals.
Important
For a set a T-SQL queries using these DMVs to troubleshoot CPU utilization issues, see Identify CPU performance issues.
Once you identify the issue, you can either tune the problem queries or upgrade the compute size or service tier to increase the capacity of your Azure SQL database to absorb the CPU requirements. For information on scaling resources for single databases, see Scale single database resources in Azure SQL Database and for scaling resources for elastic pools, see Scale elastic pool resources in Azure SQL Database. For information on scaling a managed instance, see Instance-level resource limits.
Once you are certain that you are not facing a high-CPU, running-related performance issue, you are facing a waiting-related performance issue. Namely, your CPU resources are not being used efficiently because the CPU is waiting on some other resource. In this case, your next step is to identify what your CPU resources are waiting on. The most common methods for showing the top wait type categories:
- The Query Store provides wait statistics per query over time. In Query Store, wait types are combined into wait categories. The mapping of wait categories to wait types is available in sys.query_store_wait_stats.
- sys.dm_db_wait_stats returns information about all the waits encountered by threads that executed during operation. You can use this aggregated view to diagnose performance issues with Azure SQL Database and also with specific queries and batches.
- sys.dm_os_waiting_tasks returns information about the wait queue of tasks that are waiting on some resource.
As shown in the previous chart, the most common waits are:
- Locks (blocking)
- I/O
tempdb-related contention- Memory grant waits
Important
For a set a T-SQL queries using these DMVs to troubleshoot these waiting-related issues, see:
Finally, if there are no actionable items that can improve performance of your database, you can change the amount of resources available in Azure SQL Database. You can assign more resources by changing the DTU service tier of a single database or increase the eDTUs of an elastic pool at any time. Alternatively, if you're using the vCore-based purchasing model, you can change either the service tier or increase the resources allocated to your database.
- For single databases, you can change service tiers or compute resources on-demand to improve database performance.
- For multiple databases, consider using elastic pools to scale resources automatically.
You can change application code to more optimally use the database, change indexes, force plans, or use hints to manually adapt the database to your workload. Find some guidance and tips for manual tuning and rewriting the code in the performance guidance topic article.
- To enable automatic tuning in Azure SQL Database and let automatic tuning feature fully manage your workload, see Enable automatic tuning.
- To use manual tuning, you can review Tuning recommendations in Azure portal and manually apply the ones that improve performance of your queries.
- Change resources that are available in your database by changing Azure SQL Database service tiers