Azure SQL Performance Tuning

Welcome to the definitive guide for optimizing the performance of your Azure SQL Database and Azure SQL Managed Instance. This document covers a comprehensive set of strategies, tools, and best practices to ensure your applications run efficiently and cost-effectively.

Key areas we'll explore include:

Query Performance Indexing Strategies Resource Governance Monitoring & Diagnostics Advanced Techniques

Optimizing Query Performance

Efficient queries are the cornerstone of good database performance. This section focuses on identifying and resolving performance bottlenecks within your SQL queries.

Query Store

The Query Store automatically captures query history, plans, and runtime statistics. It helps you identify top resource-consuming queries and regressions.

Enable Query Store for your database.
Analyze performance trends and identify query regressions.
Force specific query plans for better performance.

Learn more: Query Store Documentation

Execution Plans

Understanding how SQL Server executes your queries is crucial for optimization. Analyze execution plans to pinpoint expensive operations.

Use SQL Server Management Studio (SSMS) or Azure Data Studio to view estimated and actual execution plans.
Look for table scans, index scans on large tables, and costly join operations.

Important: Always test query plan changes in a non-production environment before deploying to production.

Parameter Sensitive Plan Optimization

Parameter sniffing can lead to suboptimal execution plans. Azure SQL Database has built-in features to mitigate this.

Consider using query hints like RECOMPILE or OPTIMIZE FOR UNKNOWN for specific scenarios.
Review the behavior of stored procedures and complex queries.

Indexing Strategies

Proper indexing significantly reduces I/O and improves query response times. Incorrect or missing indexes are common performance killers.

Clustered and Non-Clustered Indexes

Understand the difference and when to use each type. A table can have only one clustered index.

The clustered index determines the physical order of data in the table.
Non-clustered indexes provide a logical ordering for faster lookups.

Index Recommendations

Azure SQL Database offers intelligent recommendations to help you create and maintain indexes.

Utilize the "Missing Index" DMVs (Dynamic Management Views) and the Database Advisor in Azure portal.
Regularly review and apply recommended index changes.


SELECT
    mig.avg_total_user_cost * mig.avg_user_impact * .01 AS estimated_impact,
    mid.equality_columns,
    mid.inequality_columns,
    mid.included_columns,
    migs.user_seeks,
    migs.user_scans,
    migs.last_user_seek,
    'CREATE INDEX ix_recommendation ON ' + mid.statement + '(' +
    REPLACE(REPLACE(REPLACE(mid.equality_columns, ']', ')]'), '[', '[') +
    CASE WHEN mid.inequality_columns IS NOT NULL THEN ',' + mid.inequality_columns ELSE '' END +
    ') ' + CASE WHEN mid.included_columns IS NOT NULL THEN 'INCLUDE (' + mid.included_columns + ')' ELSE '' END + ';' AS create_index_statement
FROM
    sys.dm_db_missing_index_groups AS mig
INNER JOIN
    sys.dm_db_missing_index_group_stats AS migs ON migs.group_handle = mig.group_handle
INNER JOIN
    sys.dm_db_missing_indexes AS mid ON mig.index_handle = mid.index_handle
WHERE
    migs.last_user_seek IS NOT NULL
ORDER BY
    estimated_impact DESC;

Index Maintenance

Indexes can become fragmented over time, reducing their effectiveness. Regularly maintain your indexes.

Schedule index fragmentation analysis and rebuilding/reorganizing operations.
Use `ALTER INDEX REORGANIZE` for less fragmented indexes and `ALTER INDEX REBUILD` for highly fragmented ones.

Tip: Aim to keep index fragmentation below 30% for optimal performance.

Resource Governance and Scaling

Understanding and managing your compute and storage resources is vital for both performance and cost control.

Choosing the Right Service Tier

Azure SQL offers various service tiers (Basic, Standard, Premium, Business Critical, General Purpose) and performance levels (DTUs, vCores) tailored to different workloads.

Analyze your application's IOPS, CPU, and memory requirements.
Start with a smaller tier and scale up as needed.
Consider serverless compute for unpredictable or intermittent workloads.

Connection Pooling

Efficiently manage database connections to reduce overhead and improve scalability.

Use connection pooling libraries in your application framework.
Configure appropriate pool sizes.

Read Scale-Out

For read-intensive workloads, leverage read-only replicas in geo-replicated configurations or Hyperscale secondary replicas.

Configure your application to direct read traffic to the read-only endpoint.

Monitoring and Diagnostics

Proactive monitoring is key to identifying potential issues before they impact users.

Azure Monitor for SQL

Leverage Azure Monitor to collect, analyze, and act on telemetry from your Azure SQL resources.

Set up alerts for key performance metrics (CPU, IO, memory, storage).
Use metrics and logs to understand resource utilization.

Dynamic Management Views (DMVs)

DMVs provide real-time insights into the internal state of your Azure SQL Database.

sys.dm_exec_requests: Active requests and their status.
sys.dm_os_wait_stats: Wait statistics to identify bottlenecks.
sys.dm_db_resource_stats: Resource usage over time.

Advanced Performance Tuning Techniques

For complex scenarios, explore these advanced strategies.

Intelligent Query Processing (IQP)

IQP features in Azure SQL Database automatically improve query performance without application changes.

Features include Cardinality Estimation feedback, Parameter Sensitive Plan optimization, and Batch Mode execution.
Ensure you are running on compatible service tiers and versions.

Database Scalling and Sharding

For very large databases or high transaction volumes, consider distributing your data.

Explore elastic pools for managing multiple databases with variable usage.
Implement horizontal sharding for massive datasets.

Columnstore Indexes

Ideal for data warehousing and analytics workloads, columnstore indexes provide significant compression and performance gains for large scan operations.

Continuously monitor, analyze, and tune your Azure SQL Database to ensure optimal performance and cost efficiency.