LCK_M_I[xx] waits in Azure SQL Database indicate that a session is waiting on a lock of some type (indicated by [xx]) to be released before it can proceed. These waits are often symptoms of concurrency issues where multiple transactions are trying to access the same resource simultaneously, leading to blocking. Addressing these waits efficiently requires a comprehensive approach focusing on query optimization, database design, and application logic. Here are several tips and tricks to help reduce LCK_M_I[xx] waits in your Azure SQL environment:

1. Optimize Indexes

• Avoid unnecessary locks: Use appropriate indexing strategies to minimize the data that transactions lock. For example, a well-designed index can turn a table scan, which locks the entire table, into a more efficient index seek, locking only the required rows.

• Use index hints sparingly: While index hints can reduce waits by forcing the query optimizer to use a particular index, they can also lead to suboptimal query plans if used excessively. Use them judiciously.

2. Optimize Queries

• Minimize transaction duration: Keep transactions as short as possible to reduce lock time. This might involve breaking large operations into smaller transactions.

• Select appropriate isolation levels: Higher isolation levels like Serializable increase locking and blocking. Consider using lower isolation levels like Read Committed Snapshot Isolation (RCSI) if consistency requirements allow, as it uses row versioning rather than locks for read operations.

3. Application Design Adjustments

• Implement retry logic: In applications, implement logic to retry transactions that fail due to locking errors. This can help smooth out temporary spikes in lock contention.

• Use batching: Where possible, batch operations to reduce the number of locks required at any given time.

4. Monitoring and Analyzing Lock Waits

• Monitor lock waits: Regularly monitor your system for lock waits using tools like Azure SQL Analytics or dynamic management views (DMVs) such as sys.dm_tran_locks and sys.dm_os_wait_stats.

• Analyze blocking chains: Identify the leading blockers and the queries involved. Understanding the root cause of blocking can help in formulating a targeted solution.

5. Database Settings Adjustments

• Enable Read Committed Snapshot Isolation (RCSI): Enabling RCSI can help reduce locking contention by allowing readers to not block writers and vice versa. However, be aware of the potential increase in tempdb usage.

6. Partitioning

• Use partitioning to reduce lock contention: By partitioning large tables, you can limit the scope of locks to a specific partition rather than the entire table, reducing the potential for lock contention.

7. Review and Optimize Transaction Logic

• Avoid lock escalation: SQL Server escalates row or page locks to table locks under certain conditions. Keep the number of locks low by designing transactions that update fewer rows at a time.

Reducing LCK_M_I[xx] waits often involves a combination of these strategies, tailored to the specific patterns of database access your applications use. Regular monitoring, understanding the specific causes of waits in your environment, and applying targeted optimizations are key to minimizing these waits in Azure SQL Database.