Ensure applications properly close database connections when they are no longer needed.
Adjust the maximum number of connections in the application's database connection pool to an appropriate level.
Configure background processes to use a limited amount of system resources to avoid impacting live operations.
Reschedule maintenance, backups, and batch jobs to off-peak hours.
Implement application-level caching or load balancing to distribute requests and reduce direct database pressure.
Identify and refactor inefficient queries or code patterns that cause excessive database load.
Increase the CPU, RAM, or storage capacity of the database server or consider a more powerful instance type.
Optimize slow queries, add appropriate indexes, and tune database configuration parameters for better resource utilization.
Explore different index types (e.g., B-tree, hash, full-text) based on the nature of the queries and data.
Create indexes that include all columns needed by a query to avoid table lookups.
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Poorly optimized SQL queries, missing indexes, or excessive data retrieval can lead to long execution times and high resource consumption.
High CPU, memory, or disk I/O on the database server can bottleneck all operations, including data retrieval.
Slow network connections between the application server and the database server can significantly increase data retrieval times.
Long-running transactions or deadlocks can cause other queries to wait, leading to perceived slowdowns.
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