For a blazingly fast application, optimizing Redis is key, but it's not the only factor. Redis performance can be hindered by a range of issues, including an imbalance of write over read operations, insufficient memory leading to OOM errors, low CPU allocation, various sources of latency (network, slow commands, persistence I/O, THP), character set mismatches with other databases, "hot" or "big" keys causing contention, hitting the maxclients limit, network bandwidth saturation, and improper client-side configurations or replication lag in clustered setups.
database scalability
This blog post tackles the issue of slow queries in MySQL databases. It provides a step-by-step approach to identify these sluggish queries through slow query logging and analysis. By using the EXPLAIN statement, you can understand how MySQL retrieves data and pinpoint bottlenecks. The blog then offers solutions like creating indexes and optimizing query structure to improve performance. Finally, it emphasizes the importance of continuous monitoring to maintain a healthy and speedy MySQL database.
This blog post explores how to use Percona's pt-query-digest tool to diagnose slow queries in MySQL. After enabling the slow query log, you can use pt-query-digest to analyze the log file, identifying the slowest queries by execution time and grouping them by structure. By reviewing the detailed output and potentially optimizing the queries or using database indexing, you can tame slow queries and improve your MySQL database's performance.