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Redis Disk I/O Bottlenecks

High disk I/O when persistence (AOF or RDB) is enabled, which can impact overall performance if the disk is slow or heavily used.
  1. Identify Slow Queries: Use the SLOWLOG GET command to list the slow operations. This can help you understand if specific commands are causing disk I/O bottlenecks.
  2. Monitor Disk Latency: Check disk latency metrics. Use the iostat command (on Unix-like systems) to monitor disk I/O wait and service times. High wait times can indicate disk I/O bottlenecks.
  3. Check Redis Persistence Options: If you're using RDB snapshots or AOF persistence, consider adjusting your persistence configuration. For RDB, reduce the frequency of saves if they're too frequent by adjusting the save directives in the configuration file. For AOF, if appendfsync is set to always, consider changing it to everysec to reduce disk I/O.
  4. Evaluate Memory Usage: Run INFO memory to check memory usage. High memory usage can lead to swapping, which severely impacts disk I/O. If swapping is occurring, consider adding more memory or reducing memory usage by adjusting data eviction policies with the maxmemory-policy setting.
  5. Examine Key Sizes and Types: Use MEMORY USAGE <key> to check the memory footprint of your largest keys. Large keys, especially lists, sets, or hashes, can lead to inefficient operations that impact disk I/O during persistence.
  6. Adjust Client Buffer Limits: High client buffer limits can lead to large amounts of data being transferred to and from Redis, impacting disk I/O during persistence. Adjust client-output-buffer-limit settings if necessary.
  7. Disable Transparent Huge Pages (THP): On Linux, ensure THP is disabled as it can cause latency and memory usage issues with Redis. Use echo never > /sys/kernel/mm/transparent_hugepage/enabled to disable it.
  8. Consider Using no-appendfsync-on-rewrite Option: If AOF and RDB persistence are both enabled, enabling no-appendfsync-on-rewrite can reduce disk I/O by avoiding simultaneous AOF rewrite and RDB snapshot operations.
  9. Monitor and Optimize AOF Rewrite Process: If using AOF, the bgrewriteaof command can be manually triggered during low traffic periods. This rewrites the AOF file to optimize it and can reduce disk I/O if the file size is significantly reduced.
  10. Analyze and Optimize Data Access Patterns: Use MONITOR (cautiously, as it can reduce performance) to observe real-time command execution. Look for patterns that cause excessive or unnecessary disk I/O and optimize your application's data access patterns accordingly.
  11. Use INFO stats to Check Command Stats: This can give you insight into the commands being processed and help identify any commands contributing to the disk I/O bottleneck.

Each of these actions should be taken based on the specific context and configuration of your Redis setup, and the impact of changes should be carefully monitored.

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