MaxScale Multiplexing and Caching – Part 7

Part 7 – Warnings & Caveats

This multi-part series breaks down each section into easy logical steps.

Part 1 – Complete Guide for High-Concurrency Workloads

Part 2 – Understanding MaxScale Thread Architecture

Part 3 – Backend Sizing and Connection Pooling

Part 4 – Tuning MaxScale for Real Workloads

Part 5 – MaxScale Multiplexing

Part 6 – MaxScale Caching

Part 7 – Warnings & Caveats

Part 8 – Key Takeaways

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While MaxScale’s multiplexing and caching features can significantly improve throughput and reduce backend load, it’s important to understand the potential pitfalls and tune carefully. Here are key considerations and practical examples:

Multiplexing and Session-Specific Queries
Multiplexing works best for stateless queries. Queries that rely on session-specific variables or temporary tables may produce incorrect results if multiplexed.
Example: Applications that set SET @user_id = 123 before queries should not use multiplexing for those sessions.

Idle Pool Size

• Too Small: If persistpoolmax or idle_session_pool_time are too low, threads may frequently wait for backend connections, causing increased latency.
  Example: 50 client sessions mapped to only 5 backend connections with a small idle pool may result in queueing delays.
• Too Large: Oversized pools consume more memory without meaningful performance benefit.
  Example: A 16-core MaxScale with idle pools sized for 100 connections per thread may unnecessarily use gigabytes of memory.

Cache TTL

• Setting cache_ttl too high can serve stale data to your application.
  Example: A caching TTL of 10 minutes on frequently updated product inventory could cause customers to see outdated stock levels.

Configuration Backups

• Always back up MaxScale configuration files before making changes. Rolling back misconfigurations is faster and prevents downtime.
  Tip: Use cp /etc/maxscale.cnf /etc/maxscale.cnf.bak or version control for configuration management.

Monitoring During Peak Load

• Regularly monitor thread usage, connection pools, cache hit/miss rates, and query latency, especially during high-concurrency periods.
  Example: During monthly batch processing or flash sale events, validate that multiplexing and caching maintain low latency without saturating backend servers.

MaxScale Error Logging

• Review MaxScale error logs for warnings about sessions that cannot be multiplexed. If you see frequent warnings, it indicates your application is using session state, and multiplexing should be disabled for that service/listener.

Summary: Proper planning, monitoring, and incremental tuning are essential. Multiplexing and caching provide excellent performance benefits, but only when applied thoughtfully with awareness of session behaviour, pool sizing, and cache freshness.

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