Unlock granular resource control with queue-based QMR in Amazon Redshift Serverless

This article explains how to implement queue-based Query Monitoring Rules (QMR) in Amazon Redshift Serverless for granular resource control across different analytical workloads.

• Queue-based QMR enables dedicated queues with workload-specific monitoring rules and automated actions
• Improves upon workgroup-level monitoring by providing granular control and role-based query assignment
• Supports three example queues: Dashboard (60-second timeout), ETL (100K disk blocks limit), Admin (no limits)
• Queries routed to queues based on user roles and query groups with wildcard matching support
• Automated actions include aborting or logging queries exceeding execution time or resource thresholds
• Implementation available via AWS Console or CLI with WLM JSON configuration
• Best practices include starting simple, aligning with business priorities, and testing before production

Queue-based QMR in Redshift Serverless enables fine-grained workload isolation and cost control while maintaining serverless simplicity and automatic scaling benefits.