Underutilized or Overprovisioned WorkSpaces Applications Instances

This leads to consistently low utilization of CPU, memory, or GPU resources and inflated infrastructure costs. By right-sizing WorkSpaces Applications instances based on actual workload needs, organizations can reduce spend without compromising user experience.

WorkSpaces Applications streaming instances are billed based on the selected instance type, size, and operating system, with higher-cost options providing more CPU, memory, and GPU resources. Windows instances are charged hourly, Rocky Linux and Red Hat Enterprise Linux instances are charged per second with a 15-minute minimum, and Elastic fleet instances are billed per second. Always-On fleet instances are charged the running rate even when no users are connected, idle On-Demand fleet instances are charged a small stopped-instance fee, and Windows-based fleets also incur a monthly per-user fee. If instance types are overprovisioned relative to actual usage, customers pay for unused capacity, driving unnecessary spend.

• Identify WorkSpaces Applications fleets or stacks with consistently low CPU, memory, or GPU utilization over a representative period
• Review instance type specifications in relation to average and peak workload demands
• Conduct performance benchmarking or usage sampling for specific applications or user groups
• Check whether current instance types were selected based on assumption or inherited defaults rather than workload data

• Right-size WorkSpaces Applications fleets by selecting smaller or less specialized instance types that meet current workload demands
• Conduct performance testing after downgrading to ensure that application responsiveness and user experience are preserved
• Update provisioning templates or fleet configurations to reflect optimized instance types going forward

• WorkSpaces Applications Instance Familiesdocs.aws.amazon.com
• Amazon WorkSpaces applications pricingaws.amazon.com