#workload-priority

CPU Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for general-purpose processor scheduling. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.

Cache Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for fast temporary data layer. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.

Cluster Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for group of machines acting as one platform. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.

Container Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for packaged application runtime. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.

Edge Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for globally distributed runtime. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.

GPU Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for accelerated compute for parallel workloads. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.

Memory Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for volatile runtime storage. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.

Queue Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for asynchronous work buffer. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.

Scheduler Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for placement of work onto resources. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.

Serverless Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for event-driven function execution. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.

Storage Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for persistent data and object access. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.

Virtual Machine Workload Priority is a compute scheduling signal that tells the platform which work matters most when capacity is constrained for isolated guest compute. It uses priority classes, preemption rules, and fairness limits so teams can protect critical paths while keeping evidence, reliability, and public-safe operational boundaries clear.