Always-On PTUs for Seasonal or Cyclical Azure OpenAI Workloads

Ariel Lichterman

CER:

Azure-AI-2017

Service Category

Cloud Provider

Azure

Service Name

Azure Cognitive Services

Inefficiency Type

Unnecessary Continuous Provisioning

Explanation

Many Azure OpenAI workloads—such as reporting pipelines, marketing workflows, batch inference jobs, or time-bound customer interactions—only run during specific periods. When PTUs remain fully provisioned 24/7, organizations incur continuous fixed cost even during extended idle time. Although Azure does not offer native PTU scheduling, teams can use automation to provision and deprovision PTUs based on predictable cycles. This allows them to retain performance during peak windows while reducing cost during low-activity periods.

Relevant Billing Model

PTUs are billed for every hour they remain provisioned. If workloads operate on weekly, monthly, or seasonal cycles, keeping PTUs active outside of demand windows results in paying for idle dedicated capacity.

Detection

Identify PTU-backed workloads with recurring or predictable activity patterns
Review utilization trends showing regular periods of inactivity despite continuous PTU allocation
Evaluate whether workload timing aligns with business cycles, reporting schedules, or seasonal events
Assess whether PTUs remain active during nights, weekends, or large idle blocks

Remediation

Use automation to scale PTUs up and down according to expected workload schedules
Provision PTUs only during windows where predictable throughput and low latency are required
Establish scheduling policies for cyclical workloads to prevent unnecessary continuous provisioning
Regularly re-evaluate patterns to ensure scheduling aligns with evolving business cycles

Relevant Documentation

https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/provisioned-throughput

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