Underutilized Azure Reserved Instance Due to Workload Drift

Balazs Engedi

Service Category

Compute

Cloud Provider

Azure

Service Name

Azure Reservations

Inefficiency Type

Commitment Misalignment

Explanation

As workloads evolve, Azure Reserved Instances (RIs) may no longer align with actual usage — due to refactoring, region changes, autoscaling, or instance-type drift. When this happens, the committed usage goes unused, while new workloads run on non-covered SKUs, resulting in both underutilized reservations and full-price on-demand charges elsewhere.

The root inefficiency is architectural or operational drift away from what was originally committed — often due to team autonomy, poor RI governance, or legacy commitments. This leads to silent waste unless workloads are re-aligned to match existing reservations.

Relevant Billing Model

Azure Reservations are prepaid or monthly-commit financial instruments
The discount applies only when running matching resources (e.g., same VM size and region)
Underutilized reservations result in sunk cost with no usage offset
Azure offers limited flexibility via instance size flexibility, re-scoping, or exchange options

Detection

Identify Azure Reservations with consistently low utilization rates
Determine which SKUs, regions, or resource types are covered but underused
Compare current usage patterns to reservation scope (e.g., VM series, region, size)
Assess whether workloads moved off the committed types due to organic evolution, performance needs, or misaligned provisioning

Remediation

Evaluate whether any existing workloads could be migrated to match the reservation scope
For new workloads, consider provisioning on RI-covered instance types when technically viable
Where appropriate, exchange the reservation for a more relevant SKU
Re-scope the reservation to another subscription or region if cross-team usage can improve coverage
Use RI utilization data to inform future purchasing decisions and reduce overcommit risk

Relevant Documentation

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