CF-AZ-CM-10Commitments

How to detect reservation coverage gaps.

Reservation Coverage Gaps can quietly add recurring Azure cost when resource state, utilization, or lifecycle policy no longer matches real usage. This guide explains why it costs money, how to find it manually, and how Costframe detects it read-only.

CF-AZ-CM-10 • DETECTOR TYPE

Reservation Coverage Gaps

Impact: Very High
Resource: uncovered-compute-ea
+€1180.00/mo
Utilization Telemetry
0 IOPS / Low utilization detected
Audit Rationale

Orphaned reservation coverage gaps found in billing records with zero active workload associations over a rolling 30-day window.

Operational Description

Azure Reservations allow organizations to commit to 1- or 3-year resource plans in exchange for up to 72% cost savings. Compute resources that run continuously at on-demand list rates represent a significant commitment optimization gap.

Primary Root Cause

Failing to continuously track active continuous compute baseline footprints against existing reservation blocks as virtual machines are added or deleted.

How Costframe Detects & Verifies This

We analyze historical baseline compute curves. If a consistent baseline of a specific VM size series (e.g., Dv5 series) is identified as running entirely uncovered, we compile the optimal purchase recommendation.

Evidence:Consistent uncovered Dv5 baseline: 8 cores • Optimal recommendation: 1-Year Reserved Instance.

Continuous cloud audits, automated

Run this detector and dozens of other cloud-waste rules across all your Azure subscriptions continuously.