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Calcrivo

Azure Advisor Savings Calculator

Turn Azure Advisor cost recommendations into a realised monthly saving after an honest adoption rate.

Inputs

USD
USD/month
%

Shutting down beats resizing, but resizing is usually what gets approved.

USD/month
USD/month
%
USD/month
%

Realised Monthly Saving

$10,178.00

Saving Identified

$14,540.00

Realised Annual Saving

$122,136.00

Optimised Monthly Spend

$29,822.00

Reduction in Total Spend

25.4%

Largest Single Lever

Reservations and savings plans on steady-state compute

Step by step

  1. Values used

    Total monthly Azure spend = 40,000 USD; Spend on idle or underused VMs = 6,000 USD/month; Saving available on those VMs = 70 %; Spend on unattached disks, idle IPs and old snapshots = 1,300 USD/month; Steady-state spend eligible for reservations = 18,000 USD/month; Reservation discount available = 38 %; Windows licence spend eligible for Hybrid Benefit = 2,200 USD/month; Share of recommendations you will actually implement = 70 %

  2. Azure Advisor Savings

    identified = idle VM spend × saving rate + orphaned resource spend + reservation-eligible spend × discount + Hybrid Benefit-eligible licence spend; realised = identified × adoption rate.

  3. Realised Monthly Saving

    = 10,178.00

  4. Saving Identified

    = 14,540.00

  5. Realised Annual Saving

    = 122,136.00

  6. Optimised Monthly Spend

    = 29,822.00

  7. Reduction in Total Spend

    = 25.4

  8. Largest Single Lever

    = Reservations and savings plans on steady-state compute

How it works

Advisor reports a theoretical maximum that assumes every recommendation is applied, which never happens, so the useful number is the identified saving multiplied by a realistic adoption rate. The levers also differ in risk: deleting an unattached disk is free, resizing a VM needs a maintenance window, and a reservation trades flexibility for a discount over one or three years. Presenting an unfiltered Advisor figure to a finance team creates a target nobody can hit, while an adoption-weighted number is a commitment you can defend; the orphaned-resource line is worth attacking first because it needs no approval and carries no performance risk.

Formula

Azure Advisor Savings

identified = idle VM spend × saving rate + orphaned resource spend + reservation-eligible spend × discount + Hybrid Benefit-eligible licence spend; realised = identified × adoption rate.

adoption rate
Share of recommendations that survive change control and actually ship
orphaned
Resources billing with nothing attached — the only risk-free saving on the list
reservation discount
Percentage a 1-year or 3-year commitment takes off the pay-as-you-go rate

Frequently Asked Questions

How is Azure Advisor Savings calculated?

identified = idle VM spend × saving rate + orphaned resource spend + reservation-eligible spend × discount + Hybrid Benefit-eligible licence spend; realised = identified × adoption rate. Advisor reports a theoretical maximum that assumes every recommendation is applied, which never happens, so the useful number is the identified saving multiplied by a realistic adoption rate. The levers also differ in risk: deleting an unattached disk is free, resizing a VM needs a maintenance window, and a reservation trades flexibility for a discount over one or three years.

Why does Azure Advisor Savings matter?

Presenting an unfiltered Advisor figure to a finance team creates a target nobody can hit, while an adoption-weighted number is a commitment you can defend; the orphaned-resource line is worth attacking first because it needs no approval and carries no performance risk.

What values do I need to enter?

This calculator takes 8 inputs: Total monthly Azure spend, Spend on idle or underused VMs, Saving available on those VMs, Spend on unattached disks, idle IPs and old snapshots, Steady-state spend eligible for reservations, Reservation discount available, Windows licence spend eligible for Hybrid Benefit, Share of recommendations you will actually implement. The pre-filled defaults are a realistic starting point — replace them with figures from your own environment for a result you can act on.

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