Azure Cost Estimator

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Supports Terraform, Bicep, ARM, and zip archives

Settings

Azure Regions 1 selected

Select 2+ regions to compare pricing

Currency

Include usage guesstimates

Add estimated costs for data transfer, storage, and transactions

Include carbon footprint (experimental, rough estimates)

Estimate CO₂e emissions using CCF/SCI methodology

How it works

Upload a template, select one or more regions, and get instant retail pricing via the Azure Retail Prices API. Select multiple regions to compare costs side by side. Learn more →

Monthly Cost

$0.00

Daily Cost

$0.00

Resources Priced

Unmatched

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Cost Breakdown

Resource	SKU / Tier	Daily	Monthly	kg CO₂e/mo	Share
Total

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Monthly costs based on 730 hours/month (Azure standard). Prices are retail/pay-as-you-go. Actual costs may vary.

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Region Comparison

Monthly costs based on 730 hours/month (Azure standard). Prices are retail/pay-as-you-go. Actual costs may vary.

Usage Guesstimates

What are usage guesstimates?

Many Azure services have both a fixed base cost (the SKU/tier you provision) and variable usage costs that depend on actual consumption — things like data transfer, storage consumed, API calls, and message throughput.

Since we can only see your infrastructure template (not real usage data), we apply sensible default assumptions for each resource type to give you a more realistic “total cost of ownership” estimate.

Important: These are rough estimates meant for planning, not billing predictions. Your actual usage may be significantly higher or lower. Use them as a starting point, then refine with your own usage patterns.

How it works

Your template is parsed to extract resource types and configurations
For each resource, we determine the base cost (SKU/tier pricing)
When usage guesstimates are enabled, we add additional line items for consumption-based costs
Each usage item is queried against the Azure Retail Prices API for accurate unit prices

Default assumptions by resource

Resource	Usage assumption
Storage Account	100 GB stored, 100K write + 500K read ops, 50 GB egress/mo
Cosmos DB	800 RU/s provisioned throughput
PostgreSQL / MySQL	Storage based on template config (or 128 GB default)
SQL Database	Storage based on max_size_gb (vCore SKUs only)
Log Analytics	~100 GB/mo ingestion + 100 GB retention
Key Vault	~1M operations/mo
Service Bus	~10M messages/mo
Event Hubs	~100M ingress events/mo
Azure Firewall	~500 GB data processed/mo
App Gateway	~200 GB data processed/mo + 50 capacity units
NAT Gateway	~500 GB data processed + 50 GB egress/mo
Load Balancer	~500 GB data processed/mo (Standard)
VPN Gateway	~2 S2S tunnels + 500 GB transfer/mo
ExpressRoute	~1 TB egress/mo
Front Door / CDN	~500 GB transfer/mo
Container App	~50 GB egress/mo
VM / App Service	~100 GB egress/mo
Private Endpoint	~100 GB data processed/mo
Backup Vault	~200 GB RA-GRS storage
Data Factory	~500 hrs data movement/mo
Cognitive Services	~500K records or ~5M tokens (OpenAI)/mo
Container Instance	Memory allocation from template

In the results

Usage items appear as separate line items in the cost breakdown, grouped under their parent resource. They are clearly labelled with descriptions like “~100 GB/month est.” so you can identify which costs are guesstimates versus fixed provisioned costs.

All unit prices are queried live from the Azure Retail Prices API. Usage quantities are estimates based on typical workload patterns and may not reflect your actual usage.

Carbon Footprint Estimation

What is this?

This feature estimates the monthly carbon footprint (in kg CO₂e) of your Azure infrastructure by modelling the energy consumption of each resource and multiplying by the electricity grid’s carbon intensity for your chosen region.

Experimental: Carbon estimates are approximate and intended for awareness and comparison — not for regulatory compliance or official carbon reporting.

Methodology

We follow the Cloud Carbon Footprint (CCF) methodology and the Software Carbon Intensity (SCI) standard from the Green Software Foundation.

CO₂e = (Energy_kWh × PUE × Grid_Factor) / 1000 + Embodied

Energy components

For each resource, we estimate four energy components:

Compute

vCPU power draw based on SPECpower benchmarks: 0.78 W (idle) to 3.76 W (peak) per vCPU at 50% avg utilisation

Memory

0.000392 kWh per GB of RAM provisioned

Storage

SSD: 1.2 Wh/TB, HDD: 0.65 Wh/TB — varies by resource type

Networking

0.001 kWh per GB of estimated data transfer

Key parameters

PUE

1.185

Azure datacenter avg (Microsoft-reported)

Hours / month

730

Azure standard billing period

Server lifespan

4 years

For embodied emission amortisation

Embodied

1,200 kg / server

Manufacturing CO₂e (Dell LCA data)

Regional grid carbon intensity

The grid factor (gCO₂e/kWh) varies dramatically by region based on the local electricity mix. Choosing a region with cleaner energy can significantly reduce your carbon footprint.

Region	gCO₂e/kWh	Why
Switzerland	25	Hydro-powered
Norway	29	Hydro-powered
Sweden	45	Nuclear + hydro
France	56	Nuclear-heavy
UK	231	Mixed (wind + gas)
West US	267	Renewables + gas
West Europe	315	Mixed grid
East US	379	Gas + coal
Poland	635	Coal-heavy

In the results

A green CO₂e/month summary card appears and each resource row shows its individual carbon contribution. Click any resource’s carbon value to see the full energy breakdown and calculation. When comparing regions, use this data to choose lower-carbon deployment locations.

Sources: EPA eGRID, European Environment Agency, Ember Global Electricity Review, Microsoft PUE disclosures, SPECpower benchmarks, Dell server LCA data. Based on CCF and SCI methodology.

Template File

Settings

Cost Breakdown

Region Comparison

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Carbon Calculation Methodology

Resource

Usage Guesstimates

What are usage guesstimates?

How it works

Default assumptions by resource

In the results

Carbon Footprint Estimation

What is this?

Methodology

Energy components

Key parameters

Regional grid carbon intensity

In the results