Cost Optimization

VM Sizing Recommendations

Find out which VMs are bigger than they need to be and how much you could save by right-sizing them. StratoLens uses actual CPU, memory, and disk utilization data to recommend specific smaller SKUs, with the utilization evidence attached.

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StratoLens is a self-hosted Azure visibility platform. It runs in your own tenant; your infrastructure data never leaves it.

The Problem

Most VMs are oversized because teams spec high to be safe, and nobody goes back to check:

Over-Provisioning by Default: Teams pick larger SKUs to avoid performance risk, then never revisit
No Utilization Visibility: Without actual usage data, you can't tell which VMs are oversized
Guesswork is Risky: Right-sizing without data means guessing, and getting it wrong causes outages

The Solution

Right-size using actual performance data:

Usage-Based Recommendations: Identifies oversized VMs based on real CPU, memory, and disk utilization
Specific SKU Suggestions: Not just "this VM is too big" but "switch to this SKU and save this much"
Cost Impact Per VM: See the estimated savings for each recommendation so you prioritize the biggest wins

From the product

Inside VM Sizing Recommendations

StratoLens Azure VM sizing recommendations sorted by estimated savings, led by a heavily oversized VM with a specific smaller SKU suggested — The right-sizing list for the Contoso Financial demo environment sorted by savings, topped by a very large risk-grid VM whose utilization never comes close to justifying its SKU. Shown with demo-environment data.

The utilization evidence behind the top recommendation, with 30 days of CPU data showing the VM barely working.

A recommendation detail pairing the current SKU with the suggested one and the estimated monthly savings of making the switch.

Benefits

Key benefits

Performance-based VM sizing recommendations

Identify oversized VMs wasting budget

Specific SKU recommendations with cost impact

Data-driven decisions to reduce risk

Use cases

Common use cases

Reduce VM costs through right-sizing

Identify underutilized VMs for consolidation

Optimize dev/test environment sizing

Self-hosted

Runs in your tenant. Reads everything, changes nothing.

StratoLens deploys from the Azure Marketplace into your own tenant and scans your subscriptions over read-only Azure APIs. The data behind VM Sizing Recommendations is collected and stored inside your tenant; there is no StratoLens cloud holding a copy.

Read-only scans via Azure management APIs
Every scan at rest in your tenant, never a vendor cloud
Deployed from the Azure Marketplace in under 15 minutes

Learn more about data residency and security architecture

Want the details?

Explore our documentation to see how VM Sizing Recommendations works in detail.

Read Documentation View All Features

From the Blog

Right-Sizing Azure VMs: Why the CPU Average Lies to You

The 4% CPU average does not settle the downsizing argument. Pull percentiles and memory data from Azure Monitor, then let StratoLens map them to SKUs.

Read the article

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