Updated 2026-10-04 · Cloud security

Azure security
cost and efficiency statistics.

A source-first view of unit economics, waste and the engineering effort needed to operate the capability. Published findings provide context; the measurement framework shows what to calculate inside your own environment.

01 / Published evidence

What the public data says.

Each figure links directly to the organization that published it. Vendor telemetry and community surveys are labelled rather than blended into one invented industry average.

02 / Your baseline

Measure the system you actually run.

Use these formulas consistently for at least one complete operating cycle. Keep scope, exclusions and collection dates beside the result.

01

Unit operating cost

Monthly attributable cost ÷ active workloads or services

Use one stable denominator and record exclusions.
02

Avoidable spend ratio

Verified waste ÷ total attributable spend × 100

Use one stable denominator and record exclusions.
03

Engineering effort

Monthly engineer hours spent on routine operation and remediation

Use one stable denominator and record exclusions.

03 / Interpretation

A number without a denominator is decoration.

Segment results by environment, workload owner and business criticality. A falling average can hide one critical service getting worse; a rising count can simply reflect better discovery.

  • Record the source system and collection window.
  • Separate discovered, in-scope and actively managed populations.
  • Keep medians and tail values where averages hide risk.
  • Annotate architecture, policy and tooling changes.
  • Recalculate after remediation instead of closing on intent.

Want these numbers from your cloud?

Gritt can map the data sources, calculate a defensible baseline and implement the changes behind it.

Build the baseline →