Updated 2026-10-04 · Cloud security

Google Cloud security
operations and reliability statistics.

A source-first view of change quality, recovery speed and whether the running system meets its objectives. 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

Change failure rate

Changes causing rollback, hotfix or incident ÷ all changes × 100

Use one stable denominator and record exclusions.
02

Median recovery time

Median time from impact detection to service restoration

Use one stable denominator and record exclusions.
03

Objective attainment

Measurement windows meeting the agreed SLO ÷ all windows × 100

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 →