of contributions occurred in private repositories
GitHub’s dataset shows most day-to-day organizational development happens privately.
GitHub Octoverse 2025 · 2025 ↗Updated 2026-10-04 · Compliance
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
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.
GitHub’s dataset shows most day-to-day organizational development happens privately.
GitHub Octoverse 2025 · 2025 ↗The report says AI cost management increasingly spans cloud, SaaS and data centers.
State of FinOps 2025 · 2025 ↗CNCF described cloud-native adoption as near-universal among surveyed organizations.
CNCF Annual Cloud Native Survey · 2026 ↗02 / Your baseline
Use these formulas consistently for at least one complete operating cycle. Keep scope, exclusions and collection dates beside the result.
Monthly attributable cost ÷ active workloads or services
Verified waste ÷ total attributable spend × 100
Monthly engineer hours spent on routine operation and remediation
03 / Interpretation
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.
Related benchmarks
Gritt can map the data sources, calculate a defensible baseline and implement the changes behind it.
Build the baseline →