reported profiling in the observability stack
The CNCF annual survey highlighted profiling as an emerging observability practice.
CNCF Annual Cloud Native Survey · 2026 ↗Updated 2026-10-04 · Reliability
Site reliability engineering
adoption and scale statistics.
A source-first view of how widely the capability is used and how quickly its footprint is growing. 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.
technology professionals in the 2025 DORA survey
DORA combined this survey with more than 100 hours of qualitative research.
DORA 2025 report announcement · 2025 ↗pull requests merged per month
GitHub reported monthly merged pull requests increased 23% year over year.
GitHub Octoverse 2025 · 2025 ↗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.
Managed coverage
Actively managed assets ÷ discovered assets × 100
Standard-path adoption
Workloads using the approved path ÷ eligible workloads × 100
Quarterly footprint change
(Current assets − prior-quarter assets) ÷ prior-quarter assets × 100
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.
Related benchmarks
Look at the adjacent signal.
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