Metrics
Metrics in Advanced Analytics are pre‑aggregated measures derived from raw events and CMDB data. They are designed to power CRM Analytics dashboards, KPI tiles, and external BI tools without requiring per‑dashboard SQL.
Most metrics are computed daily and stored at multiple grains (per user, per team, per account, per module) to balance flexibility and performance.
Metric Categories
Common metric categories include:
- Adoption metrics
- Module adoption (for example, percent of assets actively using Breeze Agent, Vulnerability Management & Scanning, or Unified Monitoring).
- Operational metrics
- MTTR (mean time to resolve) - the equivalent of time to detect (TTD) and time to recover (TTR) for incidents and compliance violations.
- Coverage metrics (for example, percent of assets with monitoring, backup, or vulnerability scanning enabled).
- Job success and failure counts for critical pipelines, such as policy evaluations.
- Cost metrics when Cost Management is enabled
- Cost per asset, workload, or application.
- Cost efficiency metrics.
- Budget vs. actual spend and deltas/forecasts.
Exact metric availability depends on which modules and integrations are enabled in your environment.
Aggregation Windows
To support trend analysis and cohorts, most metrics are available with the following standard windows:
- 1‑day – point‑in‑time value for a given date.
- 7‑day rolling – last 7 full days, including the current date.
- 28‑day rolling – last 28 full days (often used for MAU and retention).
- 90‑day rolling – longer‑term adoption and stability trends.
Where applicable, cumulative lifetime metrics (for example, total policies created) are also maintained.
Dimensions & Grain
Metrics are keyed by a subset of the dimensions described in Attributes / Dimensions. Typical grains include:
- Per tenant / organization.
- Per cloud account / subscription / project.
- Per application / service / environment.
- Per module (Compliance Engine, Cost Management, Unified Monitoring, etc.).
- Per user or team.
When designing new metrics, choose the lowest grain that is practically useful, then roll up in CRM Analytics for dashboard‑level views.
Naming Conventions
Metric fields follow clear, self‑describing names, for example:
active_users_7dfeature_adoption_rate_28dtime_to_recover_p50_minutesmonitoring_coverage_pct
The same logical metric name is reused across CRM Analytics datasets and external exports.
Relationship to KPIs
The KPI catalog in Dashboards & Reporting – KPIs is defined in terms of these base metrics. Use that document as the source of truth for business definitions, and this document for implementation details such as windows and dimensions.