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enhancementNew feature or requestNew feature or requestpythonPull requests that update python codePull requests that update python code
Description
For our generated Confluence pages it is recommended that we add an approval/status column
| Title | Description | Looker Attachment | Approval |
|---|---|---|---|
| Fenix Monthly Flaky Rate | The percentage of flaky tests by month. | <URL> |
🛡️ |
The purpose of showing metric approval is to make the maturity and reliability of each data point visible at a glance — both for internal credibility and for leadership review.
Specifically:
- It signals that a metric has passed the full 5-Point Actionability (Metric Lifecycle) review, meaning it has a clear purpose, trigger, workflow integration, business value, and ownership.
- It differentiates between production-ready and informational data, preventing half-built or context-less metrics from being mistaken as authoritative.
- It establishes transparency and accountability, showing which metrics are actively monitored and which are still under evaluation.
- Finally, it provides a lightweight governance layer that helps leadership confidently present the team’s data as validated, trustworthy, and tied to business impact — rather than “in construction.”
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enhancementNew feature or requestNew feature or requestpythonPull requests that update python codePull requests that update python code