Feature Store Freshness Half-Life Calculator
Convert feature store freshness monitoring data into a quantitative half-life. Input the observation window and compliance share to reveal decay dynamics, recommended refresh intervals, and how automated remediation slows drift.
Analytical aid for data platform teams; pair with production monitoring and alerting before adjusting SLAs.
Examples
- 14-day window with 72% compliance, threshold 85%, remediation reduction 20% ⇒ Half-life 19.34 days, freshness hits 85% after 5.06 days, daily decay 3.46%.
- 7-day window with 60% compliance, threshold 75%, no remediation ⇒ Half-life 8.11 days, threshold breach at 3.11 days, daily decay 8.55%.
FAQ
What telemetry should feed the compliance share?
Use the percentage of production features or training datasets that satisfied freshness SLAs at the end of the monitoring window. Align the sample with the population used in your data contract dashboards.
How can I calibrate the remediation reduction input?
Review historical incidents where automated backfills or streaming catch-up jobs restored stale features. Estimate the percentage reduction in decay observed in subsequent windows and apply that as the remediation factor.
What if compliance improves mid-window?
If interventions occur during the window, segment the period into sub-windows with stable decay behaviour or recompute using post-intervention telemetry so the exponential assumption remains valid.
Additional Information
- Result unit: days for half-life and threshold timing; daily decay reported as a percentage.
- Decay assumes exponential freshness loss beginning from full compliance at the start of the window.
- Automated remediation reduction applies linearly to the decay constant and represents sustained effectiveness across the window.