Generate an overall platform reliability score from uptime, incidents and SLO adherence.
This composite score blends four reliability signals into a single weighted number: availability (40% weight, since uptime is the most visible reliability signal), MTTR (25%, rewarding fast recovery), incident rate (20%, penalizing frequent instability), and error budget consumption (15%, reflecting SLO health). Each sub-score is normalized to 0-100 before weighting, and the final score maps to a letter grade (A: 95+, B: 85+, C: 70+, D: 50+, F: below 50).
MTTR sub-score
mttr_score = max(0, 100 - (mttr_hours / 24) × 100)
Overall reliability score
score = availability × 0.4 + mttr_score × 0.25 + incident_rate_score × 0.2 + budget_score × 0.15
Availability is the most direct, universally understood measure of whether users can access the service, so it carries the largest weight (40%) while the other signals capture how well incidents are handled and how much reliability margin remains.
MTTR score linearly decays from 100 (instant recovery) to 0 at a 24-hour resolution time; incident-rate score linearly decays from 100 (zero incidents) to 0 at 20 incidents/month — both are heuristic reference points and can be recalibrated to your organization's norms.
No — this is a simplified composite scorecard useful for at-a-glance comparisons across teams or time periods. Formal SLO compliance should still be tracked per-service against its specific SLI/SLO definitions.
Treat it as a signal to prioritize reliability work: identify which sub-score is dragging the total down (e.g. high incident rate vs. slow MTTR) and target that specific area — a low incident-rate score points to stability work, while a low MTTR score points to on-call/runbook improvements.