Know how fast you can recover, really. Enter targets and controls for a realistic score. Prioritize fixes, rehearse drills, and reduce outage losses today.
Sample scenarios to sanity-check inputs and outputs.
| Scenario | RTO (h) | RPO (min) | Backup % | Frequency | Tests/yr | Replication | Monitoring % | Automation | Docs % | On-call | Immutable | Multi-region | Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Resilient | 1 | 5 | 98 | Hourly | 12 | Sync | 95 | Fully automated | 90 | 24x7 | Yes | Yes | 98.6 |
| Prepared | 6 | 30 | 90 | Daily | 4 | Async | 85 | Semi-automated | 75 | 24x7 | Yes | No | 69.1 |
| At Risk | 30 | 480 | 60 | Weekly | 0 | None | 55 | Manual | 40 | Ad hoc | No | No | 28.8 |
The calculator converts each input into a component score from 0 to 100. It then computes a weighted average:
Recovery Readiness Score = Σ(weightᵢ × componentScoreᵢ) ÷ 100
Tip: Use measured data where possible, not aspirational targets.
Downtime impact scales nonlinearly: a ten minute outage can be tolerable, while an hour during peak traffic may trigger revenue loss, SLA penalties, and reputation damage. A readiness score turns scattered inputs into a comparable baseline. By blending recovery time objective, recovery point objective, and operational maturity, teams can track improvements release to release and justify investment with measurable deltas.
For customer facing platforms, common RTO targets range from 15 to 240 minutes, while internal tools often accept 4 to 24 hours. RPO targets usually sit between 0 and 60 minutes for transactional data and 24 hours for archival workloads. Shorter targets require replication, frequent backups, and well tuned restore paths; they also increase cost through additional storage and network overhead.
Manual failover steps inflate recovery time because humans must coordinate, validate, and reconfigure services under pressure. Automation reduces variance by executing the same sequence every time: provisioning, DNS changes, configuration, and smoke tests. High quality runbooks include prerequisites, owner roles, rollback steps, and verification checks. If more than half the plan depends on tribal knowledge, the score should remain conservative.
Quarterly exercises catch drift: permissions, secrets, and infrastructure templates change continuously. Mature programs test monthly or per major release, with at least one full restore of critical data sets. Record artifacts such as timelines, screenshots, and metric exports to prove objectives were met. When tests are skipped, risk accumulates quickly; a single unknown dependency can add hours to recovery.
Interpret the total alongside component breakdowns. If RTO is weak, focus on automation, prebuilt environments, and faster routing updates. If RPO is weak, increase backup frequency or enable continuous replication. If testing is weak, schedule recurring drills and assign owners. Scores above 80 signal strong readiness, 60 to 79 indicates gaps, and below 60 requires immediate action. Pair the score with service tiering: map critical user journeys to higher weights, set alert thresholds, and review trends weekly so leadership sees readiness improving before the next incident in production dashboards.
It summarizes how quickly you can restore service and data, and how reliably you can execute recovery processes. It combines objective targets with operational maturity signals like automation, testing cadence, monitoring coverage, and documentation quality.
Start with current measured values: last restore duration, last failover time, backup schedule, and incident logs. If unknown, enter conservative estimates and flag gaps. Then replace estimates as you run tests and collect evidence.
Each component is converted to a 0–100 subscore using thresholds, then combined with weights. Faster RTO and smaller RPO raise the score, while infrequent testing, weak automation, and missing monitoring reduce it.
At minimum, run quarterly exercises for critical services and perform at least one real restore of important datasets. High change environments benefit from monthly or per release tests, especially after identity, networking, or infrastructure template changes.
Yes. Enter the objectives and practices for the workload’s primary recovery path, and note the weakest link. For active-active designs, use the expected failover time and data loss for a regional outage, not a single instance failure.
Automate failover and restores, standardize runbooks, increase backup frequency, validate restores, and add monitoring for replication lag and backup success. Schedule recurring drills with owners and capture evidence so improvements persist across teams and turnover.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.