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Disaster Recovery Testing

Use when asked to test backup restoration, failover, and business-continuity recovery procedures — recovery time/point objectives (RTO/RPO) — as distinct from chaos testing (see chaos-testing), which explores unknown failure modes broadly rather than validating one defined recovery plan.

Disaster recovery testing validates that systems can recover from catastrophic failures — hardware failure, network outage, cyberattack, natural disaster — while preserving data integrity and business continuity, by actually rehearsing the recovery procedure rather than just documenting it.

What gets tested

  • Backup restoration — automated verification that backups are actually complete and restorable, not merely that a backup job reported success.
  • Database recovery and application failover — switching operations from a failed primary to a secondary/backup system.
  • System synchronization — confirming data consistency is restored across the recovered components, not just that each is individually running again.
  • End-to-end recovery simulation — full system restoration from various specific failure points, exercising the complete procedure a real incident would require, not just one isolated piece of it.

The two key metrics

  • RTO (Recovery Time Objective) — how long recovery is allowed to take.
  • RPO (Recovery Point Objective) — how much data loss (measured in time since the last good backup/replication point) is acceptable.

Disaster recovery testing measures actual RTO/RPO against the targets set for the business, in a controlled environment, so gaps are found before an actual disaster forces the organization to discover them live.

Automation

Tooling can orchestrate multi-tier recovery scenarios — coordinating database restoration, application redeployment, and network reconfiguration together — and can be scheduled during off-peak hours to minimize disruption while still validating recovery on a regular cadence, integrated into CI/CD so recovery procedures are re-checked as the application evolves rather than validated once and assumed still correct.

Common pitfalls

  • Never actually testing a documented recovery plan — a runbook that exists on paper but has never been rehearsed reliably has gaps that only surface during a real incident, at the worst possible time.
  • Backups verified only by "the job succeeded," not by an actual restore test — a backup that can't actually be restored provides no real protection, however clean its completion log looks.
  • Testing recovery in isolation from the rest of the system — restoring a database without also validating application connectivity and downstream synchronization can miss issues an end-to-end test would catch.
  • Letting the recovery procedure go stale as the application changes — a runbook tested once, years ago, against a since-changed architecture may no longer describe a working recovery path.

Learn more

  • Chaos Testing for exploring unknown failure modes broadly, as a complement to testing one known recovery plan.
  • Failover Testing for the specific case of automatic backup-system switchover.

View disaster-recovery-testing/SKILL.md on GitHub