
Disaster Recovery Testing
This handles the operational side of disaster recovery by giving you structured test plans, automation scripts, and validation procedures. Use it when you're running annual DR exercises, validating RTO/RPO targets, or testing failovers after infrastructure changes. The source includes YAML test plans, pre-test checklists, and automated validation steps. The real value is in the systematic approach: it walks you through pre-test prep, execution, and post-test analysis so you're not winging it when leadership asks if your backups actually work. The emphasis on measuring actual recovery times and documenting lessons learned keeps this practical rather than just checking compliance boxes.
- skills.sh installs
- 437
- GitHub stars
- 379
- last updated
- Aug 21, 2026
Install
$ npx -y skills add aj-geddes/useful-ai-prompts --skill disaster-recovery-testing --agent claude-codeInstalls into .claude/skills of the current project.
Files
Disaster Recovery Testing
Table of Contents
Overview
Implement systematic disaster recovery testing to validate recovery procedures, measure RTO/RPO, identify gaps, and ensure team readiness for actual incidents.
When to Use
- Annual DR exercises
- Infrastructure changes
- New service deployments
- Compliance requirements
- Team training
- Recovery procedure validation
- Cross-region failover testing
Quick Start
Minimal working example:
# dr-test-plan.yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: dr-test-procedures
namespace: operations
data:
dr-test-plan.md: |
# Disaster Recovery Test Plan
## Test Objectives
- Validate backup restoration procedures
- Verify failover mechanisms
- Test DNS failover
- Validate data integrity post-recovery
- Measure RTO and RPO
- Train incident response team
Sponsors
Details
- Repository
- github.com/aj-geddes/useful-ai-prompts
- Categories
- Testing & QA, AI & Agent Building
- First seen
- Jun 3, 2026
More from aj-geddes/useful-ai-prompts
All 258- Release Planning436
- Intermittent Issue Debugging433
- Server Side Rendering433
- Mocking Stubbing432
- Data Migration Scripts430
- Correlation Tracing429
- Synthetic Monitoring427
- Canary Deployment426
- Service Mesh Implementation426
- Azure Functions424
- Data Replication Setup424
- Graphql Implementation424
- Polyglot Integration424
- Distributed Tracing418
- Multi Cloud Strategy418
- Anomaly Detection
- Causal Inference
- Classification Modeling
- Clustering Analysis
- Cohort Analysis
- Computer Vision
- Correlation Analysis
- Data Cleaning Pipeline
- Data Visualization