Georgia Tech CRC delivers enterprise-grade cloud resilience and continuous recovery capabilities for modern applications. This platform helps technology teams design, test, and operate reliable failure recovery workflows at scale.
Engineers rely on Georgia Tech CRC to validate disaster recovery strategies, automate failover testing, and meet demanding service-level objectives. The following sections outline core capabilities, deployment patterns, and operational guidance.
| Component | Role | Target Workloads | Recovery Objective |
|---|---|---|---|
| Core Engine | Executes planned and automated recovery workflows | Transactional services, stateful applications | RTO/RPO targets configuration |
| Integration Layer | Connects with CI/CD, monitoring, and cloud APIs | Microservices, data pipelines | Event-driven orchestration |
| Observability Dashboard | Shows recovery status, SLA compliance, and test history | All platform services | Real-time insight and audit trails |
| Security Controls | Manages encryption, identity, and network policies | Regulated environments | Least-privilege and compliance |
Architecture and Deployment Models
Georgia Tech CRC supports hybrid deployment across on-premises data centers and multiple cloud accounts. The architecture emphasizes modular components that can scale independently as recovery demand grows.
Core patterns include active-passive and active-active configurations, with clear guidance on data replication, network peering, and failover sequencing. Teams can start with a minimal pilot and expand coverage as confidence increases.
Deployment Checklist
- Define recovery priorities per application
- Map dependencies across services
- Configure network and security rules
- Run validation tests in staging
- Establish monitoring and alerting
Planning for Resilience
Effective resilience planning with Georgia Tech CRC begins by classifying workloads, setting realistic RTO and RPO targets, and documenting runbooks for failover and failback. The platform ties these plans to measurable test schedules.
By linking plans to CI pipelines, changes to infrastructure automatically trigger updates to recovery procedures. This keeps resilience posture aligned with rapid development cycles and reduces manual errors during incidents.
Automation and Testing
Georgia Tech CRC emphasizes automated testing to validate recovery procedures without disrupting production. Scheduled drills simulate failures at different layers, from instance termination to region-wide outages.
Test results feed directly into the observability dashboard, highlighting deviations from expected behavior. Teams can compare successive test runs to track improvements and identify remaining gaps in automation or documentation.
Security and Compliance
Security controls in Georgia Tech CRC ensure that recovery operations respect encryption, identity, and network policies defined by the organization. Role-based access and audit logging help meet internal and external compliance requirements.
Policy-as-code features allow teams to codify recovery guardrails and enforce them across environments. This reduces configuration drift and provides clear evidence of resilient design during audits.
Operational Best Practices
- Define service categories and assign recovery objectives
- Automate recovery steps and keep runbooks current
- Schedule regular failover tests in isolated environments
- Monitor dependencies and network readiness
- Review test outcomes and update plans continuously
FAQ
Reader questions
How does Georgia Tech CRC integrate with existing CI/CD pipelines?
It provides native connectors and step templates that trigger recovery plans, run failover simulations, and report status back to the pipeline without manual intervention.
Can I use CRC for multi-cloud disaster recovery?
Yes, the platform supports heterogeneous cloud environments and abstracts provider-specific networking and compute resources through a unified recovery model.
What metrics are available on the observability dashboard?
Dashboards show recovery duration, point-in-time consistency, SLA compliance, test success rates, and detailed logs for each recovery step.
How are RTO and RPO validated in practice?
Through scheduled chaos experiments that measure actual recovery time and data loss under controlled failure scenarios, with results compared against defined targets.