RTO
Definition
Recovery Time Objective - maximum acceptable time to restore service after a failure, crucial for minimizing downtime and maintaining user trust.
Use Cases
- Netflix: Maintain streaming availability during regional outages and infrastructure failures. — Built a resilient microservices architecture on AWS with redundancy across multiple Availability Zones, automated recovery practices, and chaos engineering to validate that services can recover quickly when components fail. (Improved service resilience and faster recovery from failures, reducing customer impact during incidents.)
- Etsy: Reduce downtime and recover quickly from production incidents affecting the online marketplace. — Adopted an engineering culture focused on reliability, frequent deployments, monitoring/alerting, and incident response practices designed to restore service rapidly after failures. (Faster incident detection and recovery, helping minimize downtime and protect revenue during outages.)
- GitHub: Restore core developer services after major outages affecting code hosting and collaboration. — Uses backups, replication, and documented incident response/runbooks; after high-profile incidents, invested in improving database resilience and recovery processes to reduce time to restore service. (Improved recovery capabilities over time and clearer operational practices to reduce time-to-restore during incidents.)
Frequently Asked Questions
- What's the difference between RTO and RPO?
- RTO is how long you can afford to be down (time to restore service). RPO (Recovery Point Objective) is how much data you can afford to lose (how far back you can recover). Example: RTO 30 minutes means service must be back within 30 minutes; RPO 5 minutes means you can lose at most 5 minutes of data.
- How do I choose an RTO for my application?
- Start with business impact: estimate revenue loss, customer impact, and operational risk per hour of downtime. Then classify systems (critical vs. non-critical) and set tighter RTOs for customer-facing or revenue-generating services. Validate feasibility with your architecture (automation, failover, backups) and test regularly with disaster recovery drills.
- How much does a lower RTO cost?
- Lower RTOs usually cost more because they require more redundancy and automation. Common cost drivers include running standby capacity (warm/hot standby), multi-zone or multi-region deployments, data replication, higher-performance storage, managed failover tooling, and more frequent testing. A very low RTO (minutes) often implies active-active or hot standby designs, while higher RTOs (hours) can rely more on backups and manual recovery.
Category: software
Difficulty: intermediate
Related Terms
See Also