Business continuity and disaster recovery (BCDR) are crucial aspects of any organization’s IT strategy. As more businesses move to the cloud, understanding BCDR concepts like Recovery Time Objective (RTO) and Recovery Point Objective (RPO) for cloud environments like Amazon Web Services (AWS) is key.
RTO and RPO help quantify BCDR needs and drive technical requirements. This article will cover what RTO and RPO are, their importance for cloud disaster recovery, and how to determine appropriate RTO and RPO targets for an AWS environment.
What is RTO?
Recovery Time Objective or RTO is the maximum tolerable time an application can be down after a disaster. It defines the time required to recover critical IT systems to a working state after an outage.
RTO represents business expectations for recovery time. A shorter RTO implies faster expected recovery. RTO is measured in time units like hours, minutes or seconds.
For example, an RTO of 4 hours means critical systems must be recovered within 4 hours after an outage or disaster. For mission-critical systems, RTOs could be less than an hour.
Why is RTO important?
RTO is a key metric to plan and measure disaster recovery capabilities. RTO sets the recovery timeline objective and drives technical requirements for data replication, failover automation and more. Without an RTO target, BCDR solutions cannot be properly designed.
RTO also represents maximum acceptable downtime. Violating the RTO has direct business impact from lack of availability and productivity. RTO drives the investment needed to achieve desired recoverability – lower RTO requires more robust DR infrastructure and processes.
Setting appropriate RTOs requires understanding business needs, costs and risks. A lower RTO increases IT expense to achieve faster recovery, so RTO targets must balance business needs with budget.
What is RPO?
Recovery Point Objective or RPO represents the maximum acceptable amount of data loss after an outage. It defines the point in time to which systems and data must be recovered after a disaster.
RPO is measured in time units like hours, minutes or seconds. For example, an RPO of 1 hour means critical systems and data must be restored to a state no more than 1 hour before the failure occurred.
Why is RPO important?
RPO, like RTO, is a key BCDR metric that sets data recovery requirements. A lower RPO minimizes data loss but requires more frequent data replication. RPO helps determine appropriate data backup and replication strategies.
An excessive RPO can mean unacceptable data loss. For example, losing 1 day of transaction data might not meet business needs. Balance is required between RPO, costs, and acceptable data loss if recovery exceeds the RPO.
Aligning RPO with business needs is vital. For example, a 1 second RPO could be excessive for a non-critical system but unacceptable for a high volume transaction system.
RTO and RPO Dependencies
RTO and RPO targets often have a dependent relationship. Because lower RPO requires more frequent replication, it directly supports a lower RTO by having more current data ready for fast recovery. But achieving aggressive RTO and RPO targets results in higher costs.
Here are some key dependencies between RTO and RPO:
- Lower RPO supports lower RTO by having more current data ready to restore services faster.
- Lower RTO requires infrastructure capable of faster recovery speed.
- More frequent replication drives higher costs but allows for a lower RPO.
- Lengthening RPO can reduce costs but may miss business RTO expectations.
- Aggressive RTO and RPO targets require higher investment in DR technologies and processes.
Organizations may choose to set a higher RPO target if extremely low data loss is not required. This allows optimizing the RPO to match business needs rather than defaulting to a very low RPO that drives up costs.
Sample RTO and RPO targets
RTO and RPO targets vary significantly based on the criticality of systems and business recovery needs. Here are some representative samples:
| System Criticality | RTO | RPO |
|---|---|---|
| Mission critical | Less than 1 hour | Near zero |
| Critical | Less than 4 hours | Less than 1 hour |
| Important | Less than 24 hours | 4 to 6 hours |
| Non-critical | 1 to 3 days | 24 hours |
As shown above, RTO and RPO targets for the most critical systems and applications are very aggressive at less than 1 hour. Important but non-core systems can have RTOs of a day or longer and RPOs of several hours.
RTO and RPO Considerations for AWS
The public cloud introduces some unique aspects for RTO and RPO. Here are key considerations when determining RTO and RPO targets for disaster recovery in AWS:
Availability Zone and Region Resiliency
AWS infrastructure is highly resilient within an Availability Zone (AZ) and across AZs in a Region. However, recovery across Regions may be needed for geographic diversity or isolation from large-scale outages.
Intra-AZ and intra-Region recovery may allow for shorter RTO and RPO targets compared to cross-Region. The higher latency between Regions impacts replication frequency and recovery timing.
Stateful Services
Many AWS services like EBS volumes, RDS databases and DynamoDB are stateful in nature and require replication and restoration of current data for disaster recovery. Meeting RPO targets depends on replication frequency and ability to failover to current data.
Serverless Services
Serverless services like Lambda functions, S3 storage and API Gateway have inherent resiliency within and across regions. Recovery can focus on restoring code and configuration rather than state. This supports faster RTO with potentially longer RPO.
Automated Recovery
AWS enables automation of recovery tasks like failing over instances, databases and stateful services. Orchestrating failover automatically can minimize RTO for recovering the infrastructure and platform layers.
But application validation and testing may still be needed for final recovery, so RTO will depend on recovery automation as well as application design factors.
Testing
Regular disaster recovery testing is essential to validate that RTO and RPO can actually be met in a real recovery scenario. Gaps identified in testing can be used to improve BCDR plans.
Testing should cover infrastructure as well as applications for comprehensive validation of all tiers. Each application and dependency must be recovered within its RTO and with data loss under its RPO.
Determining Appropriate RTO and RPO Targets
Setting viable RTO and RPO targets for AWS environments requires considering several aspects:
Business Impact Analysis
Understand the impacts of downtime on business processes and financials to set initial restoration timeframes. Identify maximum tolerable outage durations for each application.
Regulatory Requirements
Some industries have defined RTO and RPO standards that must be met. These represent the minimum requirements for compliance.
Data Criticality
The criticality and rate of change for data will indicate what granularity of RPO is needed. High volume transactional data will necessitate a lower RPO.
Dependency Mapping
Map dependencies between systems and business processes to determine RTO impacts propagating across integrated applications.
Cost Analysis
The infrastructure and replication mechanisms required to meet different RTO and RPO targets can be cost modeled to help set viable objectives.
Testing
Conduct testing to determine actual recovery times and data loss. Gap identification from testing can be used to adjust RTO/RPO or improve recovery capabilities.
An iterative approach adjusting RTO/RPO targets based on testing results is recommended. This helps align targets with actual recovery while managing costs.
Achieving RTO and RPO Targets in AWS
AWS provides many native capabilities and services to help meet RTO and RPO requirements for disaster recovery:
High Availability Architectures
Deploying resources across AZs and auto scaling enables resilience and uptime within a region. Global Accelerator and Route 53 can route across regions.
Service High Availability
Stateful services like RDS and DynamoDB are engineered for high availability across AZs or regions.
Storage Replication
AWS storage services provide built-in replication like cross-region S3 and cross-AZ EBS for recovery scenarios.
Database Replication
Databases like RDS provide replication features like RDS Multi-AZ for low RPO failover.
Orchestration
AWS APIs support automation of DR processes. Orchestration tools like AWS CloudFormation expand automation capabilities.
Pre-Provisioned Capacity
Capacity can be pre-deployed in a second region to support faster recovery when needed.
Backups
AWS Backup service centrally manages backups across AWS services to support recovery use cases.
Continuous Data Replication
CDP solutions continuously replicate changed data with RPOs as low as seconds to support fast recovery.
Recovery Services
Managed disaster recovery services like CloudEndure Disaster Recovery simplify and automate server replication and failover.
Combining AWS native capabilities with third party or managed solutions enables cost-effective achievement of RTO and RPO targets.
RTO and RPO Best Practices for AWS
Following AWS best practices helps meet desired recovery time and data loss targets:
- Set RTO and RPO targets based on business needs and acceptable risks.
- Use multiple AWS regions for geographic diversity and large-scale resilience.
- Deploy critical infrastructure across availability zones for intra-region HA.
- Leverage AWS native replication capabilities to minimize RPO.
- Automate recovery runbooks and failover tasks to reduce RTO.
- Pre-deploy capacity in a secondary region to support rapid recovery.
- Regularly test disaster recovery plans end-to-end.
- Review RTO and RPO targets post-testing and adjust as needed.
Conclusion
RTO and RPO are essential metrics for evaluating disaster recovery capabilities for business continuity. AWS provides native services and options for third party solutions to help meet RTO/RPO targets cost-effectively.
Setting realistic RTO and RPO based on business needs, recovery architecture and testing results is key to maintaining business continuity on AWS.