In the world of cloud resilience, the decision to initiate a multi-region failover is never taken lightly. For organizations running mission-critical workloads, a regional outage can halt digital customer journeys and result in significant revenue loss. While AWS provides foundational infrastructure for high availability, the actual execution of a multi-region failover remains an inherently complex process that requires seamless coordination across multiple technical teams.
Traditional disaster recovery (DR) strategies often fall short because they rely on manual "click-ops" and fragmented documentation. To truly master application resilience, technical leaders are turning to specialized disaster recovery platforms that automate the heavy lifting.
In this article, we will overview how IT disaster recovery solutions handle multi-region failover, and specifically how automated AI-powered runbooks streamline and simplify the process.
How IT disaster recovery platforms handle multi-region failover
Disaster recovery platforms simplify recovery by transforming static documentation into dynamic, executable runbooks. Instead of teams manually entering commands into multiple consoles, the platform acts as a central orchestrator.
Step-by-Step: Automating the Multi-Region Failover Process
Using Cutover Recover, organizations can orchestrate a multi-region failover for complex AWS workloads. Below is an example of the steps involved in a failover for Amazon OpenSearch Service through a structured, automated workflow.
1. Pre-Failover: Scaling the Standby Environment
In a "Pilot Light" strategy, the standby region maintains a minimal footprint to save costs. When a multi-region failover is imminent, the platform automates the scaling of the standby OpenSearch cluster:
- Querying Configuration: Automated tasks use the DescribeDomainConfig endpoint to identify active production capacity.
- Automated Scaling: The platform triggers UpdateDomainConfig to match the standby region to the primary region's scale.
- Verification: The runbook polls DescribeDomainChangeProgress to ensure the environment is ready before proceeding.
2. The Failover: Redirecting Traffic and Promoting Data
Once the environment is scaled, the platform facilitates the core multi-region failover steps while keeping a "human in the loop" for the final Go/No-Go decision.
- Traffic Routing: Integration with Amazon Route 53 Application Recovery Controller (ARC) turns off routing controls in the affected region to shift traffic.
- Data Promotion: For databases like Amazon Aurora, the platform executes the FailoverGlobalCluster endpoint to promote the secondary region.
- Data Integrity: The platform confirms that leader and follower checkpoints are synced before stopping replication to avoid data loss.
3. Post-Failover Validation
A successful multi-region failover requires immediate verification. Runbooks include automated validation tasks linked to monitoring dashboards to track CPU, memory, and response times.
Managing the "Return Home" (Failback)
Returning to the primary region is often more complex than the initial multi-region failover. Platforms like Cutover handle this by reversing the replication flow:
- Reverse Sync: Synchronizing data deltas from the failover region back to the original primary.
- Re-establishing Replication: Using automated tasks to start replication in the opposite direction.
- Cleanup: Scaling down the failover region after the move to maintain operational resilience and cost efficiency.
Benefits of Automated Orchestration
By standardizing multi-region failover through automated runbooks, businesses can recover up to 50% faster. This ensures that every team, from Network to Applications, executes the plan perfectly, maintaining compliance via an immutable audit log.
Multi-Region Failover FAQ
What is the difference between Multi-AZ and Multi-Region failover?
Multi-AZ provides high availability within a single region by replicating across data centers. A multi-region failover protects against total regional outages by shifting workloads to a completely different geographical area.
How long does it take to scale an OpenSearch cluster during failover?
In a benchmark scenario with ~37GB of data, scaling from a single AZ warm node to a 3-AZ production cluster takes approximately 41 minutes.
Can a multi-region failover be fully automated?
While technical steps are automated via APIs, best practices include a "human-in-the-loop" Go/No-Go decision point to prevent accidental or unnecessary failovers.
Why is "cleanup" important after a failover event?
Cleanup ensures that redundant, high-capacity nodes in the standby region are scaled back down, preventing unnecessary cloud costs once the primary region is restored.