How do cloud providers handle failover and disaster recovery?

Cloud providers handle failover and disaster recovery through a combination of redundancy, automated systems, and geographically distributed infrastructure. Failover refers to the process of switching to backup systems when a primary component fails, while disaster recovery involves restoring operations after a major outage. Providers achieve this by replicating data and services across multiple locations and using monitoring tools to detect and respond to failures automatically.

A key strategy is the use of multiple availability zones (AZs) within a region. For example, AWS operates isolated AZs with independent power, cooling, and networking. If one AZ fails, workloads automatically shift to another without downtime. Similarly, Google Cloud’s Global Load Balancer distributes traffic across regions, rerouting users to the nearest healthy instance if an outage occurs. Data is often replicated synchronously within a region for low-latency access and asynchronously across regions for disaster recovery. Azure’s Geo-Redundant Storage (GRS), for instance, copies data to a secondary region hundreds of miles away, ensuring it remains accessible even if the primary region is compromised.

Disaster recovery plans vary based on recovery time objectives (RTO) and recovery point objectives (RPO). Providers offer tools like AWS Site Recovery, which automates failover for EC2 instances, and Azure Site Recovery, which replicates VMs between regions. These services often integrate with databases (e.g., Amazon RDS Multi-AZ deployments) and storage solutions to minimize data loss. Developers can configure policies to prioritize critical systems, test failover scenarios without disrupting production, and use versioned backups (e.g., Google Cloud’s Persistent Disk snapshots) to restore to specific points in time. Regular testing and monitoring via services like CloudWatch or Azure Monitor ensure recovery processes remain reliable.