High Availability and Redundancy in Cloud Questions and Answers for Viva

Answer-1: High availability ensures that cloud services remain accessible and operational with minimal downtime.

Answer-2: Redundancy involves duplicating critical components to avoid single points of failure and ensure service continuity.

Answer-3: Techniques include load balancing, failover, clustering, and data replication.

Answer-4: Failover automatically switches operations to a backup system when the primary system fails.

Answer-5: Active-active runs multiple systems simultaneously; active-passive keeps backups idle until needed.

Answer-6: They use geographically distributed data centers with redundant power, networking, and cooling.

Answer-7: Load balancers distribute traffic evenly, preventing overload and enabling failover.

Answer-8: A Service Level Agreement specifies the guaranteed uptime percentage provided by a cloud service.

Answer-9: It means 99.999% uptime, allowing about 5 minutes of downtime per year.

Answer-10: Through replication across multiple storage nodes or regions to prevent data loss.

Answer-11: Replication copies data continuously for availability; backup is periodic and for recovery.

Answer-12: Fault tolerance allows a system to continue functioning correctly even if some components fail.

Answer-13: A SPOF is any component whose failure causes the entire system to fail.

Answer-14: By using redundant resources, failover mechanisms, and distributed systems.

Answer-15: Horizontal scaling adds more instances; vertical scaling increases resources on a single instance.

Answer-16: Health checks monitor system status to trigger failover or load redistribution automatically.

Answer-17: Auto-scaling adjusts resources dynamically based on demand to prevent overload and downtime.

Answer-18: AZs are isolated data centers within a region to provide redundancy and fault tolerance.

Answer-19: By replicating data and services across multiple regions to survive regional failures.

Answer-20: DR is the strategy to recover after major failures, complementing high availability which minimizes downtime.

Answer-21: Synchronous replication waits for confirmation from the backup; asynchronous proceeds without waiting.

Answer-22: It directs traffic to healthy instances, ensuring no traffic goes to failed servers.

Answer-23: By using multiple network paths, ISPs, and failover routing protocols.

Answer-24: Failback is returning operations from the backup system to the primary system after recovery.

Answer-25: Multiple power sources and backup generators prevent outages affecting cloud availability.

Answer-26: Solutions include Amazon RDS Multi-AZ, Google Cloud SQL HA, and Azure SQL Always On.

Answer-27: Orchestrators like Kubernetes automate container failover and scaling.

Answer-28: An availability set is a group of VMs designed to ensure uptime during planned or unplanned maintenance.

Answer-29: Replication lag can delay data consistency, impacting failover accuracy.

Answer-30: Monitoring detects failures early to trigger automated recovery processes.

Answer-31: By performing failover drills and chaos engineering exercises.

Answer-32: CAP states that a distributed system can guarantee only two of Consistency, Availability, and Partition tolerance at once.

Answer-33: DNS can route traffic to healthy endpoints and support failover.

Answer-34: CDNs distribute content closer to users, reducing latency and offloading traffic.

Answer-35: An SLA breach occurs when uptime falls below the agreed threshold, potentially leading to penalties.

Answer-36: Stateless apps can be easily replicated and load-balanced without session dependency.

Answer-37: Quorum is the minimum number of nodes that must agree to perform an operation, ensuring data consistency.

Answer-38: By having multiple instances and failover to prevent a single point of failure.

Answer-39: Deploying apps in multiple geographic regions enhances availability and disaster recovery.

Answer-40: Backups provide data restoration options if redundancy mechanisms fail.

Answer-41: RTO is Recovery Time Objective (how fast to recover); RPO is Recovery Point Objective (acceptable data loss).

Answer-42: Sharding distributes data across nodes, improving performance and fault tolerance.

Answer-43: Challenges include network partitions, data consistency, and cost management.

Answer-44: Automation enables rapid failover, recovery, and scaling without manual intervention.

Answer-45: A load balancer that automatically adjusts capacity to handle traffic changes.

Answer-46: Session persistence can limit failover if sessions are tied to specific instances.

Answer-47: Service meshes manage microservice communication, retries, and failover, enhancing availability.

Answer-48: Cloud-native apps are designed for resilience, scalability, and fault tolerance.

Answer-49: Proper planning ensures minimal downtime during scheduled maintenance.

Answer-50: By selecting appropriate redundancy levels that meet SLAs without over-provisioning resources.