Challenge your understanding of high availability and fault tolerance in cloud computing. This quiz covers key concepts, essential strategies, and best practices for building reliable, resilient cloud-based systems.
Which statement best describes high availability in the context of cloud computing?
Explanation: High availability focuses on keeping systems running with as little downtime as possible. This is different from scaling, which deals with managing increased load; encryption, which is about security; or access control, which prevents unauthorized use. The distractors represent important cloud principles, but do not capture the true meaning of high availability.
What does fault tolerance in cloud computing systems primarily aim to achieve?
Explanation: Fault tolerance ensures that a system remains functional when parts fail, providing uninterrupted service. Maximizing speed is related to performance, not fault tolerance. Lowering costs or restricting access may be goals in some scenarios but do not align with the concept of fault tolerance. The main aim is continuous operation during failures.
Which scenario best illustrates the use of redundancy to increase availability in the cloud?
Explanation: By deploying applications in multiple places, redundancy is achieved, increasing availability if one location fails. Limiting users or encrypting traffic are related to security or performance but do not address redundancy. Running only one over-allocated server introduces a single point of failure, which is the opposite of redundancy.
How does a load balancer help improve high availability in cloud-based applications?
Explanation: A load balancer directs user requests evenly, helping to avoid overloading any single resource and increasing the application's availability. Compressing data relates to storage efficiency, encryption safeguards transfers, and reducing individual server hardware expenses does not maintain availability. Only distributing traffic addresses high availability directly.
If a system relies on one database server and that server fails, what architecture flaw does this reveal?
Explanation: Depending on a single component that can cause the whole system to stop if it fails is known as a single point of failure. Excessive scaling refers to unnecessary expansion, data redundancy is about duplication for safety, and over-provisioning means allocating extra resources. Only single point of failure accurately describes this issue.
What does Recovery Time Objective (RTO) define in the context of cloud services?
Explanation: RTO specifies the longest time a service can be unavailable after an incident before causing significant harm. Minimum bandwidth, cost, or audit frequency do not represent RTO. Only the maximum time to recover from disruption fits the correct definition.
A cloud service automatically adds more servers when demand rises and removes them when demand drops. What strategy is this an example of?
Explanation: Auto-scaling adjusts the number of active servers based on current demand, supporting higher availability and performance. Fault isolation separates failures, manual provisioning requires human effort, and data sharding involves splitting data across databases. Only auto-scaling automatically manages server counts with changing demand.
Why are stateless applications easier to make highly available in the cloud than stateful ones?
Explanation: Stateless apps keep user and session data independent from any one server, allowing easy recovery or replication. While stateful apps don't always use more memory or ignore redundancy, handling their persistent data adds complexity. Running on one server limits availability, which is not true for stateless apps.
What is a key benefit of deploying cloud resources in multiple geographic locations?
Explanation: Spreading resources across locations ensures that an issue in one area doesn't bring down the whole system. This decreases risk, not increases latency or removes the need for backups. Centralized management may not help with outages and is less related to safety from regional issues.
Cloud architectures often use health checks on servers. What is the primary purpose of these health checks?
Explanation: Health checks routinely monitor if servers are working correctly and help identify failures quickly, supporting high availability. They do not directly relate to encryption, manual resource allocation, or cost measurement. Only the first option captures the routine monitoring needed for resilient cloud systems.