CLF-C02 Cloud Concepts Practice Question
Which statement best describes 'high availability' in the context of AWS cloud architecture?
⚠ Common exam trap
Many exam-takers confuse 'high availability' with 'scalability' (Option A) or 'durability' (Option D), as candidates often think adding more resources or storing extra copies automatically ensures uptime, but high availability specifically requires redundant, fault-tolerant components with automatic failover mechanisms.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
A design that minimizes downtime by eliminating single points of failure and enabling automatic recovery
High availability in AWS is achieved by designing architectures that eliminate single points of failure and enable automatic recovery, typically using services like Elastic Load Balancing (ELB) to distribute traffic across multiple Availability Zones (AZs) and Auto Scaling to replace failed instances. This ensures that if one component fails, another takes over seamlessly, minimizing downtime. Option B correctly captures this core principle of fault tolerance and automated failover.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The ability to handle any amount of traffic by adding more resources
Why it's wrong here
The ability to handle any amount of traffic by adding more resources is elasticity or scalability, a capacity-focused trait that is neither necessary nor sufficient for high availability. A scalable application that is scaled out for load still has single points of failure and no automatic failover if its architecture is not designed for resilience. Conversely, a small but redundant architecture with automatic recovery can be highly available without ever scaling to arbitrary traffic levels. HA is specifically about minimizing downtime, not maximizing throughput.
- ✓
A design that minimizes downtime by eliminating single points of failure and enabling automatic recovery
Why this is correct
High availability (HA) architectures deliberately avoid any single point of failure by replicating critical components across multiple Availability Zones and using automated detection and failover. For example, an Application Load Balancer routes traffic only to healthy instances, and Auto Scaling replaces failed instances automatically. This combination minimizes downtime because recovery is initiated without human intervention, keeping the application reachable despite a component failure.
- ✗
Using the largest available instance types for maximum performance
Why it's wrong here
Choosing the largest available instance types is a scale-up performance decision, not an availability strategy. A single oversized EC2 instance still resides in one Availability Zone and is a single point of failure; if the instance or its underlying host fails, the workload goes down. Maximum compute capacity says nothing about the system's ability to tolerate failures or recover automatically.
- ✗
Storing multiple copies of data in Amazon S3
Why it's wrong here
Amazon S3's redundant copies guarantee high data durability — objects survive disk and facility failures — but they do not by themselves make an application highly available. Durability answers the question 'will my data still exist?', while availability answers 'can users access the service right now?'. An application can lose its compute tier or database endpoint and be unavailable for hours even though its S3 data remains perfectly intact. S3 redundancy is at most one building block of an HA design, not the defining property.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This CLF-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the CLF-C02 exam.