A company runs a batch processing job on a single Amazon EC2 instance. The job takes 10 hours to complete. The company needs to reduce the processing time to under 1 hour to meet a new business requirement. The data can be split into independent chunks that can be processed in parallel. Which cloud computing concept would most directly enable the company to achieve this goal?
Scalability is the ability to increase resources (scale up or out) to handle growing workloads or to reduce task completion times. By splitting the data into independent chunks and processing them in parallel across multiple EC2 instances, the company horizontally scales its compute capacity, directly reducing the job time from 10 hours to under 1 hour.
Why this answer
Scalability is the correct answer because it refers to the ability to increase resources to handle increased load. By scaling horizontally (adding more EC2 instances) and processing the independent data chunks in parallel, the batch job can be completed in under 1 hour instead of 10 hours.
Exam trap
The trap here is that candidates confuse elasticity with scalability, but elasticity is about automatic resource adjustment to match fluctuating demand, not about adding resources to meet a fixed performance goal.
Why the other options are wrong
Elasticity refers to automatically scaling resources up or down based on demand, but the question requires reducing processing time for a fixed workload by parallelizing independent chunks, which is a scalability (specifically horizontal scaling) concern, not elasticity.
High availability focuses on ensuring system uptime and resilience to failures, not on reducing processing time through parallel execution. The requirement is to complete the job faster by processing independent chunks in parallel, which is a scalability concern.
Fault tolerance focuses on maintaining system operation during failures, not on reducing processing time. The requirement is to complete the job faster, not to handle component failures.