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CLF-C02 Billing, Pricing, and Support Practice Question

Which AWS pricing model provides the largest discount compared to On-Demand pricing in exchange for a 1 or 3-year commitment with full upfront payment?

⚠ Common exam trap

A common mix-up: candidates confuse the discount depth of Compute Savings Plans (which are flexible across instance families) with the maximum discount available, overlooking that the 3-year All Upfront Reserved Instance commitment provides the highest percentage discount due to the longest term and full upfront payment.

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

✓

Reserved Instances (All Upfront, 3-year)

Reserved Instances (All Upfront, 3-year) provide the largest discount compared to On-Demand pricing because the customer commits to a 1- or 3-year term and pays the entire amount upfront, which gives AWS predictable capacity planning and reduces billing overhead. This model can offer discounts of up to 72% off On-Demand rates, significantly more than partial upfront or no upfront options, and is the most cost-effective for steady-state workloads.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ✗

    Spot Instances

    Why it's wrong here

    Spot Instances can save up to 90% by using spare EC2 capacity, but they are interruptible with a 2-minute warning when AWS needs the capacity back. They are not a purchasing commitment like a Reserved Instance; rather, they are a flexible capacity acquisition model at a variable, market-driven price. For a critical, steady-state workload that must run without interruption, Spot's reclaim risk makes it a poor candidate for the primary cost-saving strategy.

  • ✗

    On-Demand Instances

    Why it's wrong here

    On-Demand Instances are the baseline EC2 pricing model with no upfront payment or long-term commitment, but they also receive no discount. You pay the full list price per second or per hour, which means predictable, always-on workloads incur the maximum compute spend without any savings mechanisms. While On-Demand offers absolute flexibility and is ideal for short-term or spiky workloads, it is the least cost-effective choice for a service that will run continuously for an extended period.

  • ✓

    Reserved Instances (All Upfront, 3-year)

    Why this is correct

    Reserved Instances with all upfront payment and a 3-year term provide the largest EC2 discount, commonly up to 72% or more, because the customer pays the entire compute cost in advance, locking in the lowest hourly rate. The uptime requirement of a steady, uninterrupted workload aligns perfectly with an RI commitment, since the workload itself already guarantees utilization. A Standard Regional RI also offers the best rate for a fixed EC2 configuration, making this the maximum-savings answer for a production system that will run for years.

  • ✗

    Compute Savings Plans (1-year, No Upfront)

    Why it's wrong here

    Compute Savings Plans with a 1-year term and no upfront payment give you flexibility to change instance families and even switch between EC2, Fargate, and Lambda, but that flexibility is a tradeoff: the discount is noticeably lower than an all-upfront 3-year Reserved Instance. No-upfront plans do not require paying everything at once, yet they still commit you to a consistent dollar-per-hour spend for one year while yielding a much smaller savings ratio. For a workload that is guaranteed to run continuously, accepting the lower discount of a 1-year no-upfront plan leaves significant cost savings unrealized.

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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.