SAA-C03 Design High-Performing Architectures Practice Question
A CPU-bound batch rendering service runs on EC2. The application is Linux-based, compatible with ARM64, and the team wants the best throughput per dollar without changing the workload's architecture. Which two instance-family choices should the team consider first? Select two.
⚠ Common exam trap
Watch out — candidates often confuse 'CPU-bound' with 'memory-bound' or 'storage-bound,' leading them to select memory-optimized or storage-optimized families, or they may mistakenly think burstable instances can sustain high CPU performance over long periods.
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 compute-optimized family, because it is designed for workloads that spend most of their time on CPU.
Compute-optimized families (e.g., C5, C6g) are designed for workloads that spend most of their time on CPU, such as batch rendering. Option B is correct because Graviton-based instances (e.g., C6g, M6g) use ARM64 architecture, which is compatible with the workload and often delivers better price-performance for compute-intensive tasks, maximizing throughput per dollar without architectural changes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
A compute-optimized family, because it is designed for workloads that spend most of their time on CPU.
Why this is correct
Compute-optimized families provide the highest ratio of vCPUs to memory and are engineered for workloads that need sustained, high-throughput CPU processing. These instances feature high-performance processors and low per-core latency, making them ideal for batch rendering where the application spends most of its time executing compute instructions. By selecting a compute-optimized family, you ensure the rendering service gets the maximum CPU resources per dollar without paying for unnecessary memory or storage.
- ✓
A Graviton-based family, because compatible ARM instances often provide better price performance for many compute workloads.
Why this is correct
Graviton-based instances use AWS's ARM64 processors, which are specifically designed to deliver strong price performance for many compute-bound workloads when the software is compatible with the ARM instruction set. Since the batch rendering service is ARM64-compatible, a Graviton instance (such as the C7g) can provide the same rendering throughput as comparable x86 instances at a lower cost. This makes the Graviton family a valid choice, particularly when you want to optimize for cost efficiency while still meeting CPU requirements.
- ✗
A memory-optimized family, because extra RAM always increases compute throughput.
Why it's wrong here
Memory-optimized families like the R5 or X2gd are built for workloads that need to hold large datasets in RAM, such as in-memory databases or real-time analytics, not for tasks that are compute-constrained. Adding extra RAM to a CPU-bound rendering job does not reduce the time spent on CPU calculations, because memory capacity is not the limiting factor. Choosing one of these instances would overprovision memory, increasing costs while providing no measurable rendering performance benefit.
- ✗
A storage-optimized family, because local storage bandwidth is the main factor for rendering performance.
Why it's wrong here
Storage-optimized instances (e.g., I3en, D2) prioritize high random I/O performance, ephemeral NVMe storage, and large data throughput, making them suitable for data-heavy workloads like Hadoop clusters or log processing. In this scenario, the batch rendering service is CPU-bound, meaning disk throughput is not the bottleneck, and a high-I/O instance will not accelerate the CPU calculations. Therefore, a storage-optimized family would incur unnecessary cost for storage resources that remain idle.
- ✗
A burstable family, because CPU credits make sustained rendering faster during long runs.
Why it's wrong here
Burstable instances (T3, T4g) are designed for workloads with a modest baseline CPU level and occasional spikes, using CPU credits to support short-term bursts. Sustained rendering workloads need constant, predictable CPU performance; once credits are exhausted, the instance is throttled to the baseline, causing slower render times and unstable batch completion durations. This makes the burstable family unsuitable for a CPU-bound service that runs continuously, where compute-optimized or Graviton-based instances are more appropriate.
Go deeper
Related to this question
About these practice questions
Courseiva writes every SAA-C03 question from scratch — 935 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This SAA-C03 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 SAA-C03 exam.