CLF-C02 Cloud Technology and Services Practice Question
Which Amazon EC2 instance family is optimized for memory-intensive workloads such as in-memory databases, real-time big data analytics, and high-performance computing?
⚠ Common exam trap
Candidates often confuse 'high-performance computing' with compute-optimized instances, but in the context of memory-intensive HPC (e.g., large-scale simulations or in-memory analytics), the bottleneck is memory capacity and bandwidth, not CPU speed, making memory-optimized instances the correct choice.
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
✓
Memory-optimized instances (R and X family)
Memory-optimized instances (R and X families) are designed for workloads that require large amounts of RAM and high memory bandwidth, such as in-memory databases (e.g., Redis, Memcached), real-time big data analytics (e.g., Apache Spark), and high-performance computing (HPC) tasks. These instances offer a high memory-to-vCPU ratio and support for large instance sizes, enabling efficient processing of data sets that reside primarily in memory.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Compute-optimized instances (C family)
Why it's wrong here
Compute-optimized C-family instances are engineered for CPU-bound processing, offering a high vCPU-to-memory ratio that accelerates tasks such as HPC simulation, batch processing, and media transcoding. They do not address the root need in this scenario, which is having enough RAM to hold a large working dataset; adding fast CPUs cannot compensate when memory is exhausted and the OS begins swapping.
- ✓
Memory-optimized instances (R and X family)
Why this is correct
Memory-optimized R-family and X-family instances, including X1e and the high-memory u-* types, are purpose-built with large RAM capacities—X1e offers up to 3.9 TiB and high-memory instances offer up to 24 TiB. They allow you to load massive datasets entirely into memory and are ideal for SAP HANA, in-memory databases, and real-time analytics, directly matching this workload's requirement.
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Storage-optimized instances (I and D family)
Why it's wrong here
Storage-optimized I-family and D-family instances provide high-speed, low-latency NVMe instance-store SSDs and massive HDDs for I/O-intensive workloads such as NoSQL databases and data warehousing. Their performance advantage comes from local disk architecture, not system memory; if the dataset must reside in RAM, the ephemeral storage these instances offer does not solve the memory-capacity bottleneck.
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Accelerated computing instances (P and G family)
Why it's wrong here
Accelerated computing P-family and G-family instances attach NVIDIA GPUs (or FPGAs in F-family) to offload parallel math, ML training/inference, and graphics rendering. While GPU memory exists, it is a small, specialized resource tied to the accelerator—not general-purpose system RAM—so this instance family does not meet the need for a multi-terabyte in-memory dataset.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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