- A
Amazon FSx for Lustre
High-performance file system with sub-millisecond latency.
- B
Amazon EBS Snapshots for fast restore
Why wrong: Snapshots are for backup, not caching.
- C
Amazon S3 Transfer Acceleration
Why wrong: Accelerates uploads to S3, not data loading to GPU.
- D
Amazon CloudFront
Why wrong: Content delivery network, not for ML data loading.
Question 1,688 of 1,755
MLS-C01 Practice Question: Machine Learning Implementation and Operations
This MLS-C01 practice question tests your understanding of machine learning implementation and operations. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A team is training a large language model using PyTorch on multiple GPUs. The training is taking too long due to inefficient data loading. Which AWS service can help accelerate data loading by caching data close to the GPU instances?
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
✓
Amazon FSx for Lustre
Amazon FSx for Lustre is a high-performance file system optimized for machine learning workloads. It provides sub-millisecond latencies and high throughput by caching training data on local NVMe SSDs attached to the Lustre servers, which are co-located with GPU instances in the same AWS Availability Zone. This eliminates the I/O bottleneck from remote object storage, directly accelerating data loading for PyTorch DataLoader workers.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Amazon FSx for Lustre
Why this is correct
High-performance file system with sub-millisecond latency.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon EBS Snapshots for fast restore
Why it's wrong here
Snapshots are for backup, not caching.
- ✗
Amazon S3 Transfer Acceleration
Why it's wrong here
Accelerates uploads to S3, not data loading to GPU.
- ✗
Amazon CloudFront
Why it's wrong here
Content delivery network, not for ML data loading.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse 'caching data close to compute' with general-purpose CDN or acceleration services, failing to recognize that Amazon FSx for Lustre is the only option designed for high-throughput, low-latency file system access in a GPU cluster environment on AWS.
Detailed technical explanation
How to think about this question
FSx for Lustre uses a distributed parallel file system based on the Lustre protocol, which stripes data across multiple NVMe SSDs and servers to achieve aggregate throughput of hundreds of GB/s. In a real-world scenario, training a 175B-parameter model with terabytes of tokenized data, FSx for Lustre can saturate the GPUs' PCIe bandwidth, reducing data loading time from hours to minutes compared to reading from S3 directly. A subtle behavior is that Lustre's 'import' feature can lazily fetch data from S3 on first access, but for best performance, you should pre-cache the dataset using 'hsm_restore' to avoid cold-start latency.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Machine Learning Implementation and Operations — This question tests Machine Learning Implementation and Operations — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Amazon FSx for Lustre — Amazon FSx for Lustre is a high-performance file system optimized for machine learning workloads. It provides sub-millisecond latencies and high throughput by caching training data on local NVMe SSDs attached to the Lustre servers, which are co-located with GPU instances in the same AWS Availability Zone. This eliminates the I/O bottleneck from remote object storage, directly accelerating data loading for PyTorch DataLoader workers.
What should I do if I get this MLS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
This MLS-C01 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 MLS-C01 exam.
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