CLF-C02 Cloud Technology and Services Practice Question
A company stores genomics data (several petabytes) on Amazon S3. They need to run complex analytics on this data using standard bioinformatics tools that require a POSIX file system interface. Which AWS solution provides this?
⚠ Common exam trap
Test-takers frequently confuse Amazon EFS (a POSIX file system) with the high-performance requirements of HPC workloads, overlooking that FSx for Lustre is specifically optimized for low-latency, parallel access to large datasets, while EFS is designed for general-purpose, throughput-oriented use cases.
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 linked to S3
Amazon FSx for Lustre is a high-performance file system that provides a POSIX-compliant interface and can be linked directly to an S3 bucket, allowing you to run standard bioinformatics tools on genomics data stored in S3 without needing to copy it. This solution delivers the low-latency, high-throughput file access required for complex analytics on petabyte-scale datasets, while seamlessly integrating with S3 for durable storage.
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 EFS mounted on EC2
Why it's wrong here
Amazon EFS is a regional, NFS-based shared file system that can be mounted on multiple EC2 instances, providing standard POSIX file access. However, its architecture is designed for general-purpose, bursty workloads, not the sustained, high-bandwidth parallel I/O of petabyte-scale genomics pipelines. Performance per operation and aggregate throughput fall far short of what Lustre's purpose-built parallel file system provides.
- ✓
Amazon FSx for Lustre linked to S3
Why this is correct
Amazon FSx for Lustre is a fully managed, high-performance parallel file system inspired by Lustre, built to deliver sub-millisecond latencies, millions of IOPS, and hundreds of GB/s of throughput. When linked to Amazon S3, it presents S3 objects as files with POSIX semantics, so standard bioinformatics tools can read/write data without code changes while benefiting from a shared, multi-instance namespace. This combination directly matches the requirements of genomics HPC workloads.
- ✗
Amazon EBS io2 volumes on EC2
Why it's wrong here
Amazon EBS io2 volumes provide block-level storage with high IOPS for a single EC2 instance. Although io2 supports multi-attach on specific instance types, it is not a distributed parallel file system and does not natively integrate with Amazon S3 for transparent data access. A genomics HPC cluster requires a shared, POSIX-compliant file namespace with petabyte-scale throughput, which EBS cannot deliver.
- ✗
Amazon S3 with S3 Select
Why it's wrong here
Amazon S3 Select is a data-retrieval feature that runs SQL expressions against objects (CSV, JSON, Parquet) to return only selected subsets. It does not mount as a file system, does not support POSIX operations, and would require rewriting bioinformatics tools to issue object-store queries rather than file I/O. Thus it cannot serve as the shared high-throughput storage layer for HPC genomics.
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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