SAA-C03 Design High-Performing Architectures Practice Question
Multiple EC2 instances in different Availability Zones need concurrent read/write access to the same shared files. The files are actively modified by several application servers, and low-latency metadata operations matter more than extremely high aggregate throughput. Which two changes should the team make? Select two.
⚠ Common exam trap
Candidates often confuse EBS Multi-Attach with a cross-AZ shared storage solution, but Multi-Attach is strictly limited to a single AZ and a small number of instances, while EFS is the only AWS shared file system that natively spans AZs with concurrent read/write access.
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
✓
Use Amazon EFS instead of EBS or S3 for the shared file system.
Amazon EFS provides a fully managed, POSIX-compliant, shared file system that can be mounted concurrently by multiple EC2 instances across different Availability Zones (AZs). It supports concurrent read/write access with strong consistency, and its metadata operations are optimized for low latency, making it ideal for workloads where many application servers actively modify the same files. EBS cannot be shared across AZs, and S3 lacks POSIX semantics and low-latency metadata operations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use Amazon EFS instead of EBS or S3 for the shared file system.
Why this is correct
Amazon EFS is the managed AWS file service built for shared POSIX-style file access from multiple instances. It supports concurrent read/write access from many EC2 hosts and is a better fit than EBS, which is attached to a single instance, or S3, which provides object storage rather than a native shared filesystem. For an application that expects standard filesystem semantics, EFS is the correct storage layer.
- ✓
Create EFS mount targets in every Availability Zone that hosts application instances.
Why this is correct
Mount targets in each active Availability Zone provide local network entry points to the file system for instances in that AZ. This improves availability and avoids unnecessary cross-AZ traffic for file access. In a multi-AZ application, placing mount targets wherever the workload runs is the standard design for efficient and resilient EFS connectivity.
- ✗
Use a single EBS Multi-Attach volume mounted read/write by all instances across AZs.
Why it's wrong here
EBS Multi-Attach is not a general-purpose multi-AZ shared filesystem for application servers. It has service limitations and is not the correct service for many instances requiring concurrent shared file access across AZs. EFS is the AWS-managed option designed for this use case.
- ✗
Store the files in S3 and mount them directly through the console as a shared network filesystem.
Why it's wrong here
S3 is object storage, not a native shared filesystem with standard POSIX semantics. It does not provide the same low-latency metadata behavior or filesystem-level concurrent read/write model that application servers expect. This option does not satisfy the workload requirements.
- ✗
Place the files on instance store volumes so each server has faster local access.
Why it's wrong here
Instance store is local to a single EC2 instance and is ephemeral. That means each server would have its own isolated copy of the data, which breaks the requirement for a shared filesystem across multiple instances. It also risks data loss if an instance stops or terminates.
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 |
Go deeper
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