DVA-C02 Development with AWS Services Practice Question
A company has a web application running on Amazon ECS with Fargate launch type. The application needs to store and retrieve user session data. The sessions are small and require very low latency access. The development team wants a fully managed solution. Which storage options meet these requirements? (Choose TWO.)
⚠ Common exam trap
Many exam-takers choose Amazon S3 for its simplicity and low cost, overlooking its higher latency and lack of support for low-latency session storage, or they mistakenly think EFS can be mounted directly to Fargate tasks without understanding the integration limitations.
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 DynamoDB
Amazon DynamoDB is correct because it is a fully managed NoSQL key-value database that provides single-digit millisecond latency for read and write operations, making it ideal for storing small session data with low latency requirements. It scales automatically and requires no server management, aligning with the fully managed requirement and the Fargate launch type's serverless nature.
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 DynamoDB
Why this is correct
Amazon DynamoDB is a fully managed, serverless NoSQL database service that provides consistent single-digit millisecond latency at any scale. Its key-value data model is highly efficient for storing and retrieving session data, which typically involves simple lookups by session ID. DynamoDB's automatic scaling, high availability, and built-in Time-To-Live (TTL) functionality make it an excellent choice for dynamic web application workloads requiring persistent, low-latency session state without operational overhead.
- ✗
Amazon S3
Why it's wrong here
Amazon S3 is an object storage service primarily designed for durable, highly available storage of static files and large objects, not for low-latency, real-time key-value lookups required by session management. While highly scalable, its typical latency for individual object retrieval is in the tens to hundreds of milliseconds, which is too high for interactive user sessions. Furthermore, S3 lacks built-in features for efficient session expiration or concurrent access patterns common in session stores.
- ✗
Amazon EFS
Why it's wrong here
Amazon EFS is a scalable, elastic NFS file system designed for shared file access across multiple EC2 instances or containers. While it provides persistent storage, its POSIX file system semantics and network file system overhead introduce higher latency compared to dedicated key-value stores, making it inefficient for rapid session data lookups. EFS is optimized for file-based workloads, not for the high-throughput, low-latency, non-hierarchical data access patterns characteristic of web application session management.
- ✓
Amazon ElastiCache for Redis
Why this is correct
Amazon ElastiCache for Redis is an in-memory data store that delivers sub-millisecond latency, making it exceptionally fast for session management. Redis's native support for data structures like strings and hashes, along with Time-To-Live (TTL) functionality, perfectly aligns with the requirements for storing and automatically expiring session data. Its high throughput and ability to handle millions of operations per second are crucial for high-traffic web applications needing a highly responsive session store.
- ✗
Amazon RDS for PostgreSQL
Why it's wrong here
Amazon RDS for PostgreSQL is a managed relational database service designed for complex transactional workloads requiring ACID compliance and structured data. While robust, using a relational database for simple key-value session data introduces unnecessary overhead due to schema management, SQL parsing, and disk-based operations, resulting in higher latency compared to NoSQL or in-memory solutions. Its design is not optimized for the extremely high read/write throughput of simple, ephemeral session data, making it an inefficient and more costly choice.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
Go deeper
Related to this question
About these practice questions
One of 1,135 original DVA-C02 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DVA-C02 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 DVA-C02 exam.