DVA-C02 Development with AWS Services Practice Question
A developer is designing a system that ingests high-volume data from IoT devices. The data must be processed in near real-time and then stored in Amazon S3 for analytics. Which TWO AWS services should the developer use together to meet these requirements? (Choose TWO.)
⚠ Common exam trap
Watch out — candidates often confuse Amazon SQS or SNS as suitable for real-time streaming, but they lack the ordered, replayable, and parallel-consumer capabilities that Kinesis Data Streams provides for high-volume IoT ingestion.
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 Kinesis Data Streams
Amazon Kinesis Data Streams is designed for real-time ingestion of large data streams, such as IoT telemetry, and can capture and store data in shards for up to 365 days. AWS Lambda can be configured as a consumer of the Kinesis stream to process records in near real-time and then write the results to Amazon S3 for analytics. Together, they provide a serverless, scalable pipeline for high-volume IoT data.
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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Amazon SQS
Why it's wrong here
Amazon SQS is a message queuing service that decouples microservices, distributed systems, and serverless applications. While SQS can handle a significant number of messages, it is optimized for individual message delivery and asynchronous processing, not for the continuous, ordered, and high-throughput ingestion and processing of streaming data. It doesn't provide the stream-like capabilities, such as multiple consumers reading from the same point or replaying data, that are essential for real-time analytics on high-volume streams.
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Amazon SNS
Why it's wrong here
Amazon SNS is primarily a publish/subscribe messaging service designed for sending notifications to various endpoints, such as email, SMS, or other AWS services. While it can handle a high volume of messages, its core purpose is message fan-out and decoupling, not continuous, ordered ingestion of raw streaming data for processing. It lacks the features for persistent storage, re-processing, or ordered delivery typical of streaming data platforms.
- ✓
Amazon Kinesis Data Streams
Why this is correct
Amazon Kinesis Data Streams is a fully managed, scalable service specifically designed for ingesting and processing large streams of data records in real time. It provides durable storage for up to 7 days, allowing multiple consumers to process the same data concurrently and independently. This makes it ideal for applications requiring real-time analytics, log aggregation, and continuous data ingestion from various sources at high throughput.
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Amazon EC2
Why it's wrong here
Amazon EC2 provides virtual servers in the cloud, offering complete control over the computing environment. While it's possible to build a custom streaming ingestion system on EC2 instances, this approach requires significant operational overhead for provisioning, scaling, patching, and managing the underlying infrastructure. It is not a serverless solution for data ingestion and lacks the inherent scalability and managed features of dedicated streaming services like Kinesis.
- ✓
AWS Lambda
Why this is correct
AWS Lambda is a serverless compute service that allows running code without provisioning or managing servers. It can be directly configured as a consumer for Amazon Kinesis Data Streams, automatically invoking a function whenever new data records are available in the stream. This integration enables near real-time processing of high-volume streaming data with automatic scaling and pay-per-execution billing, making it a highly efficient and cost-effective solution for stream processing.
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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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.