SAP-C02 Design for New Solutions Practice Question
A company is designing a new system that will ingest and process real-time streaming data from thousands of IoT devices. Each device sends data every second. The data must be processed with low latency (under 1 second) and then stored in Amazon S3 for long-term analytics. The company also needs to be able to reprocess data in case of processing errors. Which solution should the architect recommend?
⚠ Common exam trap
Many exam-takers confuse Kinesis Data Firehose (which has higher latency due to buffering) with Kinesis Data Streams (which offers sub-second latency), leading them to choose Firehose for low-latency requirements.
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 Kinesis Data Streams to ingest data, AWS Lambda to process, and store in S3
Amazon Kinesis Data Streams provides sub-second ingestion latency, which meets the under-1-second processing requirement. AWS Lambda can process each record with low latency and store the results directly in Amazon S3. Kinesis Data Streams also supports data replay for up to 365 days (default 24 hours), enabling reprocessing in case of errors.
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 Kinesis Data Streams to ingest data, AWS Lambda to process, and store in S3
Why this is correct
Kinesis Data Streams provides sub-second ingestion, Lambda can process in real-time, and data retention allows reprocessing.
- ✗
Use Amazon Kinesis Data Firehose to ingest data, transform with Lambda, and store in S3
Why it's wrong here
Firehose has a buffer interval of at least 60 seconds, not sub-second.
- ✗
Use AWS Database Migration Service (DMS) to ingest data into Amazon S3
Why it's wrong here
DMS is for database migration, not real-time streaming ingestion.
- ✗
Use Amazon SQS to buffer data, and an EC2 Auto Scaling group to process and store in S3
Why it's wrong here
SQS is not designed for streaming data; it's for message queues.
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 SAP-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 SAP-C02 exam.