SAP-C02 Design for New Solutions Practice Question
A company is designing a new solution to process streaming data from IoT devices. The data must be ingested, processed in real-time, and stored in a data warehouse for analytics. The company expects millions of events per second. Which combination of AWS services should be used?
⚠ Common exam trap
The SAP-C02 exam often tests the distinction between Kinesis Data Streams (real-time, sub-second) and Kinesis Data Firehose (near-real-time, minutes of latency), leading candidates to choose Firehose for real-time 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
✓
Amazon Kinesis Data Streams for ingestion, Amazon Kinesis Data Analytics for real-time processing, and Amazon S3 as a staging area before loading into Amazon Redshift.
Amazon Kinesis Data Streams can ingest millions of events per second with durable, ordered shards, while Kinesis Data Analytics provides real-time SQL or Apache Flink processing on the stream. Amazon S3 acts as a staging layer before loading into Amazon Redshift via COPY or Redshift Spectrum, enabling scalable analytics without throttling the ingestion pipeline.
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 Kinesis Data Firehose for ingestion and delivery to Amazon S3, then use AWS Glue for ETL into Amazon Redshift.
Why it's wrong here
Firehose is for near-real-time delivery, not real-time processing.
- ✗
Amazon DynamoDB Streams for ingestion, AWS Lambda for processing, and Amazon Redshift for storage.
Why it's wrong here
DynamoDB Streams is for table changes, not IoT data ingestion.
- ✗
Amazon SQS for ingestion, AWS Lambda for processing, and Amazon DynamoDB for storage.
Why it's wrong here
SQS is not suitable for high-throughput streaming and Lambda may have concurrency limits.
- ✓
Amazon Kinesis Data Streams for ingestion, Amazon Kinesis Data Analytics for real-time processing, and Amazon S3 as a staging area before loading into Amazon Redshift.
Why this is correct
Kinesis Data Streams handles high throughput, Data Analytics processes in real-time, and S3 integrates with Redshift.
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.