- A
Use Amazon Kinesis Data Streams to ingest data, use Kinesis Data Firehose to deliver data to S3, and use Athena for queries.
Why wrong: Firehose delivers data in batches (60 secs), not real-time processing; Athena is for ad-hoc queries.
- B
Use Amazon Kinesis Data Streams to ingest data, trigger a Lambda function for processing, and store results in DynamoDB.
Why wrong: Lambda can process from Kinesis but may not handle high throughput efficiently; also no filtering/aggregation built-in.
- C
Use Amazon SQS to ingest sensor data, trigger a Lambda function for processing, and store results in DynamoDB.
Why wrong: SQS is not designed for real-time streaming ingestion; it's a message queue.
- D
Use AWS IoT Core to ingest data, use IoT rules to route data to Kinesis Data Analytics for real-time processing, and store results in S3.
IoT Core is designed for IoT; Kinesis Data Analytics provides real-time SQL processing; S3 is cost-effective storage.
Real-time IoT Data Processing with AWS IoT Core and Kinesis Data Analytics | AWS Solutions Architect Professional Explained
This SAP-C02 practice question tests your understanding of design for new solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is designing a new application on AWS that processes real-time IoT sensor data from thousands of devices. The data must be ingested, processed, and stored for analysis. The company wants to use a serverless architecture to reduce operational overhead. The processing includes filtering, aggregation, and transformation. Which solution should a Solutions Architect recommend?
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 AWS IoT Core to ingest data, use IoT rules to route data to Kinesis Data Analytics for real-time processing, and store results in S3.
Option D is correct because AWS IoT Core is purpose-built for ingesting data from IoT devices, its rules engine can route data to Kinesis Data Analytics for real-time processing using SQL, and results can be stored in S3 for analysis. Option A is incorrect because Kinesis Data Firehose delivers data in batches, not real-time processing as required. Option B is incorrect because while Lambda can process, it may have concurrency limits and is less optimal for high-throughput streaming compared to Kinesis Data Analytics. Option C is incorrect because SQS is not designed for real-time streaming ingestion from IoT devices; it's a message queue, not a streaming service.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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, use Kinesis Data Firehose to deliver data to S3, and use Athena for queries.
Why it's wrong here
Firehose delivers data in batches (60 secs), not real-time processing; Athena is for ad-hoc queries.
- ✗
Use Amazon Kinesis Data Streams to ingest data, trigger a Lambda function for processing, and store results in DynamoDB.
Why it's wrong here
Lambda can process from Kinesis but may not handle high throughput efficiently; also no filtering/aggregation built-in.
- ✗
Use Amazon SQS to ingest sensor data, trigger a Lambda function for processing, and store results in DynamoDB.
Why it's wrong here
SQS is not designed for real-time streaming ingestion; it's a message queue.
- ✓
Use AWS IoT Core to ingest data, use IoT rules to route data to Kinesis Data Analytics for real-time processing, and store results in S3.
Why this is correct
IoT Core is designed for IoT; Kinesis Data Analytics provides real-time SQL processing; S3 is cost-effective storage.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 |
What to study next
Got this wrong? Here's your next step.
Identify which SAP-C02 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this SAP-C02 question test?
Design for New Solutions — This question tests Design for New Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use AWS IoT Core to ingest data, use IoT rules to route data to Kinesis Data Analytics for real-time processing, and store results in S3. — Option D is correct because AWS IoT Core is purpose-built for ingesting data from IoT devices, its rules engine can route data to Kinesis Data Analytics for real-time processing using SQL, and results can be stored in S3 for analysis. Option A is incorrect because Kinesis Data Firehose delivers data in batches, not real-time processing as required. Option B is incorrect because while Lambda can process, it may have concurrency limits and is less optimal for high-throughput streaming compared to Kinesis Data Analytics. Option C is incorrect because SQS is not designed for real-time streaming ingestion from IoT devices; it's a message queue, not a streaming service.
What should I do if I get this SAP-C02 question wrong?
Identify which SAP-C02 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more ways this is tested on SAP-C02
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company is designing a new application that will process real-time streaming data from thousands of IoT devices. The data must be ingested, processed with low latency, and stored in Amazon S3 for analytics. Which combination of AWS services should the company use to meet these requirements?
medium- A.Amazon SQS, AWS Lambda, Amazon S3
- B.Amazon Kinesis Data Firehose, Amazon Redshift, Amazon S3
- C.Amazon MQ, AWS Lambda, Amazon RDS
- ✓ D.Amazon Kinesis Data Streams, AWS Lambda, Amazon S3
Why D: Amazon Kinesis Data Streams ingests real-time streaming data from thousands of IoT devices with low latency, and AWS Lambda can process each record as it arrives via event source mapping. The processed data is then stored in Amazon S3 for analytics, meeting all requirements for ingestion, low-latency processing, and durable storage.
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Last reviewed: Jun 20, 2026
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