- A
Send the IoT messages to an Amazon SQS queue and have Lambda poll the queue in batches to reduce the number of concurrent invocations.
Why wrong: This still uses Lambda and may face concurrency issues if the batch size is not sufficient. Moreover, SQS polling adds latency and does not solve the fundamental concurrency problem as Lambda still invokes per batch.
- B
Store the raw messages in an S3 bucket and use S3 Select to query the data for anomalies periodically.
Why wrong: S3 Select is for querying objects at rest, not for real-time streaming. Periodic queries cannot achieve the 1-minute latency requirement and are not suitable for real-time anomaly detection.
- C
Ingest the messages into Amazon Kinesis Data Streams with multiple shards, and use a Lambda function to process records from the stream. Increase the Lambda concurrency limit.
This is correct. Kinesis Data Streams can scale to thousands of shards to handle high throughput. Lambda can process records in real-time, and increasing concurrency limits (by requesting a limit increase or using reserved concurrency) addresses the throttling issue. The processed data can be written to S3 via the Lambda function.
- D
Use AWS IoT Core rules to route messages to Amazon Kinesis Data Firehose, which writes raw data to S3. Then use Amazon Kinesis Data Analytics to read from S3 and perform real-time anomaly detection, writing results back to S3 via Firehose.
Why wrong: This is incorrect because Kinesis Data Analytics cannot read from S3 in real-time; it requires a Kinesis data stream as a source. The architecture would not provide real-time processing.
SAP-C02 Design for New Solutions Practice Question
This SAP-C02 practice question tests your understanding of design for new solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 data processing pipeline for real-time analytics. The pipeline ingests data from IoT devices that send JSON messages via MQTT to AWS IoT Core. The messages must be processed in real-time to detect anomalies and the results must be stored in Amazon S3 for later analysis. The company currently uses a Lambda function to process each message, but as the number of devices grows, the Lambda function is being throttled due to concurrency limits. The company needs a solution that scales to handle thousands of devices per second without losing messages. The processed data must be available in S3 within 1 minute of ingestion. Which architecture should the company use?
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
Ingest the messages into Amazon Kinesis Data Streams with multiple shards, and use a Lambda function to process records from the stream. Increase the Lambda concurrency limit.
The correct architecture is to ingest messages into Amazon Kinesis Data Streams with multiple shards to handle high throughput. Using a Lambda function to process records from the stream allows real-time anomaly detection. To address concurrency limits, the Lambda concurrency limit can be increased by requesting a limit increase from AWS Support, and you can use reserved concurrency to ensure processing capacity. This solution scales elastically and can meet the 1-minute latency requirement. Option D is incorrect because Kinesis Data Analytics cannot read directly from S3 or from Kinesis Data Firehose; it requires a Kinesis data stream as its source. The architecture in D would not provide real-time processing as it relies on periodic S3 queries.
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.
- ✗
Send the IoT messages to an Amazon SQS queue and have Lambda poll the queue in batches to reduce the number of concurrent invocations.
Why it's wrong here
This still uses Lambda and may face concurrency issues if the batch size is not sufficient. Moreover, SQS polling adds latency and does not solve the fundamental concurrency problem as Lambda still invokes per batch.
- ✗
Store the raw messages in an S3 bucket and use S3 Select to query the data for anomalies periodically.
Why it's wrong here
S3 Select is for querying objects at rest, not for real-time streaming. Periodic queries cannot achieve the 1-minute latency requirement and are not suitable for real-time anomaly detection.
- ✓
Ingest the messages into Amazon Kinesis Data Streams with multiple shards, and use a Lambda function to process records from the stream. Increase the Lambda concurrency limit.
Why this is correct
This is correct. Kinesis Data Streams can scale to thousands of shards to handle high throughput. Lambda can process records in real-time, and increasing concurrency limits (by requesting a limit increase or using reserved concurrency) addresses the throttling issue. The processed data can be written to S3 via the Lambda function.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use AWS IoT Core rules to route messages to Amazon Kinesis Data Firehose, which writes raw data to S3. Then use Amazon Kinesis Data Analytics to read from S3 and perform real-time anomaly detection, writing results back to S3 via Firehose.
Why it's wrong here
This is incorrect because Kinesis Data Analytics cannot read from S3 in real-time; it requires a Kinesis data stream as a source. The architecture would not provide real-time processing.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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.
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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: Ingest the messages into Amazon Kinesis Data Streams with multiple shards, and use a Lambda function to process records from the stream. Increase the Lambda concurrency limit. — The correct architecture is to ingest messages into Amazon Kinesis Data Streams with multiple shards to handle high throughput. Using a Lambda function to process records from the stream allows real-time anomaly detection. To address concurrency limits, the Lambda concurrency limit can be increased by requesting a limit increase from AWS Support, and you can use reserved concurrency to ensure processing capacity. This solution scales elastically and can meet the 1-minute latency requirement. Option D is incorrect because Kinesis Data Analytics cannot read directly from S3 or from Kinesis Data Firehose; it requires a Kinesis data stream as its source. The architecture in D would not provide real-time processing as it relies on periodic S3 queries.
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.
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Last reviewed: Jun 20, 2026
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