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 that will process streaming data from IoT devices. The data must be processed in real time and then stored in Amazon S3 for long-term analytics. Which combination of AWS services should be used?
Amazon Kinesis Data Firehose, Amazon Redshift
Why wrong: Firehose can deliver to S3 but Redshift is for analytics, not storage.
Amazon SQS, AWS Lambda, Amazon RDS
Why wrong: SQS is not for real-time streaming; RDS is not for analytics.
AWS IoT Core, Amazon DynamoDB
Why wrong: DynamoDB is not for long-term analytics storage.
Amazon Kinesis Data Streams, AWS Lambda, Amazon S3
Real-time ingestion, processing, and storage.
Answer choices
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, AWS Lambda, Amazon S3
Option D is correct because Amazon Kinesis Data Streams ingests and buffers streaming IoT data in real time, AWS Lambda processes each record as it arrives, and the processed data is written directly to Amazon S3 for durable long-term analytics. This combination provides the low-latency, serverless pipeline required for real-time processing and S3-based storage.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Amazon Kinesis Data Firehose, Amazon Redshift
Why it's wrong here
Firehose can deliver to S3 but Redshift is for analytics, not storage.
Amazon SQS, AWS Lambda, Amazon RDS
Why it's wrong here
SQS is not for real-time streaming; RDS is not for analytics.
AWS IoT Core, Amazon DynamoDB
Why it's wrong here
DynamoDB is not for long-term analytics storage.
Amazon Kinesis Data Streams, AWS Lambda, Amazon S3
Why this is correct
Real-time ingestion, processing, and storage.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates often confuse Kinesis Data Firehose (which delivers near-real-time batches) with Kinesis Data Streams (which enables per-record real-time processing), leading them to pick Option A despite its lack of a real-time processing component.
Detailed technical explanation
Kinesis Data Streams uses shards to scale ingestion, each providing a 1 MB/s or 1,000 records/s write capacity, and Lambda functions poll these shards via event source mappings with a batch window of up to 5 minutes. The processed records can be written to S3 using the AWS SDK, leveraging S3's 11 9s durability and lifecycle policies for cost-effective long-term storage. In a real-world scenario, IoT devices emitting sensor data at 500 messages per second would require multiple shards and a Lambda concurrency limit to avoid throttling.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
What to study next
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FAQ
Design for New Solutions — This question tests Design for New Solutions — Read the scenario before looking for a memorised answer..
The correct answer is: Amazon Kinesis Data Streams, AWS Lambda, Amazon S3 — Option D is correct because Amazon Kinesis Data Streams ingests and buffers streaming IoT data in real time, AWS Lambda processes each record as it arrives, and the processed data is written directly to Amazon S3 for durable long-term analytics. This combination provides the low-latency, serverless pipeline required for real-time processing and S3-based storage.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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.
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