SAP-C02 Design for New Solutions Practice Question
A company is building a real-time analytics platform that ingests data from thousands of IoT devices. The data must be processed in near real-time and stored in a data lake on Amazon S3 for long-term analysis. The company also needs to run complex SQL queries on the streaming data to detect anomalies. The solution must be highly available and scale automatically. Which combination of AWS services should a solutions architect recommend?
⚠ Common exam trap
The trap here is assuming that any processing service like AWS Glue or Lambda can handle real-time streaming SQL, but Glue is batch-oriented and Lambda lacks built-in SQL capabilities.
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, Amazon Kinesis Data Analytics for SQL processing, and Amazon Kinesis Data Firehose to deliver to Amazon S3.
AWS IoT Core handles IoT device ingestion at scale. Kinesis Data Analytics for SQL enables real-time SQL queries on streaming data for anomaly detection. Kinesis Data Firehose reliably delivers the processed data to S3. This combination is fully managed, scales automatically, and meets the near real-time and storage requirements.
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 AWS IoT Core to ingest data, AWS Lambda to process each record, and Amazon S3 to store the data directly.
Why it's wrong here
Lambda can process records but does not support complex SQL queries on streams. It also has a maximum execution timeout of 15 minutes, which may be insufficient for some analytics. Storing directly to S3 without a delivery stream may miss buffering and compression benefits. This approach lacks the SQL processing requirement.
- ✗
Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to ingest data, Amazon Kinesis Data Analytics for SQL processing, and AWS Lambda to write to Amazon S3.
Why it's wrong here
Amazon MSK can ingest data but requires more operational overhead than AWS IoT Core for IoT devices. Using Lambda to write to S3 from Kinesis Data Analytics is possible but less efficient than Kinesis Data Firehose, which is purpose-built for delivery. This solution adds complexity and may not be as cost-effective or simple.
- ✗
Use Amazon Kinesis Data Streams to ingest data, AWS Glue for SQL processing, and Amazon Kinesis Data Firehose to deliver to Amazon S3.
Why it's wrong here
AWS Glue is a batch-oriented ETL service, not designed for real-time SQL queries on streaming data. It would introduce latency and not meet the near real-time requirement. Kinesis Data Streams and Firehose are suitable for ingestion and delivery, but Glue is the wrong choice for streaming SQL analytics.
- ✓
Use AWS IoT Core to ingest data, Amazon Kinesis Data Analytics for SQL processing, and Amazon Kinesis Data Firehose to deliver to Amazon S3.
Why this is correct
AWS IoT Core ingests device data reliably. Kinesis Data Analytics for SQL allows running continuous SQL queries on streaming data to detect anomalies. Kinesis Data Firehose delivers the processed data to S3. This combination is fully managed, scales automatically, and provides near real-time processing and storage.
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 and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.