DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer needs to ingest streaming data from thousands of IoT devices into AWS for real-time processing. The data volume peaks at 5 GB/min. Which AWS service should be used as the ingestion endpoint?
⚠ Common exam trap
Many exam-takers confuse AWS Glue's streaming ETL capability (which reads from a stream but does not ingest) with a direct ingestion endpoint, or they assume S3's high durability makes it suitable for real-time ingestion, ignoring its lack of streaming semantics and low-latency write guarantees.
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
Amazon Kinesis Data Streams is designed for real-time data ingestion at scale, supporting throughput of up to 1 MB/s or 1,000 records/s per shard. With a peak of 5 GB/min (~83 MB/s), you can horizontally scale by adding shards to meet the required throughput, making it the ideal ingestion endpoint for high-volume streaming IoT data.
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 Streams
Why this is correct
Kinesis Data Streams ingests high-throughput streaming records with per-shard capacity that scales to thousands of producers, and delivers sub-second latency for real-time processing. It satisfies the 5 GB/min peak by adding shards, unlike S3 transfer or batch-oriented endpoints.
- ✗
AWS Glue
Why it's wrong here
AWS Glue is a serverless ETL and catalogue service that runs batch or micro-batch jobs; it cannot serve as a persistent endpoint absorbing thousands of concurrent device connections at 5 GB/min. It is tempting because Glue does transform streaming data, but that is downstream processing, not ingestion.
- ✗
Amazon S3
Why it's wrong here
Amazon S3 is object storage accessed via PUT and GET APIs, so it lacks the persistent connection handling and per-record delivery that thousands of IoT devices streaming continuously require. It is tempting because S3 is a common landing zone, but it is a destination for delivered data, not a real-time ingestion endpoint.
- ✗
AWS Lambda
Why it's wrong here
AWS Lambda is an event-driven compute service invoked per request with a 15-minute maximum runtime; it cannot hold open connections from thousands of IoT devices or buffer 5 GB/min. It is tempting because Lambda can process ingested records, but that is consumption, not the ingestion endpoint itself.
Go deeper
Related to this question
About these practice questions
This DEA-C01 question is part of Courseiva's 1,321-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
Same concept, more angles
2 more ways this is tested on DEA-C01
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 data engineer needs to ingest streaming data from a social media API into Amazon S3 for batch analytics. The data arrives at a rate of 500 records per second. Which service should be used to capture the stream?
easy- A.Amazon Simple Notification Service (SNS)
- B.Amazon Simple Queue Service (SQS)
- ✓ C.Amazon Kinesis Data Streams
- D.Amazon MQ
Why C: Amazon Kinesis Data Streams is designed for real-time streaming data ingestion at scale, supporting throughput of up to 1 MB/s or 1,000 records per second per shard. With 500 records per second, Kinesis can reliably capture and store the social media API data for up to 365 days, enabling batch analytics via S3 delivery through Kinesis Firehose or custom consumers.
Variation 2. A data engineer needs to ingest streaming data from thousands of IoT devices and immediately process each record with minimal latency. Which AWS service should be used as the ingestion point?
easy- A.AWS Lambda
- B.Amazon S3
- ✓ C.Amazon Kinesis Data Streams
- D.AWS Glue
Why C: Amazon Kinesis Data Streams is designed as a massively scalable, low-latency ingestion service for streaming data, capable of handling thousands of producers (IoT devices) and delivering records to consumers within milliseconds. It durably stores data in shards for up to 365 days and integrates natively with Lambda, Kinesis Data Analytics, and Firehose for immediate processing. This makes it the canonical ingestion point for real-time IoT pipelines on AWS.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 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 DEA-C01 exam.