DEA-C01 Data Ingestion and Transformation Practice Question
A company is ingesting streaming data into Kinesis Data Streams. The consumer application experiences high latency due to a single shard bottleneck. What is the most effective way to reduce latency?
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
✓
Increase the number of shards in the data stream.
Increasing the number of shards increases throughput and reduces latency. Waiting for autoscaling is passive, using KCL is for processing, and switching to Firehose changes the architecture.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Increase the number of shards in the data stream.
Why this is correct
More shards increase parallelism and throughput, reducing latency.
- ✗
Wait for automatic scaling to add shards.
Why it's wrong here
Kinesis Data Streams does not auto-scale shards; manual intervention is required.
- ✗
Use the Kinesis Client Library (KCL) to process records.
Why it's wrong here
KCL is already assumed; it doesn't fix the shard count issue.
- ✗
Switch to Amazon Kinesis Data Firehose.
Why it's wrong here
Firehose is for delivering to destinations, not for processing; it doesn't address the shard bottleneck.
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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.