Question 1,670 of 1,786
Data Ingestion and TransformationhardMultiple SelectObjective-mapped

Quick Answer

The answer is to increase the number of shards to 20 and enable enhanced fan-out for the Lambda consumer. Increasing shards from 10 to 20 doubles the stream’s write and read throughput from 5 MB/s to 10 MB/s, directly addressing the Lambda consumer’s processing lag. Enhanced fan-out then provides each consumer—Lambda for the dashboard and Firehose for storage—with its own dedicated 2 MB/s read throughput per shard, eliminating the contention that occurs when multiple consumers share the default 5 transactions per second per shard. On the AWS Certified Data Engineer Associate exam, this scenario tests your understanding of Kinesis shard scaling and consumer performance trade-offs, often trapping candidates who overlook that Lambda’s default polling shares throughput with Firehose. Remember the mnemonic “Double the shards, fan out the load” to recall that scaling shards boosts total capacity while enhanced fan-out isolates consumer performance.

DEA-C01 Data Ingestion and Transformation Practice Question

This DEA-C01 practice question tests your understanding of data ingestion and transformation. 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 runs a real-time analytics platform using Amazon Kinesis Data Streams. The data is consumed by multiple consumers: one for real-time dashboard (using Lambda) and one for long-term storage (using Firehose to S3). The Kinesis stream has 10 shards. Each record is 1 KB, and the total incoming data rate is 5 MB/s. The Lambda consumer is falling behind and processing latency exceeds 10 seconds. Which TWO actions should be taken to resolve the issue?

Question 1hardmulti select
Full question →

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 to 20

Options A and D are correct. Increasing the number of shards to 20 doubles the throughput capacity, allowing Lambda to process more records per second. Using enhanced fan-out eliminates contention between consumers, giving each consumer dedicated read throughput. Option B (increase Lambda memory) may help but limited by shard throughput. Option C (decrease batch size) would increase number of invocations, possibly worsening latency. Option E (use KCL) is already used by Lambda.

Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.

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 Lambda function's memory allocation

    Why it's wrong here

    More memory may speed up processing but the bottleneck is the shard throughput limit.

  • Increase the number of shards to 20

    Why this is correct

    More shards increase the total throughput of the stream, allowing Lambda to process more data in parallel.

    Related concept

    Static NAT maps one inside address to one outside address.

  • Enable enhanced fan-out for the Lambda consumer

    Why this is correct

    Enhanced fan-out provides dedicated read throughput per consumer, eliminating throttling from other consumers.

    Related concept

    Static NAT maps one inside address to one outside address.

  • Switch to using Kinesis Client Library (KCL) instead of Lambda

    Why it's wrong here

    Lambda already uses KCL under the hood; this would not solve the throughput issue.

  • Decrease the batch size in the Lambda event source mapping

    Why it's wrong here

    Smaller batch sizes increase the number of Lambda invocations, adding overhead.

Common exam traps

Common exam trap: NAT rules depend on direction and matching traffic

NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.

Detailed technical explanation

How to think about this question

NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.

KKey Concepts to Remember

  • Static NAT maps one inside address to one outside address.
  • PAT allows many inside hosts to share one public address using ports.
  • Inside local and inside global describe the private and translated addresses.
  • NAT ACLs identify traffic for translation, not always security filtering.

TExam Day Tips

  • Identify inside and outside interfaces first.
  • Check whether the scenario needs static NAT, dynamic NAT or PAT.
  • Do not confuse NAT matching ACLs with normal packet-filtering intent.

Key takeaway

NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.

Real-world example

How this comes up in practice

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

Got this wrong? Here's your next step.

Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.

Related practice questions

Related DEA-C01 practice-question pages

Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.

Practice this exam

Start a free DEA-C01 practice session

Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.

FAQ

Questions learners often ask

What does this DEA-C01 question test?

Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Static NAT maps one inside address to one outside address..

What is the correct answer to this question?

The correct answer is: Increase the number of shards to 20 — Options A and D are correct. Increasing the number of shards to 20 doubles the throughput capacity, allowing Lambda to process more records per second. Using enhanced fan-out eliminates contention between consumers, giving each consumer dedicated read throughput. Option B (increase Lambda memory) may help but limited by shard throughput. Option C (decrease batch size) would increase number of invocations, possibly worsening latency. Option E (use KCL) is already used by Lambda.

What should I do if I get this DEA-C01 question wrong?

Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.

What is the key concept behind this question?

Static NAT maps one inside address to one outside address.

About these practice questions

Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →

How Courseiva writes practice questions · Editorial policy

Same concept, more angles

1 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 real-time analytics application uses Amazon Kinesis Data Streams. The consumer application falls behind, causing increased latency. Which action would MOST effectively improve throughput?

medium
  • A.Reduce the RecordMaxBufferedTime parameter in the Firehose delivery stream.
  • B.Increase the number of shards in the data stream.
  • C.Increase the batch size in the Kinesis Producer Library.
  • D.Use enhanced fan-out to dedicate a shard per consumer.

Why B: Increasing the number of shards in the Kinesis Data Stream directly increases the stream's read capacity (each shard supports up to 2 MB/s read and 5 transactions per second for shared throughput). This allows the consumer application to process more data in parallel, reducing the backlog and latency. The question specifies a consumer application falling behind, which is a read-throughput bottleneck, and scaling shards is the most effective way to address it.

Last reviewed: Jun 20, 2026

Question Discussion

Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.

Loading comments…

Sign in to join the discussion.

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.