- A
Disable retries on the Lambda function and configure a dead-letter queue for failed records.
Why wrong: Disabling retries would lose data; dead-letter queue handles failures but does not prevent throttling.
- B
Replace Kinesis Data Streams with Amazon DynamoDB Streams for ingestion.
Why wrong: DynamoDB Streams is for database changes, not IoT ingestion, and does not solve the throttling issue.
- C
Reduce the batch size and increase the number of shards in the Kinesis stream to increase parallelism.
Reducing batch size lowers records per invocation, and more shards increase parallelism, reducing throttling.
- D
Increase the batch size in the Lambda event source mapping to reduce the number of invocations.
Why wrong: Increasing batch size increases the number of records per invocation, likely causing more throttling.
Lambda Throttling from Kinesis API: Batch Size and Shards Solution
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 data engineering team is ingesting streaming data from IoT devices into Amazon Kinesis Data Streams. The data is then consumed by an AWS Lambda function that transforms and loads it into Amazon S3. Recently, the team noticed that the Lambda function is failing with throttling errors (HTTP 429) from the Kinesis API. Which configuration change should the team make to resolve this issue?
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
Reduce the batch size and increase the number of shards in the Kinesis stream to increase parallelism.
Option C is correct because reducing the batch size and increasing the number of shards directly addresses the HTTP 429 throttling errors from the Kinesis API. Each shard supports up to 5 read transactions per second and a maximum read rate of 2 MB/s; by increasing shards, you increase the available read throughput, and reducing the batch size lowers the number of records per invocation, preventing the Lambda function from exceeding the per-shard read limits.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Disable retries on the Lambda function and configure a dead-letter queue for failed records.
Why it's wrong here
Disabling retries would lose data; dead-letter queue handles failures but does not prevent throttling.
- ✗
Replace Kinesis Data Streams with Amazon DynamoDB Streams for ingestion.
Why it's wrong here
DynamoDB Streams is for database changes, not IoT ingestion, and does not solve the throttling issue.
- ✓
Reduce the batch size and increase the number of shards in the Kinesis stream to increase parallelism.
Why this is correct
Reducing batch size lowers records per invocation, and more shards increase parallelism, reducing throttling.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the batch size in the Lambda event source mapping to reduce the number of invocations.
Why it's wrong here
Increasing batch size increases the number of records per invocation, likely causing more throttling.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume increasing the batch size reduces invocations and thus throttling, but in reality, larger batches increase the data volume per GetRecords call, making throttling worse; the correct approach is to reduce batch size and increase shards to distribute the read load.
Detailed technical explanation
How to think about this question
Under the hood, Kinesis Data Streams enforces per-shard limits: each shard supports up to 5 GetRecords calls per second, each returning up to 10 MB of data. When a Lambda event source mapping polls the stream, it uses GetRecords; if the batch size is too large or the number of shards too low, the Lambda function can exceed these limits, triggering HTTP 429 responses. In real-world scenarios, IoT data spikes can cause sudden increases in record volume, making it critical to monitor the IteratorAgeMilliseconds metric and adjust shard count dynamically using auto-scaling or manual intervention.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Visual reference
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 |
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
Data Ingestion and Transformation — study guide chapter
Learn the concepts, then practise the questions
- →
Data Ingestion and Transformation practice questions
Targeted practice on this topic area only
- →
All DEA-C01 questions
1,786 questions across all exam domains
- →
AWS Certified Data Engineer Associate DEA-C01 study guide
Full concept coverage aligned to exam objectives
- →
DEA-C01 practice test guide
How to use practice tests most effectively before exam day
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.
Data Ingestion and Transformation practice questions
Practise DEA-C01 questions linked to Data Ingestion and Transformation.
Data Operations and Support practice questions
Practise DEA-C01 questions linked to Data Operations and Support.
Data Security and Governance practice questions
Practise DEA-C01 questions linked to Data Security and Governance.
Data Store Management practice questions
Practise DEA-C01 questions linked to Data Store Management.
DEA-C01 fundamentals practice questions
Practise DEA-C01 questions linked to DEA-C01 fundamentals.
DEA-C01 scenario practice questions
Practise DEA-C01 questions linked to DEA-C01 scenario.
DEA-C01 troubleshooting practice questions
Practise DEA-C01 questions linked to DEA-C01 troubleshooting.
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 — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Reduce the batch size and increase the number of shards in the Kinesis stream to increase parallelism. — Option C is correct because reducing the batch size and increasing the number of shards directly addresses the HTTP 429 throttling errors from the Kinesis API. Each shard supports up to 5 read transactions per second and a maximum read rate of 2 MB/s; by increasing shards, you increase the available read throughput, and reducing the batch size lowers the number of records per invocation, preventing the Lambda function from exceeding the per-shard read limits.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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 →
Keep practising
More DEA-C01 practice questions
- A data pipeline uses Kinesis Data Firehose to deliver streaming data to an S3 bucket. The data volume spikes occasionall…
- An e-commerce company uses AWS Glue to run ETL jobs that transform clickstream data from Amazon S3. The job reads Parque…
- A data engineering team uses Amazon Kinesis Data Analytics for Apache Flink to process streaming data. They notice that…
- A company uses AWS Glue to process streaming data from Amazon Kinesis Data Streams. The job reads JSON records and write…
- A data engineer applies the above bucket policy to an S3 bucket containing sensitive data. The goal is to allow only enc…
- A company uses AWS Glue to catalog data in Amazon S3. The security team requires that all sensitive data be identified a…
Last reviewed: Jul 4, 2026
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.
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.
Sign in to join the discussion.