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Data Ingestion and TransformationhardMultiple ChoiceObjective-mapped

DEA-C01 Data Ingestion and Transformation Practice Question

A company uses Amazon Kinesis Data Streams to ingest IoT sensor data. The data is processed by an AWS Lambda function that transforms the records and writes to an Amazon S3 bucket. Recently, the Lambda function has been failing with 'Rate exceeded' errors for the S3 PUT API calls. The data volume is 10 MB/s with average record size 2 KB. What should be done to resolve this issue?

⚠ Common exam trap

Many exam-takers confuse Kinesis shard scaling (Option D) or Lambda concurrency (Option C) with S3 rate limits, not realizing that the bottleneck is the S3 API request rate per prefix, not the data ingestion pipeline throughput.

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

Add a random prefix to the S3 object key to distribute writes across multiple prefixes

The 'Rate exceeded' error for S3 PUT API calls indicates that the Lambda function is hitting S3 request rate limits. S3 buckets have a default limit of 3,500 PUT requests per second per prefix. With a data volume of 10 MB/s and an average record size of 2 KB, the Lambda function is generating approximately 5,000 PUT requests per second (10 MB/s ÷ 2 KB), which exceeds the per-prefix limit. Adding a random prefix to the S3 object key distributes writes across multiple prefixes, effectively increasing the aggregate request rate limit to 3,500 PUT requests per second per prefix, thereby resolving the throttling issue.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Add a random prefix to the S3 object key to distribute writes across multiple prefixes

    Why this is correct

    Random prefixes increase the number of S3 partitions, raising the PUT request limit.

  • Switch to Amazon Kinesis Data Firehose to write to S3

    Why it's wrong here

    Switching to Kinesis Data Firehose would indeed consolidate S3 writes, utilising its built-in buffering and batching to reduce PUT API calls and mitigate 'Rate exceeded' errors. This makes it tempting, as Firehose is designed for reliable, scalable delivery of streaming data to destinations like S3, often simplifying data ingestion pipelines. However, the existing Lambda function performs specific data transformations; Firehose's native transformation capabilities might not be sufficient, or it would still require integrating a Lambda function *within* Firehose, shifting the problem rather than directly optimising the *current* Lambda's S3 interaction. The issue is the Lambda's S3 call pattern, not the choice of stream.

  • Increase the Lambda function's reserved concurrency

    Why it's wrong here

    More concurrent Lambda invocations would increase the PUT request rate, making throttling worse.

  • Increase the number of Kinesis shards

    Why it's wrong here

    More shards increase parallelism but don't change the S3 rate limit issue.

Visual reference

Client Recursive Resolver Root DNS (13 root servers) TLD DNS (.com, .org, …) Authoritative example.com query IP addr answer

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-term compliance archive

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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.