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Data Ingestion and TransformationmediumMultiple ChoiceObjective-mapped

DEA-C01 Data Ingestion and Transformation Practice Question

Network Topology
aws kinesis describe-streamstream-name my-streamRefer to the exhibit."StreamDescription": {"StreamName": "my-stream","StreamARN": "arn:aws:kinesis:us-east-1:123456789012:stream/my-stream","StreamStatus": "ACTIVE","Shards": ["ShardId": "shardId-000000000000","HashKeyRange": {"StartingHashKey": "0","EndingHashKey": "113427455640312821154458202477256070485"},"SequenceNumberRange": {"StartingSequenceNumber": "49640292012345678901234567890123456789012345678901234567890""ShardId": "shardId-000000000001","StartingHashKey": "113427455640312821154458202477256070485","EndingHashKey": "226854911280625642308916404954512140970""StartingSequenceNumber": "49640292012345678901234567890123456789012345678901234567891"],"EnhancedMonitoring": [],"EncryptionType": "KMS","KeyId": "arn:aws:kms:us-east-1:123456789012:key/1234abcd-12ab-34cd-56ef-1234567890ab","RetentionPeriodHours": 24,"ShardCount": 2

Refer to the exhibit. A data engineer is troubleshooting a Kinesis Data Streams consumer that is falling behind. The stream has 2 shards and is receiving data at a rate of 2 MB/s. The consumer is an AWS Lambda function with a batch size of 100 records. What should the engineer do to improve consumer throughput?

⚠ Common exam trap

The DEA-C01 exam often tests the misconception that Lambda memory or batch size adjustments are the primary levers for throughput, when in fact the shard count directly controls the parallelism and read capacity of a Kinesis stream consumer.

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 stream to 4

Increasing the number of shards to 4 doubles the stream's total ingestion capacity to 4 MB/s, which directly increases the number of concurrent Lambda invocations and thus consumer throughput. With 2 shards, each shard can support up to 1 MB/s input and 2 MB/s output, so the current 2 MB/s load is at the shard-level output limit, causing the consumer to fall behind.

Answer analysis

Option-by-option breakdown

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

  • Decrease the Lambda batch size to 10 records

    Why it's wrong here

    Smaller batch size reduces efficiency and throughput.

  • Increase the retention period of the stream to 168 hours

    Why it's wrong here

    Does not affect throughput.

  • Increase the number of shards in the stream to 4

    Why this is correct

    More shards increase parallelism and throughput for both producers and consumers.

  • Increase the memory allocation of the Lambda function

    Why it's wrong here

    May help if CPU-bound, but not the primary bottleneck for a 2-shard stream.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

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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.