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Continuous Improvement for Existing SolutionshardMultiple ChoiceObjective-mapped

SAP-C02 Continuous Improvement for Existing Solutions Practice Question

A media company runs a video processing pipeline on AWS. Videos are uploaded to an S3 bucket (input-bucket), which triggers an AWS Lambda function that starts an AWS Glue job. The Glue job processes the video metadata and stores results in a DynamoDB table. Then, a second Lambda function triggers an Amazon ECS Fargate task to transcode the video into multiple formats. The transcoded videos are stored in another S3 bucket (output-bucket). Recently, the company started receiving complaints about delays in video availability. The operations team notices that CloudWatch Logs show no errors, but the ECS tasks often take longer than expected. They also see that the DynamoDB table has a high number of throttled write events. The video upload rate has increased by 50% in the last month. The team needs to improve the pipeline's performance and reduce delays. What should they do?

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

Enable DynamoDB auto scaling on the table with a target utilization of 70%.

The primary bottleneck is DynamoDB throttling due to increased write load. Enabling DynamoDB auto scaling (Option A) dynamically adjusts read/write capacity to match demand, reducing throttling and delays. Option B (increasing Lambda timeout) does not address DynamoDB throttling. Option C (SQS queue) improves decoupling but does not directly solve the DynamoDB issue. Option D (reserved concurrency) limits Lambda concurrency, which could reduce load on DynamoDB but also slows down processing and is not the best solution.

Answer analysis

Option-by-option breakdown

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

  • Enable DynamoDB auto scaling on the table with a target utilization of 70%.

    Why this is correct

    Auto scaling will dynamically adjust write capacity to handle increased traffic, reducing throttling.

  • Increase the Lambda function timeout for both functions to 15 minutes.

    Why it's wrong here

    Increasing timeout does not address the DynamoDB throttling issue.

  • Introduce an Amazon SQS queue between the second Lambda and ECS to buffer requests.

    Why it's wrong here

    SQS helps decouple but the immediate bottleneck is DynamoDB writes.

  • Set reserved concurrency on the first Lambda function to 10 to control throttling.

    Why it's wrong here

    Reserved concurrency may limit processing and worsen delays.

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

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