Exam AWS Certified DevOps Engineer - Professional DOP-C02 topic 1 question 243 discussion

Exam question from Amazon's AWS Certified DevOps Engineer - Professional DOP-C02

Question #: 243
Topic #: 1

[All AWS Certified DevOps Engineer - Professional DOP-C02 Questions]

A company's application has an API that retrieves workload metrics. The company needs to audit, analyze, and visualize these metrics from the application to detect issues at scale.

Which combination of steps will meet these requirements? (Choose three.)

A. Configure an Amazon EventBridge schedule to invoke an AWS Lambda function that calls the API to retrieve workload metrics. Store the workload metric data in an Amazon S3 bucket.
B. Configure an Amazon EventBridge schedule to invoke an AWS Lambda function that calls the API to retrieve workload metrics. Store the workload metric data in an Amazon DynamoDB table that has a DynamoDB stream enabled.
C. Create an AWS Glue crawler to catalog the workload metric data in the Amazon S3 bucket. Create views in Amazon Athena for the cataloged data.
D. Connect an AWS Glue crawler to the Amazon DynamoDB stream to catalog the workload metric data. Create views in Amazon Athena for the cataloged data.
E. Create Amazon QuickSight datasets from the Amazon Athena views. Create a QuickSight analysis to visualize the workload metric data as a dashboard.
F. Create an Amazon CloudWatch dashboard that has custom widgets that invoke AWS Lambda functions. Configure the Lambda functions to query the workload metrics data from the Amazon Athena views.

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Suggested Answer: ACE 🗳️

by xdkonorek2 at July 5, 2024, 6:31 p.m.

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jamesf

11 months ago

Selected Answer: ACE

Option A: Using Amazon EventBridge to schedule an AWS Lambda function that retrieves workload metrics from the API and stores the data in Amazon S3 provides a scalable and automated way to collect and store the data. Option C: AWS Glue can be used to catalog the data stored in Amazon S3, making it queryable using Amazon Athena. This step prepares the data for analysis by creating a schema and making it available for querying. Option E: Amazon QuickSight can be used to create datasets from the Athena views and then visualize the data in dashboards. This provides the capability to analyze and visualize workload metrics at scale. https://aws.amazon.com/blogs/mt/analyzing-amazon-cloudwatch-internet-monitor-measurement-logs-using-amazon-athena-amazon-quicksight/

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jamesf

11 months ago

Additional Note: Not Option B: Storing workload metric data in an Amazon DynamoDB table with DynamoDB Streams enabled is an option, but it’s not ideal for large-scale metrics and querying. DynamoDB is better suited for high-speed key-value access and doesn’t provide the same level of querying capabilities for large datasets compared to Amazon S3 with Athena. DynamoDB Streams captures a time-ordered sequence of item-level modifications in any DynamoDB table and stores this information in a log for up to 24 hours. Applications can access this log and view the data items as they appeared before and after they were modified, in near-real time.

upvoted 1 times

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