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Question 148 - MLS-C01 discussion

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A Machine Learning Specialist is developing a daily ETL workflow containing multiple ETL jobs The workflow consists of the following processes

* Start the workflow as soon as data is uploaded to Amazon S3

* When all the datasets are available in Amazon S3, start an ETL job to join the uploaded datasets with multiple terabyte-sized datasets already stored in Amazon S3

* Store the results of joining datasets in Amazon S3

* If one of the jobs fails, send a notification to the Administrator

Which configuration will meet these requirements?

A.
Use AWS Lambda to trigger an AWS Step Functions workflow to wait for dataset uploads to complete in Amazon S3. Use AWS Glue to join the datasets Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure
Answers
A.
Use AWS Lambda to trigger an AWS Step Functions workflow to wait for dataset uploads to complete in Amazon S3. Use AWS Glue to join the datasets Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure
B.
Develop the ETL workflow using AWS Lambda to start an Amazon SageMaker notebook instance Use a lifecycle configuration script to join the datasets and persist the results in Amazon S3 Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure
Answers
B.
Develop the ETL workflow using AWS Lambda to start an Amazon SageMaker notebook instance Use a lifecycle configuration script to join the datasets and persist the results in Amazon S3 Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure
C.
Develop the ETL workflow using AWS Batch to trigger the start of ETL jobs when data is uploaded to Amazon S3 Use AWS Glue to join the datasets in Amazon S3 Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure
Answers
C.
Develop the ETL workflow using AWS Batch to trigger the start of ETL jobs when data is uploaded to Amazon S3 Use AWS Glue to join the datasets in Amazon S3 Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure
D.
Use AWS Lambda to chain other Lambda functions to read and join the datasets in Amazon S3 as soon as the data is uploaded to Amazon S3 Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure
Answers
D.
Use AWS Lambda to chain other Lambda functions to read and join the datasets in Amazon S3 as soon as the data is uploaded to Amazon S3 Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure
Suggested answer: A

Explanation:

To develop a daily ETL workflow containing multiple ETL jobs that can start as soon as data is uploaded to Amazon S3, the best configuration is to use AWS Lambda to trigger an AWS Step Functions workflow to wait for dataset uploads to complete in Amazon S3. Use AWS Glue to join the datasets. Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure.

AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. You can use Lambda to create functions that respond to events such as data uploads to Amazon S3. You can also use Lambda to invoke other AWS services such as AWS Step Functions and AWS Glue.

AWS Step Functions is a service that lets you coordinate multiple AWS services into serverless workflows. You can use Step Functions to create a state machine that defines the sequence and logic of your ETL workflow. You can also use Step Functions to handle errors and retries, and to monitor the execution status of your workflow.

AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics. You can use Glue to create and run ETL jobs that can join data from multiple sources in Amazon S3. You can also use Glue to catalog your data and make it searchable and queryable.

Amazon CloudWatch is a service that monitors your AWS resources and applications. You can use CloudWatch to create alarms that trigger actions when a metric or a log event meets a specified threshold. You can also use CloudWatch to send notifications to Amazon Simple Notification Service (SNS) topics, which can then deliver the notifications to subscribers such as email addresses or phone numbers.

Therefore, by using these services together, you can achieve the following benefits:

You can start the ETL workflow as soon as data is uploaded to Amazon S3 by using Lambda functions to trigger Step Functions workflows.

You can wait for all the datasets to be available in Amazon S3 by using Step Functions to poll the S3 buckets and check the data completeness.

You can join the datasets with terabyte-sized datasets in Amazon S3 by using Glue ETL jobs that can scale and parallelize the data processing.

You can store the results of joining datasets in Amazon S3 by using Glue ETL jobs to write the output to S3 buckets.

You can send a notification to the Administrator if one of the jobs fails by using CloudWatch alarms to monitor the Step Functions or Glue metrics and send SNS notifications in case of a failure.

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asked 16/09/2024
Balvant Variya
37 questions
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