AWS Certified Machine Learning Specialty · Free Practice Question Medium
Question 19
A financial services company aims to automate the analysis of daily transaction costs, execution reporting, and market performance. The company has developed its own Big Data tools for this purpose. These tools require efficient scheduling and dynamic configuration of computing resources to manage variable workloads and data volumes. Considering the need for a scalable, flexible solution that minimizes operational overhead, which AWS service should be leveraged to configure the resources dynamically and schedule the data analytic workloads?
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A
Deploy Amazon Simple Workflow Service (SWF) to orchestrate the data analytics workflows, manually configuring EC2 instances for resource allocation based on anticipated workloads.
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B
Use AWS Batch to schedule jobs and dynamically provision resources, leveraging its integration with other AWS services for end-to-end data processing workflows.
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C
Utilize Amazon SQS to queue data processing tasks, managing resource allocation and scheduling through manual scaling and application logic.
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D
Implement AWS Step Functions to coordinate multiple AWS services into serverless workflows for data processing, using AWS Lambda for dynamic resource allocation.
Reveal correct answer
Correct answer: B
Explanation
Selecting the correct AWS service for automating data analytics workflows requires understanding the capabilities of each service in terms of job scheduling, resource management, and integration with big data tools.
Correct Choice: Use AWS Batch to schedule jobs and dynamically provision resources, leveraging its integration with other AWS services for end-to-end data processing workflows.
AWS Batch is specifically designed for batch processing jobs. It simplifies job scheduling and automatically manages the computing infrastructure, scaling up or down as needed without requiring manual intervention. This makes it ideal for the company’s need to dynamically configure resources based on the variable demands of their Big Data tools.
Incorrect Choice: Implement AWS Step Functions to coordinate multiple AWS services into serverless workflows for data processing, using AWS Lambda for dynamic resource allocation.
AWS Step Functions is a service designed for coordinating complex workflows across AWS services. While it offers robust options for workflow management, it does not inherently provide the same level of resource management and job scheduling specificity for batch processing tasks as AWS Batch.
Incorrect Choice: Utilize Amazon SQS to queue data processing tasks, managing resource allocation and scheduling through manual scaling and application logic.
Amazon SQS is a message queuing service, which can decouple and scale microservices, distributed systems, and serverless applications. However, it doesn't directly address the need for scheduling data analytics workloads or dynamically provisioning computing resources.
Incorrect Choice: Deploy Amazon Simple Workflow Service (SWF) to orchestrate the data analytics workflows, manually configuring EC2 instances for resource allocation based on anticipated workloads.
Amazon Simple Workflow Service (SWF) allows for the orchestration of workflow tasks, including in the context of data analytics. However, like AWS Step Functions, it requires more manual management of resources and does not offer the automatic scaling and simplified job scheduling capabilities of AWS Batch for batch processing needs.
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