Amazon Redshift Serverless for Infrequent Analytics
A data engineer uses Amazon Redshift to run resource-intensive analytics processes once every month. Every month, the data engineer creates a new Redshift provisioned cluster. The data engineer deletes the Redshift provisioned cluster after the analytics processes are complete every month. Before the data engineer deletes the cluster each month, the data engineer unloads backup data from the cluster to an Amazon S3 bucket. The data engineer needs a solution to run the monthly analytics processes that does not require the data engineer to manage the infrastructure manually. Which solution will meet these requirements with the LEAST operational overhead?
Community Votes
100% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
The core trap is confusing 'serverless' (fully managed, no cluster management) with 'automation' (using CLI or CloudFormation to manage clusters). The key phrase 'does not require... manage the infrastructure manually' points directly to serverless options.
This question evaluates the use of Amazon Redshift Serverless to eliminate manual infrastructure management for intermittent workloads. The correct solution leverages a fully managed service that scales automatically with minimal operational overhead.
Many learners might choose AWS CloudFormation or Step Functions because they automate the *creation* and *deletion* of resources. However, managing these stacks/states still requires operational oversight, whereas Redshift Serverless removes the need to manage the compute layer entirely.
Community Discussion (6 comments)
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Expert Analysis
Why the Answer Is Correct
Amazon Redshift Serverless is a fully managed option that automatically provisions and manages computing resources based on the workload size. Since the requirement specifies running resource-intensive processes once a month without managing infrastructure, Redshift Serverless is ideal because it eliminates the need to provision, scale, or terminate clusters manually. It charges only for the data processing units (DPUs) consumed during execution, making it cost-effective for infrequent usage.Why the Other Options Are Wrong
Options A, C, and D all involve managing underlying infrastructure or automation frameworks. Using Step Functions (A) to pause/resume provisioned clusters still requires managing the cluster lifecycle and configuration. Using AWS CLI (C) or CloudFormation (D) automates the creation/deletion process but still requires the engineer to maintain the templates/scripts and handle any failures in the provisioning logic. These options do not meet the 'least operational overhead' criterion compared to a truly serverless experience.Community Comment Notes
The community consensus strongly supports Option B. As Christina666 noted, 'Fully Managed, Serverless: Redshift Serverless eliminates the need to manually create, manage, or delete clusters.' Felix_G highlighted that other options 'still involve manual tasks like administering CloudFormation stacks,' reinforcing that serverless is the only path to zero cluster management.Exam Strategy
When you see 'least operational overhead' combined with 'manage infrastructure manually', look for Serverless or Fully Managed services first. Automation tools (CLI, Terraform, CloudFormation) reduce effort but do not eliminate the responsibility of managing the underlying resources.
Frequently Asked Questions
Why isn't CloudFormation the best choice for least overhead?
CloudFormation automates deployment but you still manage the stack, errors, and updates. Redshift Serverless removes the compute management entirely.
Is Redshift Serverless cost-effective for monthly jobs?
Yes, it uses a pay-per-use model for DPUs, so you only pay when the job runs, avoiding costs for idle provisioned clusters.
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