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Difficulty: MediumAWS Compute Services

AWS offers a variety of compute services tailored to different application workloads, scaling requirements, and management preferences. A cloud architect is planning the deployment of four separate application components. Which AWS compute service is the most appropriate choice for each of these business and technical requirements? Match each workload scenario on the left with its most suitable AWS compute service on the right.

  • A development team needs to launch a simple Python application environment with pre-configured virtual private servers, storage, databases, and a static IP under a flat, predictable monthly pricing structure.Amazon Lightsail
  • A financial analysis firm needs to execute thousands of highly parallelized, containerized batch processing jobs that run to completion across dynamically scaled resources.AWS Batch
  • A software company wants to deploy a Node.js microservice that has highly sporadic traffic patterns and needs to scale instantly, ensuring they only pay for active execution time in milliseconds.AWS Lambda
  • An enterprise security team wants to run containerized web services where they specify container CPU and memory requirements, but want AWS to fully manage and patch the underlying host instances.AWS Fargate

Answer

The correct matches pair the simple Python environment with Amazon Lightsail, the highly parallelized batch jobs with AWS Batch, the sporadic Node.js microservice with AWS Lambda, and the serverless container configuration with AWS Fargate.
Matching the workloads to their appropriate compute services is based on matching the management model, cost structure, and technical requirements. Amazon Lightsail is best for simple environments with a flat monthly rate. AWS Batch is optimized for executing large-scale parallel batch jobs to completion. AWS Lambda provides event-driven serverless scaling billed by millisecond execution for sporadic workloads. AWS Fargate provides serverless container compute where container specifications are declared without managing host instances.

Step-by-Step Solution

1
Analyze the workload requirements and key constraints for each scenario, paying attention to terms like 'predictable monthly pricing', 'highly parallelized batch', 'sporadic traffic with millisecond execution', and 'containerized without managing servers'.
Identify that the first scenario requires a simple VPS with flat pricing (Amazon Lightsail), the second requires batch orchestration (AWS Batch), the third requires event-driven micro-billing (AWS Lambda), and the fourth requires serverless containers (AWS Fargate).
This establishes the core pedagogical criteria for matching each requirement to its unique service characteristics.
2
Verify that the selected services align with the AWS Shared Responsibility Model and architectural best practices, ensuring that constraints such as Lambda's execution limits or Fargate's serverless container model match the scenario requirements.
All four scenarios are correctly paired without violating any technical constraints.
Ensures that the cloud architecture choices are valid and correct according to AWS CCP guidelines.

Key Concept

Matching workloads to AWS Compute Services based on operational model, billing, and management overhead.
Estimated Time:1m 30s
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Topics

AWS Compute Services

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