Question

Difficulty: MediumAWS Compute Services

An IT consultancy is planning the migration of several distinct client applications to AWS. To optimize costs and operational efficiency, they must pair each workload with the correct compute service. How should the following workload scenarios be matched to their most appropriate AWS compute services?

  • A developer needs to host a simple, low-cost personal portfolio website with a pre-configured LAMP stack and predictable monthly pricing.Amazon Lightsail
  • A system administrator needs to run a legacy enterprise software application that requires full control over the underlying operating system and administrative access to configure custom kernel modules.Amazon Elastic Compute Cloud (Amazon EC2)
  • A software engineer wants to run a serverless, event-driven background job that automatically processes image uploads to an Amazon S3 bucket within milliseconds, with no infrastructure management.AWS Lambda
  • A DevOps team needs to run containerized microservices where AWS manages the underlying server provisioning, cluster scaling, and server maintenance.AWS Fargate

Answer

The portfolio website matches Amazon Lightsail; the legacy application requiring kernel control matches Amazon Elastic Compute Cloud (Amazon EC2); the event-driven image processing job matches AWS Lambda; and the containerized microservices requiring serverless management match AWS Fargate.
The correct matches map each business workload to the compute service that aligns with its administration requirements and scaling parameters. Amazon Lightsail is correct for the LAMP site because it bundles compute, storage, and networking into a simple package with predictable pricing. Amazon EC2 is correct for the legacy application because it provides full host and operating system administrative control. AWS Lambda is correct for the S3-triggered event processing because it runs short-lived functions in response to event triggers without provisioning servers. AWS Fargate is correct for containerized microservices because it is a serverless container host that eliminates server management.

Step-by-Step Solution

1
Analyze the workload requirements for each scenario, noting key constraints such as operating system control, serverless scaling, pre-configured environments, and pricing predictability.
Identified key requirements: predictable pricing/LAMP for scenario 1, OS/kernel control for scenario 2, serverless/event-driven trigger for scenario 3, and serverless container management for scenario 4.
Matching AWS compute services depends on mapping specific workload characteristics to the capabilities and management models of each service.
2
Evaluate Amazon Lightsail against the portfolio website scenario.
Amazon Lightsail is selected because it offers pre-configured stacks (like LAMP) and predictable pricing structures.
Lightsail provides all-in-one virtual private servers tailored for simple projects with fixed monthly plans.
3
Evaluate Amazon EC2 against the legacy software scenario.
Amazon Elastic Compute Cloud (Amazon EC2) is selected because the customer requires full root access and OS/kernel customization.
EC2 is an Infrastructure-as-a-Service (IaaS) offering that grants complete administrative control over virtual machines.
4
Evaluate AWS Lambda against the image processing scenario.
AWS Lambda is selected because the execution is short-lived, event-driven (triggered by Amazon S3 uploads), and serverless.
Lambda is the primary serverless function service for running code in response to S3 events without managing container images or servers.
5
Evaluate AWS Fargate against the containerized microservices scenario.
AWS Fargate is selected because it allows running containers (ECS/EKS) without managing or provisioning underlying EC2 instances.
Fargate is a serverless compute engine specifically designed for running containerized workloads.

Key Concept

Selecting appropriate AWS compute services based on operational control, cost structure, serverless capabilities, and container orchestration requirements.
Estimated Time:2m 0s
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