SAP-C02 - Accelerate Workload Migration and Modernization (20% of the exam) - Section 4.4

Identify opportunities to modernise by decoupling components and moving to serverless compute with AWS Lambda and containers with Amazon ECS, Amazon EKS and AWS Fargate.

Identify modernisation opportunities in monolithic workloads by decomposing tightly coupled components and migrating stateless logic to AWS Lambda or containerised services on Amazon EKS and AWS Fargate. Recognise when decoupling via event-driven integration reduces operational burden compared to running self-managed container infrastructure.

AWS LambdaAmazon EKSAWS FargateDecoupling

Practice question for this objective

Free sampleAccelerate Workload Migration and Modernizationhard

An insurer is rehosting a batch-processing application that already ships as a Docker image and runs as long-lived background workers reading jobs from a queue. Management wants the workers in AWS without buying, patching, or right-sizing any container host fleet, while keeping per-task CPU and memory isolation and paying only for the resources each running task consumes. The workload is steady but unpredictable in volume, and the platform team has no appetite for managing EC2 capacity. Which compute platform MOST cost-effectively and efficiently meets these requirements?

  • ARun the containers on an Amazon ECS cluster backed by an EC2 capacity provider, sizing an Auto Scaling group of container instances and patching the host operating system so the cluster can place the worker tasks.
  • BConvert the worker logic into AWS Lambda functions triggered by the queue, repackaging the container so each job runs as a short-lived invocation within the Lambda execution timeout instead of a long-lived process.
  • CDeploy the containers to a self-managed Kubernetes cluster on EC2 so the platform team controls scheduling and networking in detail, scaling worker nodes manually as the queue depth rises and falls over time.
  • DRun the existing container image as Amazon ECS tasks on AWS Fargate, letting Fargate provision isolated task capacity on demand so the team manages no host fleet and pays only for the vCPU and memory each task uses. Correct
Select AWS Fargate to run existing containers as ECS tasks when the goal is serverless, per-task billing with no host fleet to manage. Containerised long-lived workers that must run with per-task isolation and no host management map onto ECS on Fargate, which provisions serverless task capacity and bills per task, whereas ECS on EC2 keeps host toil, Lambda misfits long-running jobs, and self-managed Kubernetes adds cluster operations.

Why A is wrong: ECS on EC2 places the tasks correctly, but it leaves the team owning host capacity planning, patching, and right-sizing, which is exactly the undifferentiated work management asked to avoid in this rehost.

Why B is wrong: Lambda is serverless, but its bounded execution duration and event-driven model do not suit long-lived background workers and would force re-architecting the batch processes, exceeding the scope of a container rehost.

Why C is wrong: Self-managed Kubernetes on EC2 maximises control but adds substantial cluster and node operations, contradicting the explicit requirement to avoid managing host capacity and patching for this workload.

Why D is correct: Fargate runs the unchanged container image as ECS tasks with per-task CPU and memory isolation, provisions capacity serverlessly, and bills only for resources each task consumes, removing all host management for these queue workers.

See more SAP-C02 practice questions, answers explained.

Exam traps in Accelerate Workload Migration and Modernization

Answers that look right on this material and are not. Each one is a distractor from a different question in the SAP-C02 bank for this domain.

  • Run the stateless unpredictable API on ECS with an Amazon EC2 Auto Scaling group of On-Demand instances, so the team controls the host kernel and pays a predictable rate for the instances backing the service during demand swings.

    Why it is wrong: An On-Demand EC2 capacity provider is tempting for control, but it forces the team to provision, patch and right-size hosts and pay for idle instances, contradicting the API team's explicit no-host-management requirement.

  • Run the services on Amazon EKS with a managed node group, letting AWS handle node provisioning and rolling AMI updates while the team applies the in-place kernel and operating-system security patches required by the compliance rule on a recurring schedule.

    Why it is wrong: Managed node groups simplify provisioning but the nodes are still EC2 instances the team owns, so operating-system patching remains their responsibility, which the compliance rule expressly forbids despite the Kubernetes compatibility being fine.

  • Move the entire service to the AWS Fargate launch type so capacity scales automatically with the settlement bursts, and replicate the specialised network driver behaviour by selecting a higher Fargate platform version that exposes additional kernel networking features to the task.

    Why it is wrong: Fargate abstracts away the host, so the team loses the kernel-level control the network driver needs, and Fargate platform versions do not expose custom kernel modules, so this breaks the firm's hard requirement to keep host control.

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