Amazon Web Services SAA-C03 Exam With Confidence Using Practice Dumps

Because the workload follows apredictable business-hours schedule, the lowest-overhead solution is to usescheduled scalingwith EC2 Auto Scaling. AWS documentation states that scheduled actions let you scale an Auto Scaling group at specific times or on recurring schedules by changing desired, minimum, and maximum capacity. That directly matches a workload that needs instances during business hours and not at night. Manual start and stop actions add operational work, Spot Instances risk interruptions during business hours, and sizing for maximum load with Reserved Instances would overpay for idle time. Scheduled scaling automates the exact time-based pattern the question describes.

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The requirements emphasize high availability across multiple Availability Zones, automatic recovery, and least operational overhead. The simplest way to achieve this for containerized microservices is to use a fully managed container orchestration service with serverless compute. Amazon ECS with the Fargate launch type provides exactly that.

With ECS Fargate, AWS manages the underlying compute infrastructure (no EC2 instances to provision, patch, scale, or secure at the OS level). You define task definitions and services, and ECS schedules tasks across Availability Zones based on your networking configuration (multiple subnets in different AZs). If a container fails, ECS service scheduling automatically replaces it, fulfilling the “recover from failures” requirement. Fargate also integrates with load balancing, CloudWatch logging, and scaling policies, reducing the operational burden of keeping the platform healthy.

Option A (ECS on EC2) is still managed orchestration, but it requires managing the EC2 capacity layer: AMI updates, instance patching, cluster capacity planning, and instance scaling. Option B (EKS with self-managed nodes) typically carries even more operational responsibility because you manage node groups, upgrades, and Kubernetes operational complexity in addition to the underlying instances. Option D is the highest operational overhead because it lacks managed scheduling and self-healing; you would need to build and maintain your own process manager and failover mechanisms.

Therefore, C is the best answer because it provides a managed, multi-AZ capable, self-healing container platform with minimal infrastructure management—matching the operational efficiency goal while maintaining high availability.

AWS Step Functions supports long-running workflows and error retries, making it ideal for a job composed of many tasks. Integration with EventBridge allows automatic triggering from S3 events. This setup is resilient and supports up to 1-year execution duration.