A company has application services that have been containerized and deployed on multiple Amazon EC2 instances with public IPs. An Apache Kafka cluster has been deployed to the EC2 instances. A…

While creating an EC2 Auto Scaling group and RDS read replicas improves scalability, it still requires managing the underlying EC2 instances for containers and the self-managed Kafka cluster, which does not significantly reduce overall operational overhead.

This option has similar drawbacks to A regarding EC2 management and self-managed Kafka. Deploying the DB instance to Multi-AZ primarily provides high availability, not necessarily the read scalability for a significant increase in orders.

Deploying a Kubernetes cluster on EC2 instances introduces significant operational overhead for managing the Kubernetes control plane and worker nodes, directly contradicting the requirement to reduce operational overhead for the entire architecture.

Deploying the containerized application on Amazon EKS with AWS Fargate eliminates the operational overhead of managing EC2 instances for containers, providing auto-scaling capabilities. Migrating the self-managed Apache Kafka cluster to Amazon MSK Serverless further reduces operational overhead by fully managing the Kafka infrastructure and automatically scaling throughput to meet increased demand for orders, ensuring both scalability and reduced management burden.