Exam AWS Certified Solutions Architect - Associate SAA-C03 topic 1 question 8 discussion

A - incorrect: Schedule scaling policy doesn't make sense. C, D - incorrect: Primary server should not be in same Auto Scaling group with compute nodes. B is correct.

The answer seems to be B for me: A: doesn't make sense to schedule auto-scaling C: Not sure how CloudTrail would be helpful in this case, at all. D: EventBridge is not really used for this purpose, wouldn't be very reliable

keywords resilient and scalability application B is the correct answer since we need sqs designed as a destination to consume jobs from mutiple compute notes and use auto scaling group based on the size of the queue A: is not considerd to be a correct answer since if we use scheduled scaling its not optimize in this use case if suddenly the workload unpredictable C: cloudtrail is used for monitoring actions in aws not use for managing the workload D:

Decouple with Amazon SQS and EC2 instances can be managed in an auto scaling group for scalability https://docs.aws.amazon.com/prescriptive-guidance/latest/modernization-mainframe-decoupling-patterns/queue.html

B doesn't make sense to me because you're scaling based on the queue size and not the requirements of the varying workloads. Eventbridge can act as a trigger for workloads, so it might just cut, although it wouldn't be my first choice.

1.Amazon SQS for Decoupling: Amazon SQS provides a fully managed message queue to decouple the primary server from the compute nodes. Jobs are sent to the queue, and compute nodes process them independently. This architecture eliminates a single point of failure (the primary server) and increases resilience. 2.Auto Scaling Group for Compute Nodes: EC2 instances managed in an Auto Scaling group process the jobs in the SQS queue. Auto Scaling dynamically adjusts the number of instances based on the queue size, ensuring scalability to handle variable workloads. 3.Scalability Based on Queue Size: Scaling based on the size of the SQS queue ensures that the system adjusts to workload demands efficiently. When the queue grows, more instances are launched; when the queue shrinks, instances are terminated.

keywords: - Legacy platform consists of a primary server that coordinates jobs across multiple compute nodes. - Maximizes resiliency and scalability. A: Incorrect - the question don't mention about schedule for high workload. So we don't use scheduled scaling for this case. B: Correct - SQS can keep your message in the queue in case of high workload and if it too high we can increase the EC2 instance base on size of the queue. C: Incorrect - AWS CloudTrail is API logs it is use for audit log of AWS user activity. D: Incorrect - Event Bridge is use for filter event and trigger event.

B. Explanation: To maximize resiliency and scalability, the best solution is to use an Amazon SQS queue as a destination for the jobs. This decouples the primary server from the compute nodes, allowing them to scale independently. This also helps to prevent job loss in the event of a failure. Using an Auto Scaling group of Amazon EC2 instances for the compute nodes allows for automatic scaling based on the workload. In this case, it's recommended to configure the Auto Scaling group based on the size of the Amazon SQS queue, which is a better indicator of the actual workload than the load on the primary server or compute nodes. This approach ensures that the application can handle variable workloads, while also minimizing costs by automatically scaling up or down the compute nodes as needed.

SQS helps to process messages in case of variable workloads. The compute nodes must be implemented using EC2 instances (or alternatively, ECS tasks or managed Kubernetes nodes, but this option is not available). AutoScaling must be based on the workload, which is controlled by the queue. So, the correct option is B. A is not correct because the instances should not scale based on a schedule which is not deterministic. On the contrary, scales based on the workload (queue size) is more effective. AWS CloudTrail should not be used as a destination job and it is not related to the question. The same applies to EventBridge.

B: Explanation: Amazon SQS provides a reliable, highly scalable, and fully managed message queuing service that enables you to decouple and coordinate the components of a distributed application. EC2 Auto Scaling allows you to automatically adjust the number of EC2 instances based on demand, ensuring that your application can handle variable workloads efficiently. Auto Scaling based on the size of the queue ensures that your application scales out when there are many jobs to process and scales in when the job load decreases, providing cost efficiency and responsiveness to workload changes.

A lot of answer B's... but I'm not convinced its Ans B which states: “Configure EC2 Auto Scaling based on the size of the queue” – because basing scaling on the size of the queue ignores the specific workload each job requires. The problem states “The application serves variable workloads” – you can’t determine the processing required for a variable workload based solely on queue size; this can only be done when you scope the size of the specific variable load – and that to my mind points to answer D: “Configure EC2 Auto Scaling based on the load on the compute nodes” – but then I run into the (potential) problem that Eventbridge may not be up to the task…

why are almost all of the "correct answers" I see on this site all wrong? how the fuck is this an educational resource? good thing the community voting system exists or else this side would be pure unadulterated putrid shit.

B for sure

B for sure

option D leverages serverless services (EventBridge) and Auto Scaling for a modern, scalable, and resilient architecture suitable for the distributed application with varying workloads.

In option C, Ignore the line that's talking about cloud trail and then the answer would make much more sense.

B for sure