Amazon Web Services Updated SAA-C03 Exam Questions and Answers by kobie

The question focuses on minimizing costs while serving static content to users in the US and Europe.

Option A uses a single S3 bucket and configures CloudFront to limit edge locations, reducing costs by using fewer edge locations while still improving performance.

Option B maximizes edge locations, which increases costs unnecessarily.

Options C and D involve storing data in multiple regions, which increases storage and operational costs.Thus, Option A is the most cost-effective solution.

A. VPC peering: Creates a fully meshed architecture, which is complex to manage for multiple VPCs.

B. Transit gateway: Simplifies network management by connecting multiple VPCs and on-premises networks via a central hub.

C. PrivateLink: Restricts communication to the application endpoint but may not allow full VPC connectivity.

D. ALB with internet exposure: Not secure or specific to private network communication.

References: AWS Transit Gateway

This solution is the most suitable for running cron jobs on AWS with minimal refactoring, while also supporting the possibility of running jobs in response to future events.

Container Image for Cron Jobs: By containerizing the cron jobs, you can package the environment and dependencies required to run the jobs, ensuring consistency and ease of deployment across different environments.

Amazon EventBridge Scheduler: EventBridge Scheduler allows you to create a recurring schedule that can trigger tasks (like running your cron jobs) at specific times or intervals. It provides fine-grained control over scheduling and integrates seamlessly with AWS services.

AWS Fargate: Fargate is a serverless compute engine for containers that removes the need to manage EC2 instances. It allows you to run containers without worrying about the underlying infrastructure. Fargate is ideal for running jobs that can vary in duration, like cron jobs, as it scales automatically based on the task's requirements.

Why Not Other Options?:

Option A (Lambda): While AWS Lambda could handle short-running cron jobs, it has limitations in terms of execution duration (maximum of 15 minutes) and might not be suitable for jobs that run up to 20 minutes.

Option B (AWS Batch on ECS): AWS Batch is more suitable for batch processing and workloads that require complex job dependencies or orchestration, which might be more than what is needed for simple cron jobs.

Option D (Step Functions with Wait State): While Step Functions provide orchestration capabilities, this approach would introduce unnecessary complexity and overhead compared to the straightforward scheduling with EventBridge and running on Fargate.

AWS References:

Amazon EventBridge Scheduler - Details on how to schedule tasks using Amazon EventBridge Scheduler.

AWS Fargate - Information on how to run containers in a serverless manner using AWS Fargate.

In Amazon Aurora, a custom endpoint is a feature that allows you to create a load-balanced endpoint that directs traffic to a specific set of instances in your Aurora DB cluster. This is particularly useful when you want to route traffic to a subset of instances that have different configurations or when you want to isolate specific workloads (e.g., reporting queries) to certain instances.

Custom Endpoint: The correct solution is to create a custom endpoint that includes the three Aurora Replicas that the department wants to use for near-real-time reporting. This custom endpoint will distribute the reporting queries only across the three selected replicas with the specified compute and memory configurations, ensuring that these queries do not affect the rest of the DB cluster.

Other Options:

Option B (Create a three-node cluster clone): This would create a separate cluster with its own resources, but it is not necessary and could incur additional costs. Also, it doesn't leverage the existing replicas.

Option C (Use any of the instance endpoints): This would involve manually managing connections to individual instances, which is not scalable or automatic.

Option D (Use the reader endpoint): The reader endpoint would distribute the read queries across all replicas in the cluster, not just the selected three. This would not meet the requirement to limit the reporting queries to only three specific replicas.

AWS References:

Amazon Aurora Endpoints - Provides detailed information on the different types of endpoints available in Aurora, including custom endpoints.

Custom Endpoints in Amazon Aurora - Specific documentation on how to create and use custom endpoints to direct traffic to selected instances in an Aurora cluster.