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A media company hosts its video processing workload on AWS. The workload uses Amazon EC2 instances in an Auto Scaling group to handle varying levels of demand. The workload stores the original videos and the processed videos in an Amazon S3 bucket.
The company wants to ensure that the video processing workload is scalable. The company wants to prevent failed processing attempts because of resource constraints. The architecturemust be able to handle sudden spikes in video uploads without impacting the processing capability.
Which solution will meet these requirements with the LEAST overhead?
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C
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Explanation
This solution addresses the scalability needs of the workload while preventing failed processing attempts due to resource constraints. Amazon S3 event notificationscan be used to trigger a message to an SQS queue whenever a new video is uploaded. The existing Auto Scaling group of EC2 instances can poll the SQS queue, ensuring that the EC2 instances only process videos when there is a job in the queue. SQS decouplesthe video upload and processing steps, allowing the system to handle sudden spikes in video uploads without overloading EC2 instances. The use ofAuto Scalingensures that the EC2 instances can scale in or out based on the demand, maintaining cost efficiency while avoiding processing failures due to insufficient resources. AWS References: S3 Event Notificationsdetails how to configure notifications for S3 events. Amazon SQSis a fully managed message queuing service that decouples components of the system. Auto Scaling EC2explains how to manage automatic scaling of EC2 instances based on demand. Why the other options are incorrect: A. AWS Lambda functions: While Lambda can handle some workloads, video processing is often resource-intensive and long-running, making EC2 a more suitable solution. B. Using SNS with Lambda: Similar to A, Lambda is not ideal for large-scale video processing due to its time and memory limitations. D. AWS Step Functions: While a valid orchestration solution, this introduces more complexity and overhead compared to the simpler SQS-based solution. |
A company is developing a photo-hosting application in the us-east-1 Region. The application gives users across multiple countries the ability to upload and view photos. Some photos are heavily viewed for months, while other photos are viewed for less than a week. The application allows users to upload photos that are up to 20 MB in size. The application uses photo metadata to determine which photos to display to each user.
The company needs a cost-effective storage solution to support the application.
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B
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Explanation
Amazon S3 Intelligent-Tiering automatically moves objects between frequent and infrequent access tiers based on access patterns, which minimizes cost without performance impact. Storing photo metadata in Amazon DynamoDB provides fast and scalable lookup by user or tag. From AWS Documentation: “The S3 Intelligent-Tiering storage class automatically optimizes storage costs by moving data between frequent and infrequent access tiers when access patterns change.” (Source: Amazon S3 User Guide – Intelligent-Tiering) Why B is correct: S3 Intelligent-Tiering optimizes storage automatically for cost without lifecycle management overhead. DynamoDB stores small metadata items and S3 URLs, enabling efficient queries and photo lookups. This architecture scales globally, integrates seamlessly with applications, and minimizes operational cost. Why other options are incorrect: A & D: DynamoDB is not intended for storing binary objects like images. C: Lifecycle rules are static and don’t adapt dynamically to unpredictable access patterns. [References:, Amazon S3 User Guide – “Storage Classes and Intelligent-Tiering”, AWS Well-Architected Framework – Cost Optimization Pillar, AWS Developer Guide – “Building Serverless Image Hosting with S3 and DynamoDB”, , , ]
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A company runs an on-premises application on a Kubernetes cluster. The company recently added millions of new customers. The company's existing on-premises infrastructure is unable to handle the large number of new customers. The company needs to migrate the on-premises application to the AWS Cloud.
The company will migrate to an Amazon Elastic Kubernetes Service (Amazon EKS) cluster. The company does not want to manage the underlying compute infrastructure for the new architecture on AWS.
Which solution will meet these requirements with the LEAST operational overhead?
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C
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Explanation
AWS Fargate is a serverless compute engine for containers that works with Amazon EKS. With Fargate, you do not need to provision or manage EC2 instances or clusters. You simply define and deploy your pods, and Fargate automatically launches the required compute resources. This results in the lowest operational overhead because AWS manages the infrastructure. Fargate profiles allow you to specify which pods run on Fargate. AWS Documentation Extract: “AWS Fargate is a serverless, pay-as-you-go compute engine that lets you focus on building applications without managing servers. With Amazon EKS and Fargate, you only need to define your application’s pods; Fargate provisions and manages the required compute resources for you.” (Source: Amazon EKS documentation, AWS Fargate integration) Other options: A: Self-managed nodes require you to manage EC2 instances. B: Managed node groups reduce some overhead, but you are still responsible for patching and managing the EC2 instances. D: Managed node groups with Karpenter automate scaling but do not remove the need to manage underlying instances. [Reference: AWS Certified Solutions Architect – Official Study Guide, EKS and Fargate Section., , ]
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Find answers to the most common questions about the Amazon Web Services SAA-C03 exam, including what it is, how to prepare, and how it can boost your career.
The Amazon Web Services SAA-C03 certification is a globally-acknowledged credential that is awarded to candidates who pass this certification exam by obtaining the required passing score. This credential attests and validates the candidates' knowledge and hands-on skills in domains covered in the Amazon Web Services SAA-C03 certification syllabus. The Amazon Web Services SAA-C03 certified professionals with their verified proficiency and expertise are trusted and welcomed by hiring managers all over the world to perform leading roles in organizations. The success in Amazon Web Services SAA-C03 certification exam can be ensured only with a combination of clear knowledge on all exam domains and securing the required practical training. Like any other credential, Amazon Web Services SAA-C03 certification may require periodic renewal to stay current with new innovations in the concerned domains.