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Most Recent Amazon SAA-C03 Exam Dumps
Prepare for the Amazon AWS Certified Solutions Architect - Associate exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.
QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Amazon SAA-C03 exam and achieve success.
The questions for SAA-C03 were last updated on Feb 22, 2025.
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A company hosts a website on Amazon EC2 instances behind an Application Load Balancer (ALB) The website serves static content Website traffic is increasing and the company is concerned about a potential increase in cost.
What should a solutions architect do to reduce the cost of the website?
Amazon CloudFront is a content delivery network (CDN) that can improve the performance and reduce the cost of serving static content from a website. CloudFront can cache static files at edge locations closer to the users, reducing the latency and data transfer costs. CloudFront can also integrate with Amazon S3 as the origin for the static content, eliminating the need for EC2 instances to host the website. CloudFront meets all the requirements of the question, while the other options do not. Reference:
https://aws.amazon.com/blogs/architecture/architecting-a-low-cost-web-content-publishing-system/
https://nodeployfriday.com/posts/static-website-hosting/
https://aws.amazon.com/cloudfront/
A company stores data in Amazon S3. According to regulations, the data must not contain personally identifiable information (Pll). The company recently discovered that S3 buckets have some objects that contain Pll. The company needs to automatically detect Pll in S3 buckets and to notify the company's security team.
Which solution will meet these requirements?
A company wants to migrate an application to AWS. The company wants to increase the application's current availability The company wants to use AWS WAF in the application's architecture.
Which solution will meet these requirements?
Understanding the Requirement: The company wants to migrate an application to AWS, increase its availability, and use AWS WAF in the architecture.
Analysis of Options:
Auto Scaling group with ALB and WAF: This option provides high availability by distributing instances across multiple Availability Zones. The ALB ensures even traffic distribution, and AWS WAF provides security at the application layer.
Cluster placement group with ALB and WAF: Cluster placement groups are for low-latency networking within a single AZ, which does not provide the high availability across AZs.
Two EC2 instances with ALB and WAF: This setup provides some availability but does not scale automatically, missing the benefits of an Auto Scaling group.
Auto Scaling group with WAF directly: AWS WAF cannot be directly connected to an Auto Scaling group; it needs to be attached to an ALB, CloudFront distribution, or API Gateway.
Best Solution:
Auto Scaling group with ALB and WAF: This configuration ensures high availability, scalability, and security, meeting all the requirements effectively.
A company is developing an application that will run on a production Amazon Elastic Kubernetes Service (Amazon EKS) cluster The EKS cluster has managed node groups that are provisioned with On-Demand Instances.
The company needs a dedicated EKS cluster for development work. The company will use the development cluster infrequently to test the resiliency of the application. The EKS cluster must manage all the nodes.
Which solution will meet these requirements MOST cost-effectively?
Spot Instances are EC2 instances that are available at up to a 90% discount compared to On-Demand prices. Spot Instances are suitable for stateless, fault-tolerant, and flexible workloads that can tolerate interruptions. Spot Instances can be reclaimed by EC2 when the demand for On-Demand capacity increases, but they provide a two-minute warning before termination. EKS managed node groups automate the provisioning and lifecycle management of nodes for EKS clusters. Managed node groups can use Spot Instances to reduce costs and scale the cluster based on demand. Managed node groups also support features such as Capacity Rebalancing and Capacity Optimized allocation strategy to improve the availability and resilience of Spot Instances. This solution will meet the requirements most cost-effectively, as it leverages the lowest-priced EC2 capacity and does not require any manual intervention.
1 explains how to create and use managed node groups with EKS.
2 describes how to use Spot Instances with managed node groups.
3 provides an overview of Spot Instances and their benefits.
A solutions architect is building an Amazon S3 data lake for a company. The company uses Amazon Kinesis Data Firehose to ingest customer personally identifiable information (PII) and transactional data in near real-time to an S3 bucket. The company needs to mask all PII data before storing the data in the data lake.
Which solution will meet these requirements?
Using a Lambda function as part of the Kinesis Data Firehose pipeline allows for real-time detection and masking of PII before data is written to S3. This ensures that PII is never stored in its raw form in the data lake.
Option B: Amazon Macie can scan and classify data but does not provide in-line PII masking for data ingestion.
Option C: Server-side encryption secures data but does not mask PII.
Option D: CloudHSM is unnecessary for PII masking and adds complexity without addressing the requirements.
AWS Documentation Reference:
Using Lambda with Kinesis Data Firehose
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