Amazon AWS-Solutions-Associate Online Practice Test (Amazon-AWS-Solutions-Associate-Practice-Test)

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Amazon AWS-Solutions-Associate Exam Syllabus Topics:

Section	Weight	Objectives
Design High-Performing Architectures	24%	- Design high-performing storage solutions 1. Data access patterns 2. Caching strategies 3. Storage performance optimization - Design high-performing network architectures 1. Global acceleration 2. Content delivery 3. Network throughput and latency - Design high-performing compute solutions 1. Workload optimization 2. Compute selection and sizing 3. Parallel processing
Design Secure Architectures	30%	- Design secure network architectures 1. Network isolation and segmentation 2. Traffic protection 3. Edge security - Design access management 1. Identity and access management 2. Federated access 3. Resource access control - Design secure workloads and applications 1. Security by design principles 2. Threat detection and mitigation 3. Data protection
Design Resilient Architectures	26%	- Design highly available and fault-tolerant architectures 1. Disaster recovery strategies 2. High availability configurations 3. Fault tolerance mechanisms - Design resilient compute solutions 1. Auto-scaling and elasticity 2. Workload distribution 3. Compute redundancy - Design resilient storage solutions 1. Replication and backup 2. Storage durability and availability 3. Data consistency models
Design Cost-Optimized Architectures	20%	- Design cost-optimized storage solutions 1. Storage class selection 2. Cost monitoring and optimization 3. Data lifecycle management - Design cost-optimized network architectures 1. Network service selection 2. Traffic routing efficiency 3. Data transfer cost optimization - Design cost-optimized compute solutions 1. Right-sizing and scaling 2. Instance selection and purchasing options 3. Serverless and managed services

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Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Sample Questions (Q496-Q501):

NEW QUESTION # 496
A company is developing a platform to process large volumes of data for complex analytics and machine learning (ML) tasks. The platform must handle compute-intensive workloads. The workloads currently require 20 to 30 minutes for each data processing step.
The company wants a solution to accelerate data processing.
Which solution will meet these requirements with the LEAST operational overhead?

A. Create an AWS Lambda function for each data processing step. Deploy an Amazon Simple Queue Service (Amazon SQS) queue to relay data between Lambda functions.
B. Deploy three Amazon EC2 instances. Distribute the EC2 instances across three Availability Zones. Use traditional batch processing techniques for data processing.
C. Create an Amazon EMR cluster. Use managed scaling. Install Apache Spark to assist with data processing.
D. Create a series of AWS Lambda functions to process the data. Use AWS Step Functions to orchestrate the Lambda functions into data processing steps.

Answer: C

Explanation:
Amazon EMR provides a managed big data framework that supports Apache Spark, which is ideal for distributed and compute-intensive data transformations. Managed scaling dynamically adjusts cluster resources, ensuring high performance with minimal management.
From AWS Documentation:
"Amazon EMR provides a managed environment for big data frameworks such as Apache Spark and Hadoop.
With managed scaling, EMR automatically resizes clusters to meet workload demands." (Source: Amazon EMR Developer Guide) Why B is correct:
Provides distributed parallel processing for large datasets.
Reduces operational overhead with managed scaling and auto-termination.
Integrates easily with S3, Glue, and ML pipelines.
Optimized for heavy ETL and analytics workloads.
Why others are incorrect:
A: Manual scaling and limited processing capacity.
C & D: Lambda has execution time and memory limits unsuitable for 30-minute compute-intensive tasks.
References:
Amazon EMR Developer Guide - "Using Managed Scaling"
AWS Well-Architected Framework - Performance Efficiency Pillar

NEW QUESTION # 497
A company is moving a business-critical, multi-tier application to AWS. The architecture consists of a desktop client application and server infrastructure. The server infrastructure resides in an on-premises data center that frequently fails to maintain the application uptime SLA of 99.95%. A Solutions Architect must re-architect the application to ensure that it can meet or exceed the SLA.
The application contains a PostgreSQL database running on a single virtual machine. The business logic and presentation layers are load balanced between multiple virtual machines. Remote users complain about slow load times while using this latency-sensitive application.
Which of the following will meet the availability requirements with little change to the application while improving user experience and minimizing costs?

A. Migrate the database to an Amazon Redshift cluster with at least two nodes. Combine and host the application and presentation layers in automatically scaled Amazon ECS containers behind an Application Load Balancer. Use Amazon CloudFront to improve the user experience.
B. Migrate the database to an Amazon RDS Aurora PostgreSQL configuration. Host the application and presentation layers in an Auto Scaling configuration on Amazon EC2 instances behind an Application Load Balancer. Use Amazon AppStream 2.0 to improve the user experience.
C. Migrate the database to a PostgreSQL database in Amazon EC2. Host the application and presentation layers in automatically scaled Amazon ECS containers behind an Application Load Balancer. Allocate an Amazon WorkSpaces WorkSpace for each end user to improve the user experience.
D. Migrate the database to an Amazon RDS PostgreSQL Multi-AZ configuration. Host the application and presentation layers in automatically scaled AWS Fargate containers behind a Network Load Balancer.
Use Amazon ElastiCache to improve the user experience.

Answer: A

Explanation:
Explanation/Reference:

NEW QUESTION # 498
A company has an application that receives and processes purchase orders. The application supports only XML data. The company needs to configure the application to accept orders in JSON format. The company does not want to modify the application.
A solutions architect is using an Amazon API Gateway HTTP API to create a new purchase order API. The solutions architect needs to modify the application DNS record to point to the new HTTP API.

A. Use an HTTP proxy integration to pass XML requests to the application. For JSON requests, use an AWS Lambda function that is integrated with API Gateway to convert the purchase orders from JSON to XML and to call the application.
B. Use an HTTP proxy integration to pass XML requests to the application. For JSON requests, use API Gateway mappings to convert the purchase orders to XML. Use an AWS Lambda function that is integrated with API Gateway to call the application.
C. Use an HTTP custom integration to pass XML requests to the application. For JSON requests, use an AWS Lambda function that is integrated with API Gateway to convert the purchase orders to JSON and to call the application.
D. Use an HTTP custom integration to pass XML requests to the application. For JSON requests, use API Gateway mappings to convert the purchase orders to XML. Use an AWS Lambda function that is integrated with API Gateway to call the application.

Answer: A

Explanation:
Why Option B is Correct:
HTTP Proxy Integration: Passes XML requests directly to the application, which already supports XML.
JSON Conversion: An AWS Lambda function converts JSON requests to XML and calls the application.
API Gateway: Acts as a front end to handle JSON requests and integrates seamlessly with Lambda for the transformation process.
Why Other Options Are Not Ideal:
Option A: Suggests using API Gateway mappings to convert JSON to XML. API Gateway mapping templates are limited in functionality and are not ideal for complex transformations.
Option C and D: Use HTTP custom integration unnecessarily, which adds complexity without additional benefits.
AWS References:
Amazon API Gateway Integration:AWS Documentation - API Gateway Integration AWS Lambda:AWS Documentation - Lambda

NEW QUESTION # 499
A company processes large amounts of data. The output data is stored in Amazon S3 Standard storage in an S3 bucket, where it is analyzed for 1 month. The data must remain immediately accessible after the 1-month analysis period.
Which storage solution meets these requirements MOST cost-effectively?

A. Configure an S3 Lifecycle policy to transition the objects to S3 Glacier after 30 days.
B. Configure an S3 Lifecycle policy to transition the objects to S3 One Zone-Infrequent Access (S3 One Zone-IA) after 30 days.
C. Configure an S3 Lifecycle policy to delete the objects after 30 days. Enable versioning on the S3 bucket so that deleted objects can still be immediately restored as needed.
D. Configure S3 Intelligent-Tiering to transition the objects to S3 Glacier after 30 days.

Answer: D

NEW QUESTION # 500
A global company hosts its web application on Amazon EC2 instances behind an Application Load Balancer (ALB). The web application has static data and dynamic data. The company stores its static data in an Amazon S3 bucket. The company wants to improve performance and reduce latency for the static data and dynamic data. The company is using its own domain name registered with Amazon Route 53.
What should a solutions architect do to meet these requirements?

A. Create an Amazon CloudFront distribution that has the ALB as an origin Create an AWS Global Accelerator standard accelerator that has the S3 bucket as an endpoint Create two domain names. Point one domain name to the CloudFront DNS name for dynamic content, Point the other domain name to the accelerator DNS name for static content Use the domain names as endpoints for the web application.
B. Create an Amazon CloudFront distribution that has the S3 bucket and the ALB as origins Configure Route 53 to route traffic to the CloudFront distribution.
C. Create an Amazon CloudFront distribution that has the ALB as an origin Create an AWS Global Accelerator standard accelerator that has the S3 bucket as an endpoint. Configure Route 53 to route traffic to the CloudFront distribution.
D. Create an Amazon CloudFront distribution that has the S3 bucket as an origin Create an AWS Global Accelerator standard accelerator that has the ALB and the CloudFront distribution as endpoints Create a custom domain name that points to the accelerator DNS name Use the custom domain name as an endpoint for the web application.

Answer: C

NEW QUESTION # 501
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