2026 Amazon Updated AWS-Solutions-Associate Test Result

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Amazon AWS-Solutions-Associate Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Design Secure Architectures	30%	- Design secure access to AWS resources 1. Least privilege access 2. Identity and access management 3. Authentication and authorization mechanisms - Determine appropriate data security controls 1. Data protection in transit 2. Data protection at rest 3. Key management - Design secure workloads and applications 1. Secure application integration 2. Data encryption 3. Network security controls
Topic 2: Design High-Performing Architectures	24%	- Determine high-performing database and network architectures 1. Database service selection 2. Network performance optimization 3. Caching strategies - Design high-performing compute solutions 1. Compute service selection 2. Serverless architectures 3. Performance optimization - Determine high-performing and scalable storage solutions 1. File storage 2. Object storage 3. Block storage
Topic 3: Design Cost-Optimized Architectures	20%	- Design cost-optimized storage solutions 1. Storage class selection 2. Lifecycle management - Design cost-optimized compute, database, and network solutions 1. Pricing models 2. Cost monitoring and optimization 3. Resource right-sizing
Topic 4: Design Resilient Architectures	26%	- Design scalable and loosely coupled architectures 1. Event-driven architectures 2. Decoupled services 3. Elastic scaling - Design highly available and fault-tolerant architectures 1. Multi-AZ and multi-region strategies 2. Disaster recovery planning 3. Backup and recovery

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Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Sample Questions (Q565-Q570):

NEW QUESTION # 565
A company has two VPCs named Management and Production. The Management VPC uses VPNs through a customer gateway to connect to a single device in the data center. The Production VPC uses a virtual private gateway with two attached AWS Direct Connect connections. The Management and Production VPCs both use a single VPC peering connection to allow communication between the applications.
What should a solutions architect do to mitigate any single point of failure in this architecture?

A. Add a second VPC peering connection between the Management VPC and the Production VPC.
B. Add a second set of VPNs to the Management VPC from a second customer gateway device.
C. Add a second virtual private gateway and attach it to the Management VPC.
D. Add a set of VPNs between the Management and Production VPCs.

Answer: D

NEW QUESTION # 566
You are configuring a new VPC for one of your clients for a cloud migration project, and only a public VPN will be in place. After you created your VPC, you created a new subnet, a new internet gateway, and attached your internet gateway to your VPC. When you launched your first instance into your VPC, you realized that you aren't able to connect to the instance, even if it is configured with an elastic IP. What should be done to access the instance?

A. A NACL should be created that allows all outbound traffic.
B. A route should be created as 0.0.0.0/0 and your internet gateway as target.
C. A NAT instance should be created and all traffic should be forwarded to NAT instance.
D. Attach another ENI to the instance and connect via new ENI.

Answer: B

Explanation:
All traffic should be routed via Internet Gateway. So, a route should be created with 0.0.0.0/0 as a source, and your Internet Gateway as your target.
Reference: http://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Scenario1.html

NEW QUESTION # 567
A photo-sharing service stores pictures in Amazon Simple Storage Service (53) and allows application sign-in using an OpenID Connect-compatible identity provider. Which AWS Security Token Service approach to temporary access should you use for the Amazon 53 operations?

A. Web Identity Federation
B. AWS Identity and Access Management roles
C. Cross-Account Access
D. SAML-based Identity Federation

Answer: A

NEW QUESTION # 568
Your startup wants to implement an order fulfillment process for selling a personalized gadget that needs an average of 3-4 days to produce with some orders taking up to 6 months you expect 10 orders per day on your first day. 1000 orders per day after 6 months and 10,000 orders after 12 months.
Orders coming in are checked for consistency men dispatched to your manufacturing plant for production quality control packaging shipment and payment processing If the product does not meet the quality standards at any stage of the process employees may force the process to repeat a step Customers are notified via email about order status and any critical issues with their orders such as payment failure.
Your case architecture includes AWS Elastic Beanstalk for your website with an RDS MySQL instance for customer data and orders.
How can you implement the order fulfillment process while making sure that the emails are delivered reliably?

A. Use SWF with an Auto Scaling group of activity workers and a decider instance in another Auto Scaling group with min/max=1 Use the decider instance to send emails to customers.
B. Use SWF with an Auto Scaling group of activity workers and a decider instance in another Auto Scaling group with min/max=1 use SES to send emails to customers.
C. Use an SQS queue to manage all process tasks Use an Auto Scaling group of EC2 Instances that poll the tasks and execute them. Use SES to send emails to customers.
D. Add a business process management application to your Elastic Beanstalk app servers and re-use the ROS database for tracking order status use one of the Elastic Beanstalk instances to send emails to customers.

Answer: B

NEW QUESTION # 569
A company needs a solution to prevent photos with unwanted content from being uploaded to the company's web application. The solution must not involve training a machine learning (ML) model. Which solution will meet these requirements?

A. Create an Amazon CloudFront function that uses Amazon Comprehend to detect unwanted content.
Associate the function with the web application.
B. Create an AWS Lambda function that uses Amazon Rekognition to detect unwanted content. Create a Lambda function URL that the web application invokes when new photos are uploaded.
C. Create an AWS Lambda function that uses Amazon Rekognition Video to detect unwanted content.
Create a Lambda function URL that the web application invokes when new photos are uploaded.
D. Create and deploy a model by using Amazon SageMaker Autopilot. Create a real-time endpoint that the web application invokes when new photos are uploaded.

Answer: B

Explanation:
The solution that will meet the requirements is to create an AWS Lambda function that uses Amazon Rekognition to detect unwanted content, and create a Lambda function URL that the web application invokes when new photos are uploaded. This solution does not involve training a machine learning model, as Amazon Rekognition is a fully managed service that provides pre-trained computer vision models for image and video analysis. Amazon Rekognition can detect unwanted content such as explicit or suggestive adult content, violence, weapons, drugs, and more. By using AWS Lambda, the company can create a serverless function that can be triggered by an HTTP request from the web application. The Lambda function can use the Amazon Rekognition API to analyze the uploaded photos and return a response indicating whether they contain unwanted content or not.
The other solutions are not as effective as the first one because they either involve training a machine learning model, do not support image analysis, or do not work with photos. Creating and deploying a model by using Amazon SageMaker Autopilot involves training a machine learning model, which is not required for the scenario. Amazon SageMaker Autopilot is a service that automatically creates, trains, and tunes the best machine learning models for classification or regression based on the data provided by the user. Creating an Amazon CloudFront function that uses Amazon Comprehend to detect unwanted content does not support image analysis, as Amazon Comprehend is a natural language processing service that analyzes text, not images. Amazon Comprehend can extract insights and relationships from text such as language, sentiment, entities, topics, and more. Creating an AWS Lambda function that uses Amazon Rekognition Video todetect unwanted content does not work with photos, as Amazon Rekognition Video is designed for analyzing video streams, not static images. AmazonRekognition Video can detect activities, objects, faces, celebrities, text, and more in video streams.
References:
Amazon Rekognition
AWS Lambda
Detecting unsafe content - Amazon Rekognition
Amazon SageMaker Autopilot
Amazon Comprehend

NEW QUESTION # 570
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