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Amazon SAA-C03 (Amazon AWS Certified Solutions Architect - Associate) Certification Exam is a globally recognized certification exam designed for professionals seeking to validate their skills and expertise in designing and deploying secure, scalable, and reliable applications on the Amazon Web Services (AWS) platform. SAA-C03 Exam is intended for individuals who are proficient in AWS technologies, understand AWS architecture best practices, and have practical experience in designing and deploying scalable, fault-tolerant, and highly available systems.
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Amazon SAA-C03 (Amazon AWS Certified Solutions Architect - Associate) Certification Exam is designed for IT professionals who want to establish their expertise in designing and deploying scalable, highly available, and fault-tolerant systems on Amazon Web Services (AWS) platform. SAA-C03 exam is intended for individuals who have experience working with AWS services and possess foundational knowledge of AWS cloud computing.
Individuals who pass the Amazon SAA-C03 Exam will receive a certification that demonstrates their expertise in AWS solutions. AWS Certified Solutions Architect - Associate certification is highly valued in the industry and can lead to better job opportunities and higher salaries. It is also a great way for individuals to stay up-to-date with the latest AWS technologies and best practices.
Amazon AWS Certified Solutions Architect - Associate Sample Questions (Q331-Q336):
NEW QUESTION # 331
A government entity is conducting a population and housing census in the city. Each household information uploaded on their online portal is stored in encrypted files in Amazon S3. The government assigned its Solutions Architect to set compliance policies that verify data containing personally identifiable information (PII) in a manner that meets their compliance standards. They should also be alerted if there are potential policy violations with the privacy of their S3 buckets.
Which of the following should the Architect implement to satisfy this requirement?
- A. Set up and configure Amazon Macie to monitor their Amazon S3 data.
- B. Set up and configure Amazon Kendra to monitor malicious activity on their Amazon S3 data
- C. Set up and configure Amazon Polly to scan for usage patterns on Amazon S3 data
- D. Set up and configure Amazon Fraud Detector to send out alert notifications whenever a security violation is detected on their Amazon S3 data.
Answer: A
Explanation:
Amazon Macie is an ML-powered security service that helps you prevent data loss by automatically discovering, classifying, and protecting sensitive data stored in Amazon S3. Amazon Macie uses machine learning to recognize sensitive data such as personally identifiable information (PII) or intellectual property, assigns a business value, and provides visibility into where this data is stored and how it is being used in your organization.

Amazon Macie generates two categories of findings: policy findings and sensitive data findings. A policy finding is a detailed report of a potential policy violation or issue with the security or privacy of an Amazon S3 bucket. Macie generates these findings as part of its ongoing monitoring activities for your Amazon S3 data. A sensitive data finding is a detailed report of sensitive data in an S3 object. Macie generates these findings when it discovers sensitive data in S3 objects that you configure a sensitive data discovery job to analyze.
Hence, the correct answer is: Set up and configure Amazon Macie to monitor their Amazon S3 data. The option that says: Set up and configure Amazon Polly to scan for usage patterns on Amazon S3 data is incorrect because Amazon Polly is simply a service that turns text into lifelike speech, allowing you to create applications that talk, and build entirely new categories of speech-enabled products. Polly can't be used to scane usage patterns on your S3 data.
The option that says: Set up and configure Amazon Kendra to monitor malicious activity on their Amazon S3 data is incorrect Amazon Kendra is just an enterprise search service that allows developers to add search capabilities to their applications. This enables their end users to discover information stored within the vast amount of content spread across their company, but not monitor malcious activity on their S3 buckets.
The option that says: Set up and configure Amazon Fraud Detector to send out alert notifications whenever a security violation is detected on their Amazon S3 data is incorrect because the Amazon Fraud Detector is only a fully managed service for identifying potentially fraudulent activities and for catching more online fraud faster. It does not check any S3 data containing personally identifiable information (PII), unlike Amazon Macie.
References:
https://docs.aws.amazon.com/macie/latest/userguide/what-is-macie.html
https://aws.amazon.com/macie/faq/
https://docs.aws.amazon.com/macie/index.html
Check out this Amazon Macie Cheat Sheet:
https://tutorialsdojo.com/amazon-macie/
AWS Security Services Overview - Secrets Manager, ACM, Macie:
https://youtu.be/ogVamzF2Dzk
NEW QUESTION # 332
A global company is migrating its workloads from an on-premises data center to AWS. The AWS environment includes multiple AWS accounts. IAM roles. AWS Config rules, and a VPC.
The company wants an automated process to provision new accounts on demand when the company's business units require new accounts.
Which solution will meet these requirements with LEAST effort?
- A. Create an AWS Lambda function that uses the AWS Organizations API to create new accounts. Invoke the Lambda function from an AWS CloudFormation template in AWS Service Catalog.
- B. Use AWS Control Tower to set up an organization in AWS Organizations. Use AWS Control Tower Account Factory for Terraform (AFT) to provision new AWS accounts.
- C. Create an organization in AWS Organizations. Use AWS Step Functions to orchestrate the account creation process. Send account creation requests to an Amazon API Gateway API endpoint to invoke an AWS Lambda function that creates new accounts.
- D. Create an organization in AWS Organizations. Use the AWS CLI CreateAccount API action to provision new AWS accounts. Organize the business units with organizational units (OUs).
Answer: B
NEW QUESTION # 333
[Design Secure Architectures]
A company needs to give a globally distributed development team secure access to the company's AWS resources in a way that complies with security policies.
The company currently uses an on-premises Active Directory for internal authentication. The company uses AWS Organizations to manage multiple AWS accounts that support multiple projects.
The company needs a solution to integrate with the existing infrastructure to provide centralized identity management and access control.
Which solution will meet these requirements with the LEAST operational overhead?
- A. Use Amazon Cognito to deploy an identity federation solution. Integrate the identity federation solution with the on-premises Active Directory. Use Amazon Cognito to provide access tokens for developers to access AWS accounts and resources.
- B. Set up AWS Directory Service to create an AWS managed Microsoft Active Directory on AWS. Establish a trust relationship with the on-premises Active Directory. Use IAM roles that are assigned to Active Directory groups to access AWS resources within the company's AWS accounts.
- C. Use AD Connector in AWS Directory Service to connect to the on-premises Active Directory. Integrate AD Connector with AWS IAM Identity Center. Configure permissions sets to give each AD group access to specific AWS accounts and resources.
- D. Create an IAM user for each developer. Manually manage permissions for each IAM user based on each user's involvement with each project. Enforce multi-factor authentication (MFA) as an additional layer of security.
Answer: C
Explanation:
UsingAD ConnectorwithAWS IAM Identity Center(formerly AWS Single Sign-On) allows the company to leverage its existingon-premises Active Directoryfor centralized identity management and access control. AD Connector acts as a proxy to the on-premises AD withoutrequiring additional infrastructure or complex setup. This solution integrates seamlessly with AWS, allowing the development team to use their existing AD credentials to access AWS resources across multiple accounts managed by AWS Organizations. The permissions for AWS resources can be managed centrally through IAM Identity Center by configuring permission sets.
This solution provides:
Least operational overhead: AD Connector is fully managed, and IAM Identity Center allows centralized management of permissions across accounts.
Secure access: The solution complies with security policies by using existing AD authentication mechanisms.
Option A (AWS Managed AD): Setting up a fully managed AWS AD and establishing a trust is more complex and involves additional operational overhead.
Option B (IAM Users): Manually managing IAM users and permissions is less scalable and increases operational complexity.
Option D (Cognito): Amazon Cognito is more suited for user-facing applications rather than internal identity management for AWS resources.
AWS Reference:
AD Connector with IAM Identity Center
AWS IAM Identity Center
NEW QUESTION # 334
[Design High-Performing Architectures]
A company runs container applications by using Amazon Elastic Kubernetes Service (Amazon EKS) and the Kubernetes Horizontal Pod Autoscaler. The workload is not consistent throughout the day. A solutions architect notices that the number of nodes does not automatically scale out when the existing nodes have reached maximum capacity in the cluster, which causes performance issues Which solution will resolve this issue with the LEAST administrative overhead?
- A. Scale out the nodes by tracking the memory usage
- B. Use an Amazon EC2 Auto Scaling group to distribute the workload.
- C. Use an AWS Lambda function to resize the EKS cluster automatically.
- D. Use the Kubernetes Cluster Autoscaler to manage the number of nodes in the cluster.
Answer: D
Explanation:
The Kubernetes Cluster Autoscaler is a component that automatically adjusts the number of nodes in your cluster when pods fail or are rescheduled onto other nodes. It uses Auto Scaling groups to scale up or down the nodes according to the demand and capacity ofyour cluster1.
By using the Kubernetes Cluster Autoscaler in your Amazon EKS cluster, you can achieve the following benefits:
You can improve the performance and availability of your container applications by ensuring that there are enough nodes to run your pods and that there are no idle nodes wasting resources.
You can reduce the administrative overhead of managing your cluster size manually or using custom scripts. The Cluster Autoscaler handles the scaling decisions and actions for you based on the metrics and events from your cluster.
You can leverage the integration of Amazon EKS and AWS Auto Scaling to optimize the cost and efficiency of your cluster. You can use features such as launchtemplates, mixed instances policies, and spot instances to customize your node configuration and save up to 90% on compute costs2
NEW QUESTION # 335
A company wants to migrate an Oracle database to AWS. The database consists of a single table that contains millions of geographic information systems (GIS) images that are high resolution and are identified by a geographic code.
When a natural disaster occurs tens of thousands of images get updated every few minutes. Each geographic code has a single image or row that is associated with it. The company wants a solution that is highly available and scalable during such events Which solution meets these requirements MOST cost-effectively?
- A. Store the images and geographic codes in an Amazon DynamoDB table Configure DynamoDB Accelerator (DAX) during times of high load
- B. Store the images in Amazon S3 buckets Store geographic codes and image S3 URLs in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance.
- C. Store the images in Amazon S3 buckets Use Amazon DynamoDB with the geographic code as the key and the image S3 URL as the value
- D. Store the images and geographic codes in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance
Answer: C
Explanation:
Explanation
Amazon S3 is a highly scalable, durable, and cost-effective object storage service that can store millions of images1. Amazon DynamoDB is a fully managed NoSQL database that can handle high throughput and low latency for key-value and document data2. By using S3 to store the images and DynamoDB to store the geographic codes and image S3 URLs, the solution can achieve high availability and scalability during natural disasters. It can also leverage DynamoDB's features such as caching, auto-scaling, and global tables to improve performance and reduce costs2.
A: Store the images and geographic codes in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance. This solution will not meet the requirement of scalability and cost-effectiveness, as Oracle is a relational database that may not handle large volumes of unstructured data such as images efficiently3. It also involves higher licensing and operational costs than S3 and DynamoDB12.
C: Store the images and geographic codes in an Amazon DynamoDB table Configure DynamoDB Accelerator (DAX) during times of high load. This solution will not meet the requirement of cost-effectiveness, as storing images in DynamoDB will consume more storage space and incur higher charges than storing them in S312. It will also require additional configuration and management of DAX clusters to handle high load.
D: Store the images in Amazon S3 buckets Store geographic codes and image S3 URLs in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance. This solution will not meet the requirement of scalability and cost-effectiveness, as Oracle is a relational database that may not handle high throughput and low latency for key-value data such as geographic codes efficiently3. It also involves higher licensing and operational costs than DynamoDB2.
Reference URL: https://dynobase.dev/dynamodb-vs-s3/
NEW QUESTION # 336
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