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Earning the Amazon SAA-C03 Certification can be a valuable asset for IT professionals who work with AWS. It validates their expertise in designing and deploying scalable and fault-tolerant systems on AWS, which can help them advance their career and increase their earning potential. Additionally, it can help organizations identify professionals who have the necessary skills to deploy and manage AWS solutions effectively.

Amazon SAA-C03 Certification Exam is a highly sought-after certification for IT professionals seeking to demonstrate their expertise in designing and deploying scalable, highly available, and fault-tolerant systems on Amazon Web Services (AWS) cloud platform. Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam certification exam is designed to validate the candidate's ability to architect and deploy secure and robust applications on the AWS platform, using best practices and industry-standard techniques.

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

NEW QUESTION # 496
A company has one million users that use its mobile app. The company must analyze the data usage in near-real time. The company also must encrypt the data in near-real time and must store the data in a centralized location in Apache Parquet format for further processing.
Which solution will meet these requirements with the LEAST operational overhead?

A. Create an Amazon Kinesis data stream to store the data in Amazon S3. Create an Amazon Kinesis Data Analytics application to analyze the data. Invoke an AWS Lambda function to send the data to the Kinesis Data Analytics application.
B. Create an Amazon Kinesis data stream to store the data in Amazon S3. Create an Amazon EMR cluster to analyze the data. Invoke an AWS Lambda function to send the data to the EMR cluster.
C. Create an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Create an Amazon Kinesis Data Analytics application to analyze the data
D. Create an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Create an Amazon EMR cluster to analyze the data.

Answer: C

Explanation:
Explanation
This solution will meet the requirements with the least operational overhead as it uses Amazon Kinesis Data Firehose, which is a fully managed service that can automatically handle the data collection, data transformation, encryption, and data storage in near-real time. Kinesis Data Firehose can automatically store the data in Amazon S3 in Apache Parquet format for further processing. Additionally, it allows you to create an Amazon Kinesis Data Analytics application to analyze the data in near real-time, with no need to manage any infrastructure or invoke any Lambda function. This way you can process a large amount of data with the least operational overhead.

NEW QUESTION # 497
A company runs workloads in the AWS Cloud The company wants to centrally collect security data to assess security across the entire company and to improve workload protection.
Which solution will meet these requirements with the LEAST development effort?

A. Configure a data lake in AWS Lake Formation Use AWS Glue crawlers to ingest the security data into the data lake.
B. Configure a data lake in Amazon Security Lake to collect the security data Upload the data to an Amazon S3 bucket.
C. Configure an AWS Lambda function to collect the security data in csv format. Upload the data to an Amazon S3 bucket
D. Configure an AWS Database Migration Service (AWS DMS) replication instance to load the security data into an Amazon RDS cluster

Answer: B

Explanation:
Understanding the Requirement: The company wants to centrally collect security data with minimal development effort to assess and improve security across all workloads.
Analysis of Options:
Amazon Security Lake: This is a purpose-built service for centralizing security data from across AWS services and third-party sources into a data lake. It provides native integration and requires minimal development effort to set up.
AWS Lake Formation with AWS Glue: While this can be used to create a data lake, it requires more development effort to set up and configure Glue crawlers for ingestion.
AWS Lambda with S3: This approach involves custom development to collect and process security data before storing it in S3, which requires more effort.
AWS DMS to RDS: AWS Database Migration Service is typically used for database migrations and is not suited for collecting and analyzing security data.
Best Option for Minimal Development Effort:
Amazon Security Lake provides the least development effort for setting up a centralized repository for security data. It simplifies data ingestion and management, making it the most efficient solution for this use case.
Reference:
Amazon Security Lake
AWS Lake Formation
AWS Glue

NEW QUESTION # 498
A company's website uses an Amazon EC2 instance store for its catalog of items. The company wants to make sure that the catalog is highly available and that the catalog is stored in a durable location.
What should a solutions architect do to meet these requirements?

A. Move the catalog from the instance store to Amazon S3 Glacier Deep Archive.
B. Deploy a larger EC2 instance with a larger instance store.
C. Move the catalog to Amazon ElastiCache for Redis.
D. Move the catalog to an Amazon Elastic File System (Amazon EFS) file system.

Answer: D

Explanation:
Moving the catalog to an Amazon Elastic File System (Amazon EFS) file system provides both high availability and durability. Amazon EFS is a fully-managed, highly-available, and durable file system that is built to scale on demand. With Amazon EFS, the catalog data can be stored and accessed from multiple EC2 instances in different availability zones, ensuring high availability. Also, Amazon EFS automatically stores files redundantly within and across multiple availability zones, making it a durable storage option.

NEW QUESTION # 499
An ecommerce company wants to launch a one-deal-a-day website on AWS. Each day will feature exactly one product on sale for a period of 24 hours. The company wants to be able to handle millions of requests each hour with millisecond latency during peak hours.
Which solution will meet these requirements with the LEAST operational overhead?

A. Migrate the full application to run in containers Host the containers on Amazon Elastic Kubernetes Service (Amazon EKS) Use the Kubernetes Cluster Autoscaler to increase and decrease the number of pods to process bursts in traffic Store the data in Amazon RDS for MySQL
B. Deploy the full website on Amazon EC2 instances that run in Auto Scaling groups across multiple Availability Zones Add an Application Load Balancer (ALB) to distribute the website traffic Add another ALB for the backend APIs Store the data in Amazon RDS for MySQL
C. Use an Amazon S3 bucket to host the website's static content Deploy an Amazon CloudFront distribution. Set the S3 bucket as the origin Use Amazon API Gateway and AWS Lambda functions for the backend APIs Store the data in Amazon DynamoDB
D. Use Amazon S3 to host the full website in different S3 buckets Add Amazon CloudFront distributions Set the S3 buckets as origins for the distributions Store the order data in Amazon S3

Answer: C

Explanation:
To launch a one-deal-a-day website on AWS with millisecond latency during peak hours and with the least operational overhead, the best option is to use an Amazon S3 bucket to host the website's static content, deploy an Amazon CloudFront distribution, set the S3 bucket as the origin, use Amazon API Gateway and AWS Lambda functions for the backend APIs, and store the data in Amazon DynamoDB. This option requires minimal operational overhead and can handle millions of requests each hour with millisecond latency during peak hours. Therefore, option D is the correct answer.
Reference:
https://aws.amazon.com/blogs/compute/building-a-serverless-multi-player-game-with-aws-lambda-and-amazon-

NEW QUESTION # 500
A company stores text files in Amazon S3. The text files include customer chat messages, date and time information, and customer personally identifiable information (Pll).
The company needs a solution to provide samples of the conversations to an external service provider for quality control. The external service provider needs to randomly pick sample conversations up to the most recent conversation. The company must not share the customer Pll with the external service provider. The solution must scale when the number of customer conversations increases.
Which solution will meet these requirements with the LEAST operational overhead?

A. Create a web application on an Amazon EC2 instance that presents a list of the files, redacts the Pll from the files, and allows the external service provider to download new versions of the files that have the Pll redacted.
B. Create a batch process on an Amazon EC2 instance that regularly reads all new files, redacts the Pll from the files, and writes the redacted files to a different S3 bucket. Instruct the external service provider to access the bucket that does not contain the Pll.
C. Create an Amazon DynamoDB table. Create an AWS Lambda function that reads only the data in the files that does not contain Pll. Configure the Lambda function to store the non-PII data in the DynamoDB table when a new file is written to Amazon S3. Grant the external service provider access to the DynamoDB table.
D. Create an Object Lambda Access Point. Create an AWS Lambda function that redacts the Pll when the function reads the file. Instruct the external service provider to access the Object Lambda Access Point.

Answer: D

Explanation:
The correct solution is to create an Object Lambda Access Point and an AWS Lambda function that redacts the PII when the function reads the file. This way, the company can use the S3 Object Lambda feature to modify the S3 object content on the fly, without creating a copy or changing the originalobject. The external service provider can access the Object Lambda Access Point and get the redacted version of the file. This solution has the least operational overhead because it does not require any additional storage, processing, or synchronization. The solution also scales automatically with the number of customer conversations and the demand from the external service provider. The other options are incorrect because:
Option B is using a batch process on an EC2 instance to read, redact, and write the files to a different S3 bucket. This solution has more operational overhead because it requires managing the EC2 instance, the batch process, and the additional S3 bucket. It also introduces latency and inconsistency between the original and the redacted files.
Option C is using a web application on an EC2 instance to present, redact, and download the files. This solution has more operational overhead because it requires managing the EC2 instance, the web application, and the download process. It also exposes the original files to the web application, which increases the risk of leaking the PII.
Option D is using a DynamoDB table and a Lambda function to store the non-PII data from the files. This solution has more operational overhead because it requires managing the DynamoDB table, the Lambda function, and the data transformation. It also changes the format and the structure of the original files, which may affect the quality control process.
References:
S3 Object Lambda
Object Lambda Access Point
Lambda function

NEW QUESTION # 501
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