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The SAA-C03 Certification Exam is designed for IT professionals who are responsible for designing and deploying scalable, highly available, and fault-tolerant systems on AWS. Candidates for this certification should have a solid understanding of AWS services, architecture, and best practices. They should also have experience with designing and deploying AWS solutions using AWS services such as EC2, S3, RDS, and VPC.

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The SAA-C03 certification exam is a valuable asset for professionals who want to enhance their career opportunities and demonstrate their expertise in AWS cloud computing. Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam certification is recognized globally and is a benchmark for employers to assess the candidate's skills and knowledge in AWS services and solutions. The SAA-C03 Certification is the first step in the AWS certification path, and it is a prerequisite for the professional-level certification exams. Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam certification provides a competitive advantage to the candidate and opens up new job opportunities in the cloud computing industry.

Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam Sample Questions (Q747-Q752):

NEW QUESTION # 747
A solutions architect is designing the architecture for a software demonstration environment The environment will run on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer (ALB) The system will experience significant increases in traffic during working hours but Is not required to operate on weekends.
Which combination of actions should the solutions architect take to ensure that the system can scale to meet demand? (Select TWO)

A. Use a target tracking scaling policy to scale the Auto Scaling group based on instance CPU utilization
B. Use AWS Auto Scaling to adjust the ALB capacity based on request rate
C. Launch the EC2 instances in multiple AWS Regions to distribute the load across Regions
D. Use scheduled scaling to change the Auto Scaling group minimum, maximum, and desired capacity to zero for weekends Revert to the default values at the start of the week
E. Use AWS Auto Scaling to scale the capacity of the VPC internet gateway

Answer: A,D

Explanation:
Explanation
https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-scaling-target-tracking.html#target-tracking-choose-m A target tracking scaling policy is a type of dynamic scaling policy that adjusts the capacity of an Auto Scaling group based on a specified metric and a target value1. A target tracking scaling policy can automatically scale out or scale in the Auto Scaling group to keep the actual metric value at or near the target value1. A target tracking scaling policy is suitable for scenarios where the load on the application changes frequently and unpredictably, such as during working hours2.
To meet the requirements of the scenario, the solutions architect should use a target tracking scaling policy to scale the Auto Scaling group based on instance CPU utilization. Instance CPU utilization is a common metric that reflects the demand on the application1. The solutions architect should specify a target value that represents the ideal average CPU utilization level for the application, such as 50 percent1. Then, the Auto Scaling group will scale out or scale in to maintain that level of CPU utilization.
Scheduled scaling is a type of scaling policy that performs scaling actions based on a date and time3
. Scheduled scaling is suitable for scenarios where the load on the application changes periodically and predictably, such as on weekends2.
To meet the requirements of the scenario, the solutions architect should also use scheduled scaling to change the Auto Scaling group minimum, maximum, and desired capacity to zero for weekends. This way, the Auto Scaling group will terminate all instances on weekends when they are not required to operate. The solutions architect should also revert to the default values at the start of the week, so that the Auto Scaling group can resume normal operation.

NEW QUESTION # 748
A solutions architect has created two IAM policies: Policy1 and Policy2. Both policies are attached to an IAM group.

A cloud engineer is added as an IAM user to the IAM group. Which action will the cloud engineer be able to perform?

A. Deleting logs from Amazon CloudWatch Logs
B. Deleting directories
C. Deleting IAM users
D. Deleting Amazon EC2 instances

Answer: D

Explanation:
https://awscli.amazonaws.com/v2/documentation/api/latest/reference/ds/index.html

NEW QUESTION # 749
A company has an employee web portal. Employees log in to the portal to view payroll details. The company is developing a new system to give employees the ability to upload scanned documents for reimbursement.
The company runs a program to extract text-based data from the documents and attach the extracted information to each employee's reimbursement IDs for processing.
The employee web portal requires 100% uptime. The document extract program runs infrequently throughout the day on an on-demand basis. The company wants to build a scalable and cost-effective new system that will require minimal changes to the existing web portal. The company does not want to make any code changes.
Which solution will meet these requirements with the LEAST implementation effort?

A. Purchase a Savings Plan to run the web portal and the document extract program. Run the web portal and the document extract program in an Auto Scaling group.
B. Run Amazon EC2 Spot Instances in an Auto Scaling group for the web portal. Run the document extract program on EC2 Spot Instances Start document extract program instances when an employee uploads a new reimbursement document.
C. Create an Amazon S3 bucket to host the web portal. Use Amazon API Gateway and an AWS Lambda function for the existing functionalities. Use the Lambda function to run the document extract program.Invoke the Lambda function when the API that is associated with a new document upload is called.
D. Run Amazon EC2 On-Demand Instances in an Auto Scaling group for the web portal. Use an AWS Lambda function to run the document extract program. Invoke the Lambda function when an employee uploads a new reimbursement document.

Answer: D

Explanation:
This solution offers the most scalable and cost-effective approach with minimal changes to the existing web portal and no code modifications.
* Amazon EC2 On-Demand Instances in an Auto Scaling Group: Running the web portal on EC2 On- Demand instances ensures 100% uptime and scalability. The Auto Scaling group will maintain the desired number of instances, automatically scaling up or down as needed, ensuring high availability for the employee web portal.
* AWS Lambda for Document Extraction: Lambda is a serverless compute service that allows you to run code in response to events without provisioning or managing servers. By using Lambda to run the document extraction program, you can trigger the function whenever an employee uploads a document.
This approach is cost-effective since you only pay for the compute time used by the Lambda function.
* No Code Changes Required: This solution integrates with the existing infrastructure with minimal implementation effort and does not require any modifications to the web portal's code.
* Why Not Other Options?:
* Option B (Spot Instances): Spot Instances are not suitable for workloads requiring 100% uptime, as they can be terminated by AWS with short notice.
* Option C (Savings Plan): A Savings Plan could reduce costs but does not address the requirement for running the document extraction program efficiently or without code changes.
* Option D (S3 with API Gateway and Lambda): This would require significant changes to the existing web portal setup, including moving the portal to S3 and reconfiguring its architecture, which contradicts the requirement of minimal implementation effort and no code changes.
AWS References:
* Amazon EC2 Auto Scaling - Information on how to use Auto Scaling for EC2 instances.
* AWS Lambda - Overview of AWS Lambda and its use cases.

NEW QUESTION # 750
A company has an AWS Glue extract. transform, and load (ETL) job that runs every day at the same time. The job processes XML data that is in an Amazon S3 bucket.
New data is added to the S3 bucket every day. A solutions architect notices that AWS Glue is processing all the data during each run.
What should the solutions architect do to prevent AWS Glue from reprocessing old data?

A. Edit the job to use job bookmarks.
B. Edit the job to delete data after the data is processed
C. Use a FindMatches machine learning (ML) transform.
D. Edit the job by setting the NumberOfWorkers field to 1.

Answer: D

Explanation:
This is the purpose of bookmarks: "AWS Glue tracks data that has already been processed during a previous run of an ETL job by persisting state information from the job run. This persisted state information is called a job bookmark. Job bookmarks help AWS Glue maintain state information and prevent the reprocessing of old data." https://docs.aws.amazon.com/glue/latest/dg/monitor-continuations.html

NEW QUESTION # 751
A company needs to optimize the cost of its Amazon EC2 Instances. The company also needs to change the type and family of its EC2 instances every 2-3 months.
What should the company do lo meet these requirements?

A. Purchase an All Upfront EC2 Instance Savings Plan for a 1-year term.
B. Purchase All Upfront Reserved Instances for a 1 -year term.
C. Purchase Partial Upfront Reserved Instances tor a 3-year term.
D. Purchase a No Upfront Compute Savings Plan for a 1-year term.

Answer: D

Explanation:
Understanding the Requirements: The company needs to optimize costs and has the flexibility to change EC2 instance types and families frequently (every 2-3 months).
Savings Plans Overview: Savings Plans offer significant savings over On-Demand pricing, with the flexibility to use any instance type and family within a region.
No Upfront Compute Savings Plan: This plan allows for cost optimization without any upfront payment, offering flexibility to change instance types and families.
Term Selection: A 1-year term is appropriate for balancing cost savings and flexibility given the frequent changes in instance types.
Conclusion: A No Upfront Compute Savings Plan for a 1-year term provides the needed flexibility and cost savings without the commitment and inflexibility of Reserved Instances.
Reference
AWS Savings Plans: AWS Savings Plans
AWS Cost Management Documentation: AWS Cost Management

NEW QUESTION # 752
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SAA-C03 Test Free - SAA-C03 New Study Materials

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Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam Sample Questions (Q747-Q752):

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