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To prepare for the SAP-C02 Certification Exam, individuals are recommended to have at least two years of hands-on experience in designing and deploying AWS-based solutions. They can also enroll in training courses, attend workshops, and use study materials provided by AWS to enhance their knowledge and skills. Additionally, individuals can take practice exams to familiarize themselves with the exam format and identify areas where they need to improve.

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The SAP-C02 Certification Exam is a rigorous assessment that validates an individual's technical expertise in designing and deploying AWS-based solutions. It is a valuable credential that demonstrates an individual's commitment to their profession and opens up new opportunities for career advancement.

The topics covered in the SAP-C02 exam include advanced AWS services such as AWS Lambda, AWS Elastic Beanstalk, AWS CloudFormation, and AWS CloudTrail. Candidates are also tested on their knowledge of designing and deploying multi-tier architectures, hybrid architectures, and highly available and fault-tolerant systems on AWS. Security, compliance, and troubleshooting are also important topics covered in the exam.

Amazon AWS Certified Solutions Architect - Professional (SAP-C02) Sample Questions (Q482-Q487):

NEW QUESTION # 482
A company has purchased appliances from different vendors. The appliances all have loT sensors. The sensors send status information in the vendors' proprietary formats to a legacy application that parses the information into JSON. The parsing is simple, but each vendor has a unique format. Once daily, the application parses all the JSON records and stores the records in a relational database for analysis.
The company needs to design a new data analysis solution that can deliver faster and optimize costs.
Which solution will meet these requirements?

A. Use AWS Snowball Edge to collect data from the loT sensors directly to perform local analysis.
Periodically collect the data into Amazon Redshift to perform global analysis.
B. Create an AWS Transfer for SFTP server. Update the loT sensor code to send the information as a .csv file through SFTP to the server. Use AWS Glue to catalog the files. Use Amazon Athena for analysis.
C. Connect the loT sensors to AWS loT Core. Set a rule to invoke an AWS Lambda function to parse the information and save a .csv file to Amazon S3. Use AWS Glue to catalog the files. Use Amazon Athena and Amazon OuickSight for analysis.
D. Migrate the application server to AWS Fargate, which will receive the information from loT sensors and parse the information into a relational format. Save the parsed information to Amazon Redshift for analysis.

Answer: C

Explanation:
Explanation
Connect the IoT sensors to AWS IoT Core. Set a rule to invoke an AWS Lambda function to parse the information and save a .csv file to Amazon S3. Use AWS Glue to catalog the files. Use Amazon Athena and Amazon QuickSight for analysis. This solution meets the requirement of faster analysis and cost optimization by using AWS IoT Core to collect data from the IoT sensors in real-time and then using AWS Glue and Amazon Athena for efficient data analysis.
This solution involves connecting the loT sensors to the AWS loT Core, setting a rule to invoke an AWS Lambda function to parse the information, and saving a .csv file to Amazon S3. AWS Glue can be used to catalog the files and Amazon Athena and Amazon QuickSight can be used for analysis. This solution will enable faster and more cost-effective data analysis.
This solution is in line with the official Amazon Textbook and Resources for the AWS Certified Solutions Architect - Professional certification. In particular, the book states that: "AWS IoT Core can be used to ingest and process the data, AWS Lambda can be used to process and transform the data, and Amazon S3 can be used to store the data. AWS Glue can be used to catalog and access the data, Amazon Athena can be used to query the data, and Amazon QuickSight can be used to visualize the data." (Source:
https://d1.awsstatic.com/training-and-certification/docs-sa-pro/AWS_Certified_Solutions_Architect_Professiona

NEW QUESTION # 483
A company has a platform that consists of an on-premises single-node Kubernetes cluster. The cluster uses Windows-based and Linux-based file storage as shared storage. The company wants to migrate its platform to AWS.
The cluster has multiple containerized applications that are continuously scanned for operating system vulnerabilities and programming language package vulnerabilities. The company needs a highly available solution that supports monitoring, logging, and multiprotocol shared storage.
Which combination of steps will meet these requirements with the LEAST operational overhead? (Select TWO.)

A. Provision an Amazon FSx for Windows File Server file share and an Amazon EFS file system. Mount the file share and the file system on the containers launched on the Amazon EKS cluster as persistent volumes.
B. Replace the existing Kubernetes cluster with a multi-node Amazon EKS cluster that is managed by AWS. Install open source versions of Prometheus and Grafana on Amazon EC2 instances. Store the application Docker images in Amazon ECR. Enable ECR enhanced scanning.
C. Replace the existing Kubernetes cluster with a multi-node Amazon EKS cluster that is managed by AWS. Set up Amazon Managed Service for Prometheus and Amazon Managed Grafana for monitoring.
Store the application Docker images in Amazon ECR. Enable ECR enhanced scanning.
D. Provision an Amazon FSx for NetApp ONTAP file system. Mount the file system on the containers launched on the Amazon EKS cluster as a persistent volume.
E. Replace the existing Kubernetes cluster with a single-node Amazon EKS cluster that is managed by AWS. Install Prometheus and Grafana on the EKS cluster by using public Docker images. Store the application Docker images in Amazon ECR. Enable ECR enhanced scanning.

Answer: C,D

Explanation:
B and E are correct. A multi-node Amazon EKS cluster provides high availability for the Kubernetes control and workload layer, while Amazon Managed Service for Prometheus and Amazon Managed Grafana reduce monitoring overhead compared with self-managed Prometheus and Grafana. Amazon ECR enhanced scanning is also appropriate because it uses Amazon Inspector to scan container images for operating system and programming language package vulnerabilities. For storage, Amazon FSx for NetApp ONTAP is the correct multiprotocol shared file system because it supports access patterns such as NFS and SMB through a fully managed service. EFS plus FSx for Windows splits storage across two services and does not provide one multiprotocol storage platform. A single-node EKS cluster is not highly available.

NEW QUESTION # 484
A company is migrating a legacy application from an on-premises data center to AWS. The application uses MangeDB as a key-value database According to the company's technical guidelines, all Amazon EC2 instances must be hosted in a private subnet without an internet connection In addition, all connectivity between applications and databases must be encrypted. The database must be able to scale based on demand Which solution will meet these requirements?

A. Create new Amazon DynamoDB tables for the application with on-demand capacity Use an interface VPC endpoint for DynamoDB to connect to the DynamoDB tables
B. Create new Amazon DynamoDB tables for the application with on-demand capacity Use a gateway VPC endpoint for DynamoDB to connect lo the DynamoDB tables
C. Create new Amazon DocumentDB (with MangeDB compatibility) tables for the application with Provisioned IOPS volumes Use the cluster endpoint to connect to Amazon DocumentDB
D. Create new Amazon DocumentDB (with MangeDB compatibility) tables for the application with Provisioned IOPS volumes Use the instance endpoint to connect to Amazon DocumentDB

Answer: B

Explanation:
Explanation
https://docs.aws.amazon.com/vpc/latest/privatelink/aws-services-privatelink-support.html

NEW QUESTION # 485
A company is deploying a third-party web application to an AWS account. The company wants to deploy the application across multiple Amazon EC2 instances. The company must have the ability to scale horizontally when necessary. The application uses browser cookies for session state management. The application requires session affinity. Which solution will meet these requirements?

A. Assign each EC2 instance a public IP address. Configure an Amazon Route 53 multi-value A record for the application. Enable health checks for the A record. Configure a Route 53 resolver rule that ensures a specific cookie value will consistently return the same EC2 instance. Access the application by using the Route 53 A record.
B. Configure a Gateway Load Balancer (GWLB). Register the EC2 instances as a target group by using their instance IDs. Enable flow stickiness on the target group. Access the application by using the GWLB domain name.
C. Place the EC2 instances in an Auto Scaling group. Configure a public Application Load Balancer (ALB), and configure the ALB to direct traffic for the application to the Auto Scaling group to enable sticky sessions on the target group for the application cookies. Access the application by using the ALB domain name.
D. Place the EC2 instances in an Auto Scaling group. Configure an Amazon CloudFront distribution and set the Auto Scaling group as the origin. Create a CloudFront function to handle viewer requests. Include cookie processing logic to ensure that users are directed to the correct EC2 instance. Access the application by using the CloudFront distribution URL.

Answer: C

Explanation:
An Application Load Balancer in front of an Auto Scaling group provides horizontal scaling and can maintain session affinity by enabling sticky sessions on the target group. With stickiness enabled, the load balancer consistently routes a client's requests to the same EC2 instance based on the application's session cookie, satisfying the session affinity requirement while still allowing the fleet to scale in and out.

NEW QUESTION # 486
A security engineer determined that an existing application retrieves credentials to an Amazon RDS for MySQL database from an encrypted file in Amazon S3. For the next version of the application, the security engineer wants to implement the following application design changes to improve security:
The database must use strong, randomly generated passwords stored in a secure AWS managed service.
The application resources must be deployed through AWS CloudFormation.
The application must rotate credentials for the database every 90 days.
A solutions architect will generate a CloudFormation template to deploy the application.
Which resources specified in the CloudFormation template will meet the security engineer's requirements with the LEAST amount of operational overhead?

A. Generate the database password as a SecureString parameter type using AWS Systems Manager Parameter Store. Create an AWS Lambda function resource to rotate the database password. Specify a Parameter Store RotationSchedule resource to rotate the database password every 90 days.
B. Generate the database password as a secret resource using AWS Secrets Manager. Create an AWS Lambda function resource to rotate the database password. Create an Amazon EventBridge scheduled rule resource to trigger the Lambda function password rotation every 90 days.
C. Generate the database password as a secret resource using AWS Secrets Manager. Create an AWS Lambda function resource to rotate the database password. Specify a Secrets Manager RotationSchedule resource to rotate the database password every 90 days.
D. Generate the database password as a SecureString parameter type using AWS Systems Manager Parameter Store. Specify an AWS AppSync DataSource resource to automatically rotate the database password every 90 days.

Answer: A

Explanation:
Explanation
https://aws.amazon.com/blogs/security/how-to-securely-provide-database-credentials-to-lambda-functions-by-us
https://docs.aws.amazon.com/secretsmanager/latest/userguide/rotating-secrets.html
https://docs.aws.amazon.com/secretsmanager/latest/userguide/integrating_cloudformation.html

NEW QUESTION # 487
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