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Amazon SAP-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Design solutions for organizational complexity	26%
Accelerate workload migration and modernization	20%
Design for new solutions	29%
Continuous improvement for existing solutions	25%

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Amazon AWS Certified Solutions Architect - Professional (SAP-C02) Sample Questions (Q862-Q867):

NEW QUESTION # 862
A company wants to migrate its workloads from on premises to AWS. The workloads run on Linux and Windows. The company has a large on-premises intra structure that consists of physical machines and VMs that host numerous applications.
The company must capture details about the system configuration. system performance. running processure and network coi.net lions of its o. -premises ,on boards. The company also must divide the on-premises applications into groups for AWS migrations. The company needs recommendations for Amazon EC2 instance types so that the company can run its workloads on AWS in the most cost-effective manner.
Which combination of steps should a solutions architect take to meet these requirements? (Select THREE.)

A. Generate recommended instance types and associated costs by using AWS Migration Hub.
B. Assess the existing applications by installing AWS Application Discovery Agent on the physical machines and VMs.
C. Group servers into applications for migration by using AWS Migration Hub.
D. Group servers into applications for migration by using AWS Systems Manager Application Manager.
E. Assess the existing applications by installing AWS Systems Manager Agent on the physical machines and VMs
F. Import data about server sizes into AWS Trusted Advisor. Follow the recommendations for cost optimization.

Answer: A,B,C

Explanation:
https://docs.aws.amazon.com/application-discovery/latest/userguide/discovery-agent.html https://docs.aws.
amazon.com/migrationhub/latest/ug/ec2-recommendations.html

NEW QUESTION # 863
A company is running an Apache Hadoop cluster on Amazon EC2 instances. The Hadoop cluster stores approximately 100 TB of data for weekly operational reports and allows occasional access for data scientists to retrieve dat a. The company needs to reduce the cost and operational complexity for storing and serving this data.
Which solution meets these requirements in the MOST cost-effective manner?

A. Move the Hadoop cluster from EC2 instances to Amazon EMR. Allow data access patterns to remain the same.
B. Write a script that resizes the EC2 instances to a smaller instance type during downtime and resizes the instances to a larger instance type before the reports are created.
C. Move the data to Amazon S3 and use Amazon Athena to query the data for reports. Allow the data scientists to access the data directly in Amazon S3.
D. Migrate the data to Amazon DynamoDB and modify the reports to fetch data from DynamoDB. Allow the data scientists to access the data directly in DynamoDB.

Answer: C

Explanation:
"The company needs to reduce the cost and operational complexity for storing and serving this data. Which solution meets these requirements in the MOST cost-effective manner?" EMR storage is ephemeral. The company has 100TB that need to persist, they would have to use EMRFS to backup to S3 anyway. https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-plan-storage.html
100TB
EBS - 8.109$
S3 - 2.355$
You have saved 5.752$
This amount can be used for Athen. BTW. we don't know indexes, amount of data that is scanned. What we know is that tit will be: "occasional access for data scientists to retrieve data"

NEW QUESTION # 864
A company is building a software-as-a-service (SaaS) solution on AWS. The company has deployed an Amazon API Gateway REST API with AWS Lambda integration in multiple AWS Regions and in the same production account. The company offers tiered pricing that gives customers the ability to pay for the capacity to make a certain number of API calls per second.
The premium tier offers up to 3,000 calls per second, and customers are identified by a unique API key. Several premium tier customers in various Regions report that they receive error responses of 429 Too Many Requests from multiple API methods during peak usage hours. Logs indicate that the Lambda function is never invoked.
What could be the cause of the error messages for these customers?

A. The Lambda function reached its concurrency limit.
B. The company reached its API Gateway account limit for calls per second.
C. The company reached its API Gateway default per-method limit for calls per second.
D. The Lambda function its Region limit for concurrency.

Answer: B

Explanation:
The company reached its API Gateway account limit for calls per second. This is because Amazon API Gateway has a default account-level limit of 10,000 requests per second (RPS) and a default per-method limit of 5,000 RPS. If the company's premium tier customers are making more than 10,000 requests per second in total across all API methods and regions, they would be receiving the error message of 429 Too Many Requests. This indicates that the API Gateway account is reaching its capacity limit, and the Lambda function is not being invoked because API Gateway is blocking the requests before they reach the Lambda function.
https://docs.aws.amazon.com/apigateway/latest/developerguide/api-gateway-request- throttling.html#apig-request-throttling-account-level-limits

NEW QUESTION # 865
A solutions architect is auditing the security setup of an AWS Lambda function for a company. The Lambda function retrieves the latest changes from an Amazon Aurora database. The Lambda function and the database run in the same VPC. Lambda environment variables are providing the database credentials to the Lambda function.
The Lambda function aggregates data and makes the data available in an Amazon S3 bucket that is configured for server-side encryption with AWS KMS managed encryption keys (SSE-KMS). The data must not travel across the internet. If any database credentials become compromised, the company needs a solution that minimizes the impact of the compromise.
What should the solutions architect recommend to meet these requirements?

A. Save the database credentials in AWS Systems Manager Parameter Store. Set up password rotation on the credentials in Parameter Store. Change the IAM role for the Lambda function to allow the function to access Parameter Store. Modify the Lambda function to retrieve the credentials from Parameter Store.
Deploy a gateway VPC endpoint for Amazon S3 in the VPC.
B. Enable IAM database authentication on the Aurora DB cluster. Change the IAM role for the Lambda function to allow the function to access the database by using IAM database authentication. Deploy a gateway VPC endpoint for Amazon S3 in the VPC.
C. Enable IAM database authentication on the Aurora DB cluster. Change the IAM role for the Lambda function to allow the function to access the database by using IAM database authentication. Enforce HTTPS on the connection to Amazon S3 during data transfers.
D. Save the database credentials in AWS Secrets Manager. Set up password rotation on the credentials in Secrets Manager. Change the IAM role for the Lambda function to allow the function to access Secrets Manager. Modify the Lambda function to retrieve the credentials Om Secrets Manager. Enforce HTTPS on the connection to Amazon S3 during data transfers.

Answer: B

Explanation:
Explanation
https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/UsingWithRDS.IAMDBAuth.html

NEW QUESTION # 866
A company has a sales system that stores transactions as .csv files in an Amazon S3 bucket.
The S3 bucket is configured to use S3 Intelligent-Tiering. Most of the .csv files are between 64 KB and 100 KB in size. All rows and columns of the .csv files must be read when the data is processed. The company must keep the data for 5 years. The company stores several million xsv files every day. The company must minimize the cost of storing and querying the xsv files.
Which solution will meet these requirements?

A. Create an AWS Glue job to compress the .csv files. Schedule the AWS Glue job every hour to compress the files for the previous hour into one .csv file.
B. Create an AWS Lambda function to convert the .csv files into Apache Parquet format. Use Amazon S3 to invoke the Lambda function every time a .csv file arrives.
C. Create an AWS Lambda function to compress the .csv files. Use Amazon S3 to invoke the Lambda function every time a .csv file arrives.
D. Create an AWS Glue job to convert the .csv files into Apache Parquet format. Use Amazon S3 to invoke the AWS Glue job every time a .csv file arrives.

Answer: D

NEW QUESTION # 867
......

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