Amazon Web Services spoto sure Pass Exam Sap-c02 Pdf by Milly q126 vce pdf

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Exam Name:	AWS Certified Solutions Architect - Professional
Exam Code:	SAP-C02 Dumps
Vendor:	Amazon Web Services	Certification:	AWS Certified Professional
Questions:	674 Q&A's	Shared By:	milly

Question 84

A company wants to migrate its data analytics environment from on premises to AWS The environment consists of two simple Node js applications One of the applications collects sensor data and loads it into a MySQL database The other application aggregates the data into reports When the aggregation jobs run. some of the load jobs fail to run correctly

The company must resolve the data loading issue The company also needs the migration to occur without interruptions or changes for the company ' s customers

What should a solutions architect do to meet these requirements?

Options:

Set up an Amazon Aurora MySQL database as a replication target for the on-premises database Create an Aurora Replica for the Aurora MySQL database, and move the aggregation jobs to run against the Aurora Replica Set up collection endpomts as AWS Lambda functions behind a Network Load Balancer (NLB). and use Amazon RDS Proxy to wnte to the Aurora MySQL database When the databases are synced disable the replication job and restart the Aurora

Set up an Amazon Aurora MySQL database Use AWS Database Migration Service (AWS DMS) to perform continuous data replication from the on-premises database to Aurora Move the aggregation jobs to run against the Aurora MySQL database Set up collection endpomts behind an Application Load Balancer (ALB) as Amazon EC2 instances in an Auto Scaling group When the databases are synced, point the collector DNS record to the ALB Disable the AWS DMS syn

Set up an Amazon Aurora MySQL database Use AWS Database Migration Service (AWS DMS) to perform continuous data replication from the on-premises database to Aurora Create an AuroraReplica for the Aurora MySQL database and move the aggregation jobs to run against the Aurora Replica Set up collection endpoints as AWS Lambda functions behind an Application Load Balancer (ALB) and use Amazon RDS Proxy to write to the Aurora MySQL database When t

Set up an Amazon Aurora MySQL database Create an Aurora Replica for the Aurora MySQL database and move the aggregation jobs to run against the Aurora Replica Set up collection endpoints as an Amazon Kinesis data stream Use Amazon Kinesis Data Firehose to replicate the data to the Aurora MySQL database When the databases are synced disable the replication job and restart the Aurora Replica as the primary instance Point the collector DNS reco

Discussion

Question 85

A retail business runs an orders and payments solution that uses more than 100 AWS Lambda functions that are written in Python. As the company ' s product catalog grows, the company observes that many of the functions time out. The company reconfigures the functions to have the maximum available timeout values, and the company increases memory for the functions. However, the functions continue to time out.

The company investigates the timeout issue and finds that most failures occur when several functions have been chained together, which results in the initial function timing out while it waits for responses. A solutions architect must resolve these timeout issues while maintaining the cost and operational benefits of using Lambda functions.

Which solution will meet these requirements with the MINIMUM amount of application changes?

Options:

Convert the solution to run in containers. Deploy an Amazon EKS cluster and enable auto scaling for the containers.

Rewrite the Lambda functions in Java. Implement Amazon SQS queues between functions.

Convert the solution to use an AWS Step Functions workflow to invoke the Lambda functions. Remove the direct function-to-function invocations.

Combine groups of linked functions together in a single container image. Deploy the container by using Amazon ECS on Amazon EC2 Spot Instances.

Discussion

Answer:

Explanation:

C is correct because the root cause is synchronous chaining of Lambda functions that causes the initial function to wait and time out. AWS Step Functions is designed to orchestrate multiple steps (including Lambda invocations) with managed state, retries, and timeouts at the workflow level. By moving the chaining logic into a Step Functions state machine and removing direct function-to-function invocations, the initial Lambda no longer needs to remain running while waiting for downstream functions. Step Functions can coordinate the sequence (or parallel branches), handle transient failures with retries/backoff, and maintain execution state without requiring a long-lived “waiting” Lambda invocation. This resolves timeouts while preserving the operational and cost advantages of a serverless Lambda-based architecture and typically requires minimal code change compared to rewriting or migrating platforms.

Why the other options are incorrect:

A: Migrating to containers/EKS is a major architectural change and increases operational overhead, violating “minimum application changes” and the desire to keep Lambda benefits.

B: Rewriting in Java is extensive and unnecessary. Adding SQS between functions changes invocation style and error handling and still requires significant redesign (and does not inherently solve orchestration/branching as cleanly as Step Functions).

D: Grouping functions into containers and running on ECS Spot changes the compute model and introduces more operational overhead and larger application changes than adopting Step Functions.

[References:, AWS Step Functions Documentation: workflow orchestration for Lambda, managed state, retries, error handling, and long-running coordination without keeping a Lambda function running, AWS Lambda Documentation: timeout behavior and best practices for designing asynchronous and orchestrated serverless workflows, AWS Well-Architected Framework (Operational Excellence / Reliability): using managed orchestration for complex workflows, reducing tight coupling, and improving resilience, AWS Certified Solutions Architect – Professional (SAP-C02) Exam Guide: designing scalable serverless architectures and selecting Step Functions for multi-step workflows, , , , , ]

Question 86

A company has migrated its forms-processing application to AWS. When users interact with the application, they upload scanned forms as files through a web application. A database stores user metadata and references to files that are stored in Amazon S3. The web application runs on Amazon EC2 instances and an Amazon RDS for PostgreSQL database.

When forms are uploaded, the application sends notifications to a team through Amazon Simple Notification Service (Amazon SNS). A team member then logs in and processes each form. The team member performs data validation on the form and extracts relevant data before entering the information into another system that uses an API.

A solutions architect needs to automate the manual processing of the forms. The solution must provide accurate form extraction, minimize time to market, and minimize long-term operational overhead.

Which solution will meet these requirements?

Options:

Develop custom libraries to perform optical character recognition (OCR) on the forms. Deploy the libraries to an Amazon Elastic Kubernetes Service (Amazon EKS) cluster as an application tier. Use this tier to process the forms when forms are uploaded. Store the output in Amazon S3. Parse this output by extracting the data into an Amazon DynamoDB table. Submit the data to the target system ' s API. Host the new application tier on EC2 instan

Extend the system with an application tier that uses AWS Step Functions and AWS Lambda. Configure this tier to use artificial intelligence and machine learning (AI/ML) models that are trained and hosted on an EC2 instance to perform optical character recognition (OCR) on the forms when forms are uploaded. Store the output in Amazon S3. Parse this output by extracting the data that is required within the application tier. Submit the data to

Host a new application tier on EC2 instances. Use this tier to call endpoints that host artificial intelligence and machine learning (Al/ML) models that are trained and hosted in Amazon SageMaker to perform optical character recognition (OCR) on the forms. Store the output in Amazon ElastiCache. Parse this output by extracting the data that is required within the application tier. Submit the data to the target system ' s API.

Extend the system with an application tier that uses AWS Step Functions and AWS Lambda. Configure this tier to use Amazon Textract and Amazon Comprehend to perform optical character recognition (OCR) on the forms when forms are uploaded. Store the output in Amazon S3. Parse this output by extracting the data that is required within the application tier. Submit the data to the target system ' s API.

Discussion

Question 87

A retail company is operating its ecommerce application on AWS. The application runs on Amazon EC2 instances behind an Application Load Balancer (ALB). The company uses an Amazon RDS DB instance as the database backend. Amazon CloudFront is configured with one origin that points to the ALB. Static content is cached. Amazon Route 53 is used to host all public zones.

After an update of the application, the ALB occasionally returns a 502 status code (Bad Gateway) error. The root cause is malformed HTTP headers that are returned to the ALB. The webpage returns successfully when a solutions architect reloads the webpage immediately after the error occurs.

While the company is working on the problem, the solutions architect needs to provide a custom error page instead of the standard ALB error page to visitors.

Which combination of steps will meet this requirement with the LEAST amount of operational overhead? (Choose two.)

Options:

Create an Amazon S3 bucket. Configure the S3 bucket to host a static webpage. Upload the custom error pages to Amazon S3.

Create an Amazon CloudWatch alarm to invoke an AWS Lambda function if the ALB health check response Target.FailedHealthChecks is greater than 0. Configure the Lambda function to modify the forwarding rule at the ALB to point to a publicly accessible web server.

Modify the existing Amazon Route 53 records by adding health checks. Configure a fallback target if the health check fails. Modify DNS records to point to a publicly accessible webpage.

Create an Amazon CloudWatch alarm to invoke an AWS Lambda function if the ALB health check response Elb.InternalError is greater than 0. Configure the Lambda function to modify the forwarding rule at the ALB to point to a public accessible web server.

Add a custom error response by configuring a CloudFront custom error page. Modify DNS records to point to a publicly accessible web page.

Discussion

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