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Amazon SAP-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Design for New Solutions	29%	- Design cost-optimized architectures - Design high-performing and scalable solutions - Design secure and resilient architectures - Design for reliability and fault tolerance
Continuous Improvement for Existing Solutions	25%	- Implement monitoring, logging, and observability - Refactor and modernize legacy applications - Apply security best practices and compliance updates - Optimize existing workloads for cost, performance, and security
Design Solutions for Organizational Complexity	26%	- Design hybrid and multi-cloud networking - Design multi-account and multi-region architectures - Design for operational excellence and automation - Design for compliance and governance requirements
Accelerate Workload Migration and Modernization	20%	- Integrate AWS services with existing systems - Develop migration strategies and plans - Migrate applications, data, and infrastructure - Modernize applications and data platforms

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Amazon AWS Certified Solutions Architect - Professional (SAP-C02) Sample Questions (Q531-Q536):

NEW QUESTION # 531
A company has more than 10,000 sensors that send data to an on-premises Apache Kafka server by using the Message Queuing Telemetry Transport (MQTT) protocol. The on-premises Kafka server transforms the data and then stores the results as objects in an Amazon S3 bucket.
Recently, the Kafka server crashed. The company lost sensor data while the server was being restored. A solutions architect must create a new design on AWS that is highly available and scalable to prevent a similar occurrence.
Which solution will meet these requirements?

A. Migrate the on-premises Kafka server to Amazon Managed Streaming for Apache Kafka (Amazon MSK). Create a Network Load Balancer (NLB) that points to the Amazon MSK broker. Enable NLB health checks. Route the sensors to send the data to the NLB.
B. Deploy AWS IoT Core, and launch an Amazon EC2 instance to host the Kafka server. Configure AWS IoT Core to send the data to the EC2 instance. Route the sensors to send the data to AWS IoT Core.
C. Launch two Amazon EC2 instances to host the Kafka server in an active/standby configuration across two Availability Zones. Create a domain name in Amazon Route 53. Create a Route 53 failover policy. Route the sensors to send the data to the domain name.
D. Deploy AWS IoT Core, and connect it to an Amazon Kinesis Data Firehose delivery stream. Use an AWS Lambda function to handle data transformation. Route the sensors to send the data to AWS IoT Core.

Answer: D

Explanation:
Because MSK has Maximum number of client connections 1000 per second and the company has 10,000 sensors, the MSK likely will not be able to handle all connections.
https://docs.aws.amazon.com/msk/latest/developerguide/limits.html

NEW QUESTION # 532
A company runs an application in the cloud that consists of a database and a website. Users can post data to the website, have the data processed, and have the data sent back to them in an email. Data is stored in a MySQL database running on an Amazon EC2 instance. The database is running in a VPC with two private subnets. The website is running on Apache Tomcat in a single EC2 instance in a different VPC with one public subnet. There is a single VPC peering connection between the database and website VPC.
The website has suffered several outages during the last month due to high traffic.
Which actions should a solutions architect take to increase the reliability of the application?
(Choose three.)

A. Migrate the MySQL database to Amazon Aurora with one Aurora Replica.
B. Place the Tomcat server in an Auto Scaling group with multiple EC2 instances behind an Application Load Balancer.
C. Move the Tomcat server to the database VPC.
D. Create an additional public subnet in a different Availability Zone in the website VPC.
E. Provision two NAT gateways in the database VPC.
F. Provision an additional VPC peering connection.

Answer: A,B,D

NEW QUESTION # 533
A media storage application uploads user photos to Amazon S3 for processing by AWS Lambda functions. Application state is stored in Amazon DynamoOB tables. Users are reporting that some uploaded photos are not being processed properly. The application developers trace the logs and find that Lambda is experiencing photo processing issues when thousands of users upload photos simultaneously. The issues are the result of Lambda concurrency limits and the performance of DynamoDB when data is saved.
Which combination of actions should a solutions architect take to increase the performance and reliability of the application? (Select TWO.)

A. Use S3 Transfer Acceleration to provide lower latency to users.
B. Evaluate and adjust the WCUs for the DynamoDB tables.
C. Evaluate and adjust the RCUs for the DynamoDB tables.
D. Add an Amazon ElastiCache layer to increase the performance of Lambda functions.
E. Add an Amazon Simple Queue Service (Amazon SQS) queue and reprocessing logic between Amazon S3 and the Lambda functions.

Answer: B,E

Explanation:
B: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadWriteCapacityMode.html#HowItWorks.requests D: https://aws.amazon.com/blogs/compute/robust-serverless-application-design-with-aws-lambda-dlq/c

NEW QUESTION # 534
A company manufactures smart vehicles. The company uses a custom application to collect vehicle dat a. The vehicles use the MQTT protocol to connect to the application.
The company processes the data in 5-minute intervals. The company then copies vehicle telematics data to on-premises storage. Custom applications analyze this data to detect anomalies.
The number of vehicles that send data grows constantly. Newer vehicles generate high volumes of data. The on-premises storage solution is not able to scale for peak traffic, which results in data loss. The company must modernize the solution and migrate the solution to AWS to resolve the scaling challenges.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use AWS IOT Greengrass to send the vehicle data to Amazon Managed Streaming for Apache Kafka (Amazon MSK). Create an Apache Kafka application to store the data in Amazon S3. Use a pretrained model in Amazon SageMaker to detect anomalies.
B. Use AWS IOT Core to receive the vehicle data. Configure rules to route data to an Amazon Kinesis Data Firehose delivery stream that stores the data in Amazon S3. Create an Amazon Kinesis Data Analytics application that reads from the delivery stream to detect anomalies.
C. Use Amazon MQ for RabbitMQ to collect the vehicle data. Send the data to an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Use Amazon Lookout for Metrics to detect anomalies.
D. Use AWS IOT FleetWise to collect the vehicle data. Send the data to an Amazon Kinesis data stream. Use an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Use the built-in machine learning transforms in AWS Glue to detect anomalies.

Answer: B

Explanation:
Using AWS IoT Core to receive the vehicle data will enable connecting the smart vehicles to the cloud using the MQTT protocol1. AWS IoT Core is a platform that enables you to connect devices to AWS Services and other devices, secure data and interactions, process and act upon device data, and enable applications to interact with devices even when they are offline2. Configuring rules to route data to an Amazon Kinesis Data Firehose delivery stream that stores the data in Amazon S3 will enable processing and storing the vehicle data in a scalable and reliable way3. Amazon Kinesis Data Firehose is a fully managed service that delivers real-time streaming data to destinations such as Amazon S3. Creating an Amazon Kinesis Data Analytics application that reads from the delivery stream to detect anomalies will enable analyzing the vehicle data using SQL queries or Apache Flink applications. Amazon Kinesis Data Analytics is a fully managed service that enables you to process and analyze streaming data using SQL or Java.

NEW QUESTION # 535
An application is deployed on Amazon EC2 instances that run in an Auto Scaling group. The Auto Scaling group configuration uses only one type of instance.
CPU and memory utilization metrics show that the instances are underutilized. A solutions architect needs to implement a solution to permanently reduce the EC2 cost and increase the utilization.
Which solution will meet these requirements with the LEAST number of configuration changes in the future?

A. List instance types that have properties that are similar to the properties that the current instances have. Modify the Auto Scaling group's launch template configuration to use multiple instance types from the list.
B. Use the information about the application's CPU and memory utilization to specify CPU and memory requirements in a new revision of the Auto Scaling group's launch template. Remove the current instance type from the configuration.
C. Create a script that selects the appropriate instance types from the AWS Price List Bulk API. Use the selected instance types to create a new revision of the Auto Scaling group's launch template.
D. Use the information about the application's CPU and memory utilization to select an instance type that matches the requirements. Modify the Auto Scaling group's configuration by adding the new instance type. Remove the current instance type from the configuration.

Answer: B

Explanation:
You change the instance type/size in the launch template not the ASG. ASG can change the min/max size, not instance type.

NEW QUESTION # 536
......

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