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Amazon AWS-Solutions-Architect-Professional Exam Overview:

Certification Vendor:	Amazon Web Services (AWS)
Exam Name:	AWS Certified Solutions Architect - Professional
Exam Number:	SAP-C02
Available Languages:	English, Korean, Japanese, Simplified Chinese
Real Exam Qty:	Approximately 75 questions
Exam Format:	Multiple response, Multiple choice
Certificate Validity Period:	3 years
Exam Price:	$300 USD
Passing Score:	750 (scaled score out of 1000)
Related Certifications:	AWS Certified Solutions Architect – Associate
Exam Duration:	180 minutes
Recommended Training:	AWS Skill Builder Learning Path AWS Certified Solutions Architect – Professional Exam Readiness
Exam Registration:	AWS Training and Certification Portal AWS Certification Official Registration
Sample Questions:	Amazon AWS-Solutions-Architect-Professional Sample Questions
Exam Way:	Online proctored or test center (onsite)
Pre Condition:	Recommended: AWS Certified Solutions Architect – Associate certification and at least 1+ years of experience designing distributed systems on AWS.
Official Syllabus URL:	https://aws.amazon.com/certification/certified-solutions-architect-professional/

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Achieving the AWS Certified Solutions Architect – Professional certification can be a significant career milestone for professionals in the cloud computing industry. It demonstrates a high level of expertise and can lead to new job opportunities and higher salaries. Additionally, it can help organizations identify and hire top talent with the necessary skills to design and deploy complex systems on AWS.

Amazon AWS Certified Solutions Architect - Professional Sample Questions (Q13-Q18):

NEW QUESTION # 13
A company hosts a web application that tuns on a group of Amazon EC2 instances that ate behind an Application Load Balancer (ALB) in a VPC. The company wants to analyze the network payloads lo reverse-engineer a sophisticated attack of the application.
Which approach should the company take to achieve this goal?

A. Create an AWS WAF web ACL. and associate it with the ALB. Configure AWS WAF logging.
B. Enable VPC Flow Logs. Store the flow logs in an Amazon S3 bucket for analysis.
C. Enable logging for the ALB. Store the logs in an Amazon S3 bucket for analysis.
D. Enable Traffic Mirroring on the network interface of the EC2 instances. Send the mirrored traffic lo a target for storage and analysis.

Answer: D

Explanation:
Explanation
Traffic Mirroring allows to copy network traffic from a network interface to a destination network interface, Amazon EC2 instance or Amazon S3 bucket. The company can use Traffic Mirroring to analyze network payloads, detect sophisticated attacks and reverse-engineer the same.
Reference: AWS Certified Solutions Architect Professional Official Text Book, Chapter 9: Networking and Content Delivery, section: VPC Traffic Mirroring

NEW QUESTION # 14
A company wants to migrate an Amazon Aurora MySQL DB cluster from an existing AWS account to a new AWS account in the same AWS Region. Both accounts are members of the same organization in AWS Organizations.
The company must minimize database service interruption before the company performs DNS cutover to the new database.
Which migration strategy will meet this requirement?

A. Create an Aurora DB cluster in the new AWS account. Use AWS Database Migration Service (AWS DMS) to migrate data between the two Aurora DB clusters.
B. Create an Aurora DB cluster in the new AWS account. Use AWS Application Migration Service to migrate data between the two Aurora DB clusters.
C. Take a snapshot of the existing Aurora database. Share the snapshot with the new AWS account. Create an Aurora DB cluster in the new account from the snapshot.
D. Use AWS Backup to share an Aurora database backup from the existing AWS account to the new AWS account. Create an Aurora DB cluster in the new AWS account from the snapshot.

Answer: A

Explanation:
The best migration strategy to meet the requirement of minimizing database service interruption before the DNS cutover is to use AWS DMS to migrate data between the two Aurora DB clusters. AWS DMS can perform continuous replication of data with high availability and consolidate databases into a petabyte-scale data warehouse by streaming data to Amazon Redshift and Amazon S31. AWS DMS supports homogeneous migrations such as migrating from one Aurora MySQL DB cluster to another, as well as heterogeneous migrations between different database platforms2. AWS DMS also supports cross-account migrations, as long as the source and target databases are in the same AWS Region3.
The other options are not optimal for the following reasons:
Option A: Taking a snapshot of the existing Aurora database and restoring it in the new account would require a downtime during the snapshot and restore process, which could be significant for large databases. Moreover, any changes made to the source database after the snapshot would not be replicated to the target database, resulting in data inconsistency4.
Option C: Using AWS Backup to share an Aurora database backup from the existing AWS account to the new AWS account would have the same drawbacks as option A, as AWS Backup uses snapshots to create backups of Aurora databases.
Option D: Using AWS Application Migration Service to migrate data between the two Aurora DB clusters is not a valid option, as AWS Application Migration Service is designed to migrate applications, not databases, to AWS. AWS Application Migration Service can migrate applications from on-premises or other cloud environments to AWS, using agentless or agent-based methods.
References:
1: What Is AWS Database Migration Service? - AWS Database Migration Service
2: Sources for Data Migration - AWS Database Migration Service
3: AWS Database Migration Service FAQs
4: Working with DB Cluster Snapshots - Amazon Aurora
[Backing Up and Restoring an Amazon Aurora DB Cluster - Amazon Aurora]
[What is AWS Application Migration Service? - AWS Application Migration Service]

NEW QUESTION # 15
A company has an application that runs on a fleet of Amazon EC2 instances and stores 70 GB of device data for each instance in Amazon S3. Recently, some of the S3 uploads have been failing At the same time, the company is seeing an unexpected increase in storage data costs. The application code cannot be modified What is the MOST efficient way to upload the device data to Amazon S3 while managing storage costs?

A. Upload device data using a multipart upload Use the AWS CLI to list incomplete parts to address the failed S3 uploads Enable the lifecycle policy for the incomplete multipart uploads on the S3 bucket to delete the old uploads and prevent new failed uploads from accumulating
B. Upload device data using S3 Transfer Acceleration Use the AWS Management Console to address the failed S3 uploads Use the Multi-Object Delete operation nightly to delete the old uploads
C. Upload device data using a multipart upload Use the AWS Management Console to list incomplete parts to address the failed S3 uploads Configure a lifecycle policy to archive continuously to Amazon S3 Glacier.
D. Upload device data using S3 Transfer Acceleration Use the AWS Management Console to list incomplete parts to address the failed S3 uploads Enable the lifecycle policy for the incomplete multipart uploads on the S3 bucket to delete the old uploads and prevent new failed uploads from accumulating

Answer: B

NEW QUESTION # 16
A company consists of two separate business units. Each business unit has its own AWS account within a single organization in AWS Organizations. The business units regularly share sensitive documents with each other. To facilitate sharing, the company created an Amazon S3 bucket in each account and configured two-way replication between the S3 buckets. The S3 buckets have millions of objects.
Recently, a security audit identified that neither S3 bucket has encryption at rest enabled. Company policy requires that all documents must be stored with encryption at rest. The company wants to implement server-side encryption with Amazon S3 managed encryption keys (SSE-S3).
What is the MOST operationally efficient solution that meets these requirements?

A. Create an AWS Key Management Service (AWS KMS) key in each account. Turn on server-side encryption with AWS KMS keys (SSE-KMS) on each S3 bucket by using the corresponding KMS key in that AWS account. Encrypt the existing objects by using an S3 copy command in the AWS CLI.
B. Create an AWS Key Management Service (AWS KMS) key in each account. Turn on server-side encryption with AWS KMS keys (SSE-KMS) on each S3 bucket by using the corresponding KMS key in that AWS account. Use S3 Batch Operations to copy the objects into the same location.
C. Turn on SSE-S3 on both S3 buckets. Use S3 Batch Operations to copy and encrypt the objects in the same location.
D. Turn on SSE-S3 on both S3 buckets. Encrypt the existing objects by using an S3 copy command in the AWS CLI.

Answer: C

Explanation:
"The S3 buckets have millions of objects" If there are million of objects then you should use Batch operations.
https://aws.amazon.com/blogs/storage/encrypting-objects-with-amazon-s3-batch-operations/

NEW QUESTION # 17
A Solutions Architect is designing a system that will collect and store data from 2,000 internet-connected sensors. Each sensor produces 1 KB of data every second. The data must be available for analysis within a few seconds of it being sent to the system and stored for analysis indefinitely.
Which is the MOST cost-effective solution for collecting and storing the data?

A. Put each record into an object in Amazon S3 with a prefix what organizes the records by hour and hashes the record's key. Use S3 lifecycle management to transition objects to S3 infrequent access storage to reduce storage costs. Analyze recent and historical data by accessing the data in Amazon S3
B. Put each record in Amazon Kinesis Data Streams. Set up Amazon Kinesis Data Firehouse to read records from the stream and group them into objects in Amazon S3. Analyze recent data from Kinesis Data Streams and historical data from Amazon S3.
C. Put each record into an Amazon DynamoDB table. Analyze the recent data by querying the table. Use an AWS Lambda function connected to a DynamoDB stream to group records together, write them into objects in Amazon S3, and then delete the record from the DynamoDB table. Analyze recent data from the DynamoDB table and historical data from Amazon S3
D. Put each record in Amazon Kinesis Data Streams. Use an AWS Lambda function to write each record to an object in Amazon S3 with a prefix that organizes the records by hour and hashes the record's key.
Analyze recent data from Kinesis Data Streams and historical data from Amazon S3.

Answer: C

NEW QUESTION # 18
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