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| Certification Vendor: | Amazon AWS |
|---|---|
| Exam Name: | AWS Certified Solutions Architect - Professional |
| Exam Number: | SAP-C02 |
| Passing Score: | 750 (scaled score 100–1000) |
| Certificate Validity Period: | 3 years |
| Available Languages: | Spanish (Latin America), Japanese, Portuguese (Brazil), English, Simplified Chinese, Korean |
| Related Certifications: | AWS Certified Solutions Architect - Associate AWS Certified DevOps Engineer - Professional AWS Certified Security - Specialty |
| Exam Format: | Multiple choice, Scenario-based questions, Multiple response |
| Exam Price: | 300 USD |
| Exam Duration: | 180 minutes |
| Real Exam Qty: | 75 (65 scored, 10 unscored) |
| Recommended Training: | AWS Official Exam Guide AWS Training and Certification |
| Exam Registration: | AWS Official Registration Pearson VUE |
| Sample Questions: | Amazon SAP-C02 Sample Questions |
| Exam Way: | Online proctored or onsite testing at authorized centers (Pearson VUE, PSI) |
| Pre Condition: | No mandatory prerequisites; recommended: 2+ years of hands-on experience designing and implementing cloud solutions on AWS, AWS Certified Solutions Architect - Associate certification |
| Official Syllabus URL: | https://docs.aws.amazon.com/aws-certification/latest/examguides/solutions-architect-professional-02.html |
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To be eligible for the SAP-C02 certification exam, candidates must have a minimum of two years of experience in designing and deploying AWS-based applications. They should also have experience with multiple AWS services, including VPC, EC2, RDS, S3, and Lambda. Additionally, candidates should also have experience with other AWS services, such as CloudFormation, CloudTrail, CloudWatch, and IAM. The SAP-C02 Certification Exam is a challenging exam that requires a deep understanding of AWS services and a mastery of the skills needed to design and deploy enterprise-level solutions in the AWS cloud. Passing this certification exam can be a significant achievement for professionals who want to advance their career in the field of cloud computing.
NEW QUESTION # 233
A solutions architect works for a government agency that has strict disaster recovery requirements. All Amazon Elastic Block Store (Amazon EBS) snapshots are required to be saved in at least two additional AWS Regions. The agency also is required to maintain the lowest possible operational overhead.
Which solution meets these requirements?
Answer: A
NEW QUESTION # 234
A company has a web application that allows users to upload short videos. The videos are stored on Amazon EBS volumes and analyzed by custom recognition software for categorization.
The website contains stat c content that has variable traffic with peaks in certain months. The architecture consists of Amazon EC2 instances running in an Auto Scaling group for the web application and EC2 instances running in an Auto Scaling group to process an Amazon SQS queue The company wants to re-architect the application to reduce operational overhead using AWS managed services where possible and remove dependencies on third-party software.
Which solution meets these requirements?
Answer: A
Explanation:
Explanation
Option C is correct because hosting the web application in Amazon S3, storing the uploaded videos in Amazon S3, and using S3 event notifications to publish events to the SQS queue reduces the operational overhead of managing EC2 instances and EBS volumes. Amazon S3 can serve static content such as HTML, CSS, JavaScript, and media files directly from S3 buckets. Amazon S3 can also trigger AWS Lambda functions through S3 event notifications when new objects are created or existing objects are updated or deleted. AWS Lambda can process the SQS queue with an AWS Lambda function that calls the Amazon Rekognition API to categorize the videos. This solution eliminates the need for custom recognition software and third-party dependencies345 References: 1: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-spot-instances.html 2:
https://aws.amazon.com/efs/pricing/ 3:
https://docs.aws.amazon.com/AmazonS3/latest/userguide/WebsiteHosting.html 4:
https://docs.aws.amazon.com/AmazonS3/latest/userguide/NotificationHowTo.html 5:
https://docs.aws.amazon.com/rekognition/latest/dg/what-is.html 6:
https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/Welcome.html
NEW QUESTION # 235
A company that provisions job boards for a seasonal workforce is seeing an increase in traffic and usage. The backend services run on a pair of Amazon EC2 instances behind an Application Load Balancer with Amazon DynamoDB as the datastore. Application read and write traffic is slow during peak seasons.
Which option provides a scalable application architecture to handle peak seasons with the LEAST development effort?
Answer: A
Explanation:
* Option C is correct because using Auto Scaling groups for the backend services allows the company to scale up or down the number of EC2 instances based on the demand and traffic. This way, the backend services can handle more requests during peak seasons without compromising performance or availability. Using DynamoDB auto scaling allows the company to adjust the provisioned read andwrite capacity of the table or index automatically based on the actual traffic patterns. This way, the table or index can handle sudden increases or decreases in workload without throttling or overprovisioning1.
* Option A is incorrect because migrating the backend services to AWS Lambda may require significant development effort to rewrite the code and test the functionality. Moreover, increasing the read and write capacity of DynamoDB manually may not be efficient or cost-effective, as it does not account for the variability of the workload. The company may end up paying for unused capacity or experiencing throttling if the workload exceeds the provisioned capacity1.
* Option B is incorrect because migrating the backend services to AWS Lambda may require significant development effort to rewrite the code and test the functionality. Moreover, configuring DynamoDB to use global tables may not be necessary or beneficial for the company, as global tables are mainly used for replicating data across multiple AWS Regions for fast local access and disaster recovery. Global tables do not automatically scale the provisioned capacity of each replica table; they still require manual or auto scaling settings2.
* Option D is incorrect because using Amazon Simple Queue Service (Amazon SQS) and an AWS Lambda function to write to DynamoDB may introduce additional complexity and latency to the application architecture. Amazon SQS is a message queue service that decouples and coordinates the components of a distributed system. AWS Lambda is a serverless compute service that runs code in response to events. Using these services may require significant development effort to integrate them with the backend services and DynamoDB. Moreover, they may not improve the read performance of DynamoDB, which may also be affected by high traffic3.
:
Auto Scaling groups
DynamoDB auto scaling
AWS Lambda
DynamoDB global tables
AWS Lambda vs EC2: Comparison of AWS Compute Resources - Simform
Managing throughput capacity automatically with DynamoDB auto scaling - Amazon DynamoDB AWS Aurora Global Database vs. DynamoDB Global Tables Amazon Simple Queue Service (SQS)
NEW QUESTION # 236
A manufacturing company is building an inspection solution for its factory. The company has IP cameras at the end of each assembly line. The company has used Amazon SageMaker to train a machine learning (ML) model to identify common defects from still images.
The company wants to provide local feedback to factory workers when a defect is detected. The company must be able to provide this feedback even if the factory's internet connectivity is down.
The company has a local Linux server that hosts an API that provides local feedback to the workers.
How should the company deploy the ML model to meet these requirements?
Answer: B
Explanation:
AWS IoT Greengrass enables ML inference locally using models that are created, trained, and optimized in the cloud using Amazon SageMaker, AWS Deep Learning AMI, or AWS Deep Learning Containers, and deployed on the edge devices.
https://aws.amazon.com/blogs/machine-learning/anomaly-detection-with-amazon-sagemaker- edge-manager-using-aws-iot-greengrass-v2/
NEW QUESTION # 237
A company is planning to migrate an Amazon RDS for Oracle database to an RDS for PostgreSQL DB instance in another AWS account. A solutions architect needs to design a migration strategy that will require no downtime and that will minimize the amount of time necessary to complete the migration. The migration strategy must replicate all existing data and any new data that is created during the migration The target database must be identical to the source database at completion of the migration process All applications currently use an Amazon Route 53 CNAME record as their endpoint for communication with the RDS for Oracle DB instance The RDS for Oracle DB instance is in a private subnet.
Which combination of steps should the solutions architect take to meet these requirements? (Select THREE)
Answer: A,C,E
NEW QUESTION # 238
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