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Test SAP-C02 Pattern | Cheap SAP-C02 Dumps

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Amazon SAP-C02 is a certification exam that tests the knowledge and skills of an individual in designing and deploying AWS solutions using best practices and architectural principles. It is intended for professionals who have experience in the field of AWS solutions architecture and want to validate their skills and knowledge. Passing the SAP-C02 Exam demonstrates that an individual has the ability to design and deploy scalable, highly available, and fault-tolerant systems on AWS.

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Quiz 2026 Amazon SAP-C02 – Newest Test Pattern

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Amazon SAP-C02 certification exam is a highly sought-after credential for professionals who specialize in cloud computing and solutions architecture. AWS Certified Solutions Architect - Professional (SAP-C02) certification is designed to validate an individual's expertise in designing and deploying scalable, highly available, and fault-tolerant systems on the Amazon Web Services (AWS) platform. SAP-C02 exam is designed to test the candidate's knowledge and skills in various domains, such as designing and deploying scalable and highly available systems, migration of complex multi-tier applications, implementation of AWS services, and more.

Amazon SAP-C02 Exam is an advanced certification for IT professionals who want to demonstrate their expertise in designing and deploying scalable, fault-tolerant, and highly available systems on the Amazon Web Services (AWS) platform. SAP-C02 exam is intended for individuals who have already obtained the AWS Certified Solutions Architect – Associate certification and have at least two years of experience in designing and deploying AWS-based applications.

Amazon AWS Certified Solutions Architect - Professional (SAP-C02) Sample Questions (Q26-Q31):

NEW QUESTION # 26
A company processes environment data. The has a set up sensors to provide a continuous stream of data from different areas in a city. The data is available in JSON format.
The company wants to use an AWS solution to send the data to a database that does not require fixed schemas for storage. The data must be send in real time.
Which solution will meet these requirements?

A. Use Amazon Kinesis Data firehouse to send the data to Amazon Keyspaces (for Apache Cassandra).
B. Use Amazon Kinesis Data streams to send the data to Amazon DynamoDB.
C. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to send the data to Amazon Aurora.
D. Use Amazon Kinesis Data Firehouse to send the data to Amazon Redshift.

Answer: B

Explanation:
Explanation
Amazon Kinesis Data Streams is a service that enables real-time data ingestion and processing. Amazon DynamoDB is a NoSQL database that does not require fixed schemas for storage. By using Kinesis Data Streams and DynamoDB, the company can send the JSON data to a database that can handle schemaless data in real time. References:
https://docs.aws.amazon.com/streams/latest/dev/introduction.html
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Introduction.html

NEW QUESTION # 27
A data analytics company has an Amazon Redshift cluster that consists of several reserved nodes. The cluster is experiencing unexpected bursts of usage because a team of employees is compiling a deep audit analysis report. The queries to generate the report are complex read queries and are CPU intensive.
Business requirements dictate that the cluster must be able to service read and write queries at all times. A solutions architect must devise a solution that accommodates the bursts of usage.
Which solution meets these requirements MOST cost-effectively?

A. Provision an Amazon EMR cluster Offload the complex data processing tasks.
B. Deploy an AWS Lambda function to add capacity to the Amazon Redshift cluster by using an elastic resize operation when the cluster's CPU metrics in Amazon CloudWatch reach 80%.
C. Deploy an AWS Lambda function to add capacity to the Amazon Redshift cluster by using a classic resize operation when the cluster's CPU metrics in Amazon CloudWatch reach 80%.
D. Turn on the Concurrency Scaling feature for the Amazon Redshift cluster.

Answer: D

Explanation:
The most cost-effective solution for addressing bursts of usage and accommodating complex queries in Amazon Redshift is to turn on the Concurrency Scaling feature for the Amazon Redshift cluster.

NEW QUESTION # 28
A company has a web application that securely uploads pictures and videos to an Amazon S3 bucket. The company requires that only authenticated users are allowed to post content. The application generates a presigned URL that is used to upload objects through a browser interface. Most users are reporting slow upload times for objects larger than 100 MB.
What can a Solutions Architect do to improve the performance of these uploads while ensuring only authenticated users are allowed to post content?

A. Set up an Amazon API Gateway with a regional API endpoint that has a resource as an S3 service proxy. Configure the PUT method for this resource to expose the S3 PutObject operation. Secure the API Gateway using an AWS Lambda authorizer. Have the browser interface use API Gateway instead of the presigned URL to upload API objects.
B. Configure an Amazon CloudFront distribution for the destination S3 bucket. Enable PUT and POST methods for the CloudFront cache behavior. Update the CloudFront origin to use an origin access identity (OAI). Give the OAI user s3:PutObject permissions in the bucket policy. Have the browser interface upload objects using the CloudFront distribution
C. Set up an Amazon API Gateway with an edge-optimized API endpoint that has a resource as an S3 service proxy. Configure the PUT method for this resource to expose the S3 PutObject operation.
Secure the API Gateway using a COGNITO_USER_POOLS authorizer. Have the browser interface use API Gateway instead of the presigned URL to upload objects.
D. Enable an S3 Transfer Acceleration endpoint on the S3 bucket. Use the endpoint when generating the presigned URL. Have the browser interface upload the objects to this URL using the S3 multipart upload API.

Answer: D

Explanation:
S3 Transfer Acceleration is a feature that enables fast, easy, and secure transfers of files over long distances between your client and an S3 bucket1. It works by leveraging the CloudFront edge network to route your requests to S3 over an optimized network path1. By using a Transfer Acceleration endpoint when generating a presigned URL, you can allow authenticated users to upload objects fasterand more reliably2. Additionally, using the S3 multipart upload API can improve the performance of large object uploads by breaking them into smaller parts and uploading them in parallel3.
S3 Transfer Acceleration
Using Transfer Acceleration with presigned URLs
Uploading objects using multipart upload API

NEW QUESTION # 29
A retail company needs to provide a series of data files to another company, which is its business partner These files are saved in an Amazon S3 bucket under Account A. which belongs to the retail company. The business partner company wants one of its 1AM users. User_DataProcessor. to access the files from its own AWS account (Account B).
Which combination of steps must the companies take so that User_DataProcessor can access the S3 bucket successfully? (Select TWO.)

A. C. In Account A. set the S3 bucket policy to the following:
B. Turn on the cross-origin resource sharing (CORS) feature for the S3 bucket in Account
C. E. In Account Bt set the permissions of User_DataProcessor to the following:
D. D. In Account B. set the permissions of User_DataProcessor to the following:
E. In Account A. set the S3 bucket policy to the following:

Answer: A,D

Explanation:
https://aws.amazon.com/premiumsupport/knowledge-center/cross-account-access-s3/

NEW QUESTION # 30
A life sciences company is using a combination of open source tools to manage data analysis workflows and Docker containers running on servers in its on-premises data center to process genomics data Sequencing data is generated and stored on a local storage area network (SAN), and then the data is processed. The research and development teams are running into capacity issues and have decided to re-architect their genomics analysis platform on AWS to scale based on workload demands and reduce the turnaround time from weeks to days The company has a high-speed AWS Direct Connect connection Sequencers will generate around 200 GB of data for each genome, and individual jobs can take several hours to process the data with ideal compute capacity. The end result will be stored in Amazon S3. The company is expecting 10-15 job requests each day Which solution meets these requirements?

A. Use AWS Data Pipeline to transfer the sequencing data to Amazon S3 Use S3 events to trigger an Amazon EC2 Auto Scaling group to launch custom-AMI EC2 instances running the Docker containers to process the data
B. Use regularly scheduled AWS Snowball Edge devices to transfer the sequencing data into AWS When AWS receives the Snowball Edge device and the data is loaded into Amazon S3 use S3 events to trigger an AWS Lambda function to process the data
C. Use an AWS Storage Gateway file gateway to transfer the sequencing data to Amazon S3 Use S3 events to trigger an AWS Batch job that runs on Amazon EC2 instances running the Docker containers to process the data
D. Use AWS DataSync to transfer the sequencing data to Amazon S3 Use S3 events to trigger an AWS Lambda function that starts an AWS Step Functions workflow Store the Docker images in Amazon Elastic Container Registry (Amazon ECR) and trigger AWS Batch to run the container and process the sequencing data

Answer: D

Explanation:
Explanation
AWS DataSync can be used to transfer the sequencing data to Amazon S3, which is a more efficient and faster method than using Snowball Edge devices. Once the data is in S3, S3 events can trigger an AWS Lambda function that starts an AWS Step Functions workflow. The Docker images can be stored in Amazon Elastic Container Registry (Amazon ECR) and AWS Batch can be used to run the container and process the sequencing data.

NEW QUESTION # 31
......

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