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Prepare for the Amazon AWS Certified Solutions Architect - Professional Exam exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.
QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Amazon SAP-C02 exam and achieve success.
The questions for SAP-C02 were last updated on Feb 20, 2025.
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An e-commerce company is revamping its IT infrastructure and is planning to use AWS services. The company's CIO has asked a solutions architect to design a simple, highly available, and loosely coupled order processing application. The application is responsible for receiving and processing orders before storing them in an Amazon DynamoDB table. The application has a sporadic traffic pattern and should be able to scale during marketing campaigns to process the orders with minimal delays.
Which of the following is the MOST reliable approach to meet the requirements?
The best option is to use Amazon SQS and AWS Lambda to create a serverless order processing application. Amazon SQS is a fully managed message queue service that can decouple the order receiving and processing components, making the application more scalable and fault-tolerant. AWS Lambda is a serverless compute service that can automatically scale to handle the incoming messages from the SQS queue and process them according to the business logic. AWS Lambda can also integrate with Amazon DynamoDB to store the processed orders in a fast and flexible NoSQL database. This approach eliminates the need to provision, manage, or scale any servers or containers, and reduces the operational overhead and cost.
Option A is not reliable because using an EC2-hosted database to receive the orders introduces a single point of failure and a scalability bottleneck. EC2 instances also require more management and configuration than serverless services.
Option C is not reliable because using AWS Step Functions to receive the orders adds unnecessary complexity and cost to the application. AWS Step Functions is a service that coordinates multiple AWS services into a serverless workflow, but it is not designed to handle high-volume, sporadic, or unpredictable traffic patterns. AWS Step Functions also charges per state transition, which can be expensive for a large number of orders. Launching an ECS container to process each order also requires more resources and management than invoking a Lambda function.
Option D is not reliable because using Amazon Kinesis Data Streams to receive the orders is not suitable for this use case. Amazon Kinesis Data Streams is a service that enables real-time processing of streaming data at scale, but it is not meant for asynchronous message queuing. Amazon Kinesis Data Streams requires consumers to poll the data from the stream, which can introduce latency and complexity. Amazon Kinesis Data Streams also charges per shard hour, which can be expensive for a sporadic traffic pattern.
A company is planning to migrate an application to AWS. The application runs as a Docker container and uses an NFS version 4 file share.
A solutions architect must design a secure and scalable containerized solution that does not require provisioning or management of the underlying infrastructure.
Which solution will meet these requirements?
This option uses Amazon Elastic Container Service (Amazon ECS) with the Fargate launch type to deploy the application containers. Amazon ECS is a fully managed container orchestration service that allows running Docker containers on AWS at scale. Fargate is a serverless compute engine for containers that eliminates the need to provision or manage servers or clusters. With Fargate, the company only pays for the resources required to run its containers, which reduces costs and operational overhead. This option also uses Amazon Elastic File System (Amazon EFS) for shared storage. Amazon EFS is a fully managed file system that provides scalable, elastic, concurrent, and secure file storage for use with AWS cloud services. Amazon EFS supports NFS version 4 protocol, which is compatible with the application's requirements. To use Amazon EFS with Fargate containers, the company needs to reference the EFS file system ID, container mount point, and EFS authorization IAM role in the ECS task definition.
A company is planning a migration from an on-premises data center to the AWS cloud. The company plans to use multiple AWS accounts that are managed in an organization in AWS organizations. The company will cost a small number of accounts initially and will add accounts as needed. A solution architect must design a solution that turns on AWS accounts.
What is the MOST operationally efficient solution that meets these requirements.
The most operationally efficient solution for turning on AWS CloudTrail across multiple AWS accounts managed within an AWS Organization is to create a single CloudTrail trail in the organization's management account and configure it to log events for all accounts within the organization. This approach leverages CloudTrail's ability to consolidate logs from all accounts in an organization, thereby simplifying management, reducing overhead, and ensuring consistent logging across accounts. This method eliminates the need for manual intervention in each account, making it an operationally efficient choice for organizations planning to scale their AWS usage.
AWS CloudTrail Documentation: Provides detailed instructions on setting up CloudTrail, including how to configure it for an organization.
AWS Organizations Documentation: Offers insights into best practices for managing multiple AWS accounts and how services like CloudTrail integrate with AWS Organizations.
AWS Best Practices for Security and Governance: Guides on how to effectively use AWS services to maintain a secure and well-governed AWS environment, with a focus on centralized logging and monitoring.
A company runs a Python script on an Amazon EC2 instance to process dat
a. The script runs every 10minutes. The script ingests files from an Amazon S3 bucket and processes the files. On average, the script takes approximately 5minutes to process each file The script will not reprocess a file that the script has already processed.
The company reviewed Amazon CloudWatch metrics and noticed that the EC2 instance is idle for approximately 40% of the time because of the file processing speed. The company wants to make the workload highly available and scalable. The company also wants to reduce long-term management overhead.
Which solution will meet these requirements MOST cost-effectively?
migrating the data processing script to an AWS Lambda function and using an S3 event notification to invoke the Lambda function to process the objects when the company uploads the objects. This solution meets the company's requirements of high availability and scalability, as well as reducing long-term management overhead, and is likely to be the most cost-effective option.
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?
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.
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