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| Section | Weight | Objectives |
|---|---|---|
| Design Secure Architectures | 30% | - Design for security and threat detection
|
| Design Resilient Architectures | 26% | - Design for reliability and recovery
|
| Design High-Performing Architectures | 24% | - Design high-performance compute solutions
|
| Design Cost-Optimized Architectures | 20% | - Identify cost-effective storage solutions
|
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NEW QUESTION # 737
A company has an employee web portal. Employees log in to the portal to view payroll details.
The company is developing a new system to give employees the ability to upload scanned documents for reimbursement. The company runs a program to extract text-based data from the documents and attach the extracted information to each employee's reimbursement IDs for processing. The employee web portal requires 100% uptime. The document extract program runs infrequently throughout the day on an on-demand basis. The company wants to build a scalable and cost-effective new system that will require minimal changes to the existing web portal. The company does not want to make any code changes. Which solution will meet these requirements with the LEAST implementation effort?
Answer: A
Explanation:
This solution offers the most scalable and cost-effective approach with minimal changes to the existing web portal and no code modifications.
Amazon EC2 On-Demand Instances in an Auto Scaling Group: Running the web portal on EC2 On-Demand instances ensures 100% uptime and scalability. The Auto Scaling group will maintain the desired number of instances, automatically scaling up or down as needed, ensuring high availability for the employee web portal.
AWS Lambda for Document Extraction: Lambda is a serverless compute service that allows you to run code in response to events without provisioning or managing servers. By using Lambda to run the document extraction program, you can trigger the function whenever an employee uploads a document. This approach is cost-effective since you only pay for the compute time used by the Lambda function.
No Code Changes Required: This solution integrates with the existing infrastructure with minimal implementation effort and does not require any modifications to the web portal's code.
Why Not Other Options?
Option B (Spot Instances): Spot Instances are not suitable for workloads requiring 100% uptime, as they can be terminated by AWS with short notice.
Option C (Savings Plan): A Savings Plan could reduce costs but does not address the requirement for running the document extraction program efficiently or without code changes.
Option D (S3 with API Gateway and Lambda): This would require significant changes to the existing web portal setup, including moving the portal to S3 and reconfiguring its architecture, which contradicts the requirement of minimal implementation effort and no code changes.
NEW QUESTION # 738
A company is using microservices to build an ecommerce application on AWS. The company wants to preserve customer transaction information after customers submit orders. The company wants to store transaction data in an Amazon Aurora database. The company expects sales volumes to vary throughout each year.
Answer: B
Explanation:
Analysis:
The solution must handle variable sales volumes, preserve transaction information, and store data in an Amazon Aurora database with minimal operational overhead. Using API Gateway, AWS Lambda, and SQS is the best option because it provides scalability, reliability, and resilience.
Why Option A is Correct:
* API Gateway: Serves as an entry point for transaction data in a serverless, scalable manner.
* AWS Lambda: Processes the transactions and sends them to Amazon SQS for queuing.
* Amazon SQS: Buffers the transaction data, ensuring durability and resilience against spikes in transaction volume.
* Second Lambda Function: Processes messages from the SQS queue and updates the Aurora database, decoupling the workflow for better scalability.
* Dead-Letter Queue (DLQ): Ensures failed transactions are logged for later debugging or reprocessing.
Why Other Options Are Not Ideal:
* Option B:
* Using an ALB with ECS on EC2 introduces operational overhead, such as managing EC2 instances and scaling ECS tasks.Not cost-effective.
* Option C:
* EKS is highly operationally intensive and requires Kubernetes cluster management, which is unnecessary for this use case.Too complex.
* Option D:
* Amazon Data Firehose and DMS are not designed for real-time transactional workflows. They are better suited for data analytics pipelines.Not suitable.
AWS References:
* Amazon API Gateway:AWS Documentation - API Gateway
* AWS Lambda:AWS Documentation - Lambda
* Amazon SQS:AWS Documentation - SQS
* Amazon Aurora:AWS Documentation - Aurora
NEW QUESTION # 739
A company has applications that run in an organization in AWS Organizations. The company outsources operational support of the applications. The company needs to provide access for the external support engineers without compromising security.
The external support engineers need access to the AWS Management Console. The external support engineers also need operating system access to the company's fleet of Amazon EC2 instances that run Amazon Linux in private subnets.
Which solution will meet these requirements MOST securely?
Answer: B
Explanation:
This solution provides the most secure access for external support engineers with the least exposure to potential security risks.
AWS Systems Manager (SSM) and Session Manager: Systems Manager Session Manager allows secure and auditable access to EC2 instances without the need to open inbound SSH ports or manage SSH keys. This reduces the attack surface significantly. The SSM Agent must be installed and configured on all instances, and the instances must have an instance profile with the necessary IAM permissions to connect to Systems Manager.
IAM Identity Center: IAM Identity Center provides centralized management of access to the AWS Management Console for external support engineers. By using IAM Identity Center, youcan control console access securely and ensure that external engineers have the appropriate permissions based on their roles.
Why Not Other Options?:
Option B (Local IAM user credentials): This approach is less secure because it involves managing local IAM user credentials and does not leverage the centralized management and security benefits of IAM Identity Center.
Option C (Security group with SSH access): Allowing SSH access opens up the infrastructure to potential security risks, even when restricted by IP addresses. It also requires managing SSH keys, which can be cumbersome and less secure.
Option D (Bastion host): While a bastion host can secure SSH access, it still requires managing SSH keys and opening ports. This approach is less secure and more operationally intensive compared to using Session Manager.
AWS References:
AWS Systems Manager Session Manager- Documentation on using Session Manager for secure instance access.
AWS IAM Identity Center- Overview of IAM Identity Center and its capabilities for managing user access.
NEW QUESTION # 740
A company has stored 10 TB of log files in Apache Parquet format in an Amazon S3 bucket The company occasionally needs to use SQL to analyze the log files Which solution will meet these requirements MOST cost-effectively?
Answer: B
Explanation:
AWS Glue is a serverless data integration service that can crawl, catalog, and prepare data for analysis. AWS Glue can automatically discover the schema and partitioning of the data stored in Apache Parquet format in S3, and create a table in the AWS Glue Data Catalog. Amazon Athena is a serverless interactive query service that can run SQL queries directly on data in S3, without requiring any data loading or transformation. Athena can use the table metadata from the AWS Glue Data Catalog to query the data in S3. By using AWS Glue and Athena, you can analyze the log files in S3 most cost-effectively, as you only pay for the resources consumed by the crawler and the queries, and you do not need to provision or manage any servers or clusters.
References:
AWS Glue
Amazon Athena
Analyzing Data in S3 using Amazon Athena
NEW QUESTION # 741
A gaming company is moving its public scoreboard from a data center to the AWS Cloud. The company uses Amazon EC2 Windows Server instances behind an Application Load Balancer to host its dynamic application. The company needs a highly available storage solution for the application. The application consists of static files and dynamic server-side code.
Which combination of steps should a solutions architect take to meet these requirements? (Select TWO.)
Answer: A,B
Explanation:
A because Elasticache, despite being ideal for leaderboards per Amazon, doesn't cache at edge locations. D because FSx has higher performance for low latency needs.
https://www.techtarget.com/searchaws/tip/Amazon-FSx-vs-EFS-Compare-the-AWS-file-services "FSx is built for high performance and submillisecond latency using solid-state drive storage volumes. This design enables users to select storage capacity and latency independently. Thus, even a subterabyte file system can have 256 Mbps or higher throughput and support volumes up to 64 TB." Amazon S3 is an object storage service that can store static files such as images, videos, documents, etc.
Amazon EFS is a file storage service that can store files in a hierarchical structure and supports NFS protocol.
Amazon FSx for Windows File Server is a file storage service that can store files in a hierarchical structure and supports SMB protocol. Amazon EBS is a block storage service that can store data in fixed-size blocks and attach to EC2 instances.
Based on these definitions, the combination of steps that should be taken to meet the requirements are:
A: Store the static files on Amazon S3. Use Amazon CloudFront to cache objects at the edge. D. Store the server-side code on Amazon FSx for Windows File Server. Mount the FSx for Windows File Server volume on each EC2 instance to share the files.
NEW QUESTION # 742
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