SAP-C02 第 94 题
题目
A company has migrated Its forms-processing application to AWS. When users interact with the application, they upload scanned forms as files through a web application. A database stores user metadata and references to files that are stored in Amazon S3. The web application runs on Amazon EC2 instances and an Amazon RDS for PostgreSQL database. When forms are uploaded, the application sends notifications to a team through Amazon Simple Notification Service (Amazon SNS). A team member then logs in and processes each form. The team member performs data validation on the form and extracts relevant data before entering the information into another system that uses an API. A solutions architect needs to automate the manual processing of the forms. The solution must provide accurate form extraction. minimize time to market, and minimize tong-term operational overhead. Which solution will meet these requirements?
中文翻译：
一家公司已将其表单处理应用程序迁移到 AWS。当用户与应用程序交互时，他们通过 Web 应用程序将扫描的表单作为文件上传。数据库存储用户元数据以及对 Amazon S3 中存储的文件的引用。 Web 应用程序在 Amazon EC2 实例和 Amazon RDS for PostgreSQL 数据库上运行。上传表单后，应用程序通过 Amazon Simple Notification Service (Amazon SNS) 向团队发送通知。然后，团队成员登录并处理每个表单。团队成员在将信息输入到使用 API 的另一个系统之前，对表单执行数据验证并提取相关数据。解决方案架构师需要自动化表单的手动处理。该解决方案必须提供准确的表单提取。最大限度地缩短上市时间，并最大限度地减少长期运营费用。哪种解决方案可以满足这些要求？
选项
A. Develop custom libraries to perform optical character recognition (OCR) on the forms. Deploy the libraries to an Amazon Elastic Kubernetes Service (Amazon EKS) cluster as an application tier. Use this tier to process the forms when forms are uploaded. Store the output in Amazon S3. Parse this output by extracting the data into an Amazon DynamoDB table. Submit the data to the target system's APL. Host the new application tier on EC2 instances.
中文翻译：
开发自定义库以在表单上执行光学字符识别 (OCR)。将库作为应用程序层部署到 Amazon Elastic Kubernetes Service (Amazon EKS) 集群。上传表单时使用此层处理表单。将输出存储在 Amazon S3 中。通过将数据提取到 Amazon DynamoDB 表中来解析此输出。将数据提交到目标系统的 APL。在 EC2 实例上托管新的应用程序层。
B. Extend the system with an application tier that uses AWS Step Functions and AWS Lambda. Configure this tier to use artificial intelligence and machine learning (AI/ML) models that are trained and hosted on an EC2 instance to perform optical character recognition (OCR) on the forms when forms are uploaded. Store the output in Amazon S3. Parse this output by extracting the data that is required within the application tier. Submit the data to the target system's API.
中文翻译：
通过使用 AWS Step Functions 和 AWS Lambda 的应用程序层扩展系统。配置此层以使用在 EC2 实例上训练和托管的人工智能和机器学习 (AI/ML) 模型，以便在上传表单时对表单执行光学字符识别 (OCR)。将输出存储在 Amazon S3 中。通过提取应用程序层中所需的数据来解析此输出。将数据提交到目标系统的API。
C. Host a new application tier on EC2 instances. Use this tier to call endpoints that host artificial intelligence and machine teaming (AI/ML) models that are trained and hosted in Amazon SageMaker to perform optical character recognition (OCR) on the forms. Store the output in Amazon ElastiCache. Parse this output by extracting the data that is required within the application tier. Submit the data to the target system's API.
中文翻译：
在 EC2 实例上托管新的应用程序层。使用此层调用托管在 Amazon SageMaker 中训练和托管的人工智能和机器组合 (AI/ML) 模型的终端节点，以在表单上执行光学字符识别 (OCR)。将输出存储在 Amazon ElastiCache 中。通过提取应用程序层中所需的数据来解析此输出。将数据提交到目标系统的API。
D. Extend the system with an application tier that uses AWS Step Functions and AWS Lambda. Configure this tier to use Amazon Textract and Amazon Comprehend to perform optical character recognition (OCR) on the forms when forms are uploaded. Store the output in Amazon S3. Parse this output by extracting the data that is required within the application tier. Submit the data to the target system's API.
中文翻译：
通过使用 AWS Step Functions 和 AWS Lambda 的应用程序层扩展系统。配置此层以在上传表单时使用 Amazon Textract 和 Amazon Comprehend 对表单执行光学字符识别 (OCR)。将输出存储在 Amazon S3 中。通过提取应用程序层中所需的数据来解析此输出。将数据提交到目标系统的API。
答案
D
解析
正确答案：D 解析： 本题应选择 D。 正确选项： D. 通过使用 AWS Step Functions 和 AWS Lambda 的应用程序层扩展系统。配置此层以在上传表单时使用 Amazon Textract 和 Amazon Comprehend 对表单执行光学字符识别 (OCR)。将输出存储在 Amazon S3 中。通过提取应用程序层中所需的数据来解析此输出。将数据提交到目标系统的API。 选择理由： 该选项最直接地满足题干中...