Q10 — AWS DEA-C01 Ch.1

Question 10 of 100 | ← Chapter 1

A manufacturing company collects sensor data from its factory floor to monitor and enhance operational efficiency. The company uses Amazon Kinesis Data Streams to publish the data that the sensors collect to a data stream. Then Amazon Kinesis Data Firehose writes the data to an Amazon S3 bucket. The company needs to display a real-time view of operational efficiency on a large screen in the manufacturing facility. Which solution will meet these requirements with the LOWEST latency?

• A. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Use a connector for Apache Flink to write data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard. ✓
• B. Configure the S3 bucket to send a notification to an AWS Lambda function when any new object is created. Use the Lambda function to publish the data to Amazon Aurora. Use Aurora as a source to create an Amazon QuickSight dashboard.
• C. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Create a new Data Firehose delivery stream to publish data directly to an Amazon Timestream database. Use the Timestream database as a source to create an Amazon QuickSight dashboard.
• D. Use AWS Glue bookmarks to read sensor data from the S3 bucket in real time. Publish the data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard.

Correct Answer: A. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Use a connector for Apache Flink to write data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard.

Explanation

在这个场景中，公司需要从传感器收集数据，并实时显示在制造设施的大屏幕上。考虑到最低延迟的要求，我们需要一个能够快速处理数据流并实时更新数据库的方案。选项A使用AmazonManagedServiceforApacheFlink来处理传感器数据，并将数据写入AmazonTimestream数据库。由于Flink是专为实时数据处理设计的，并且Timestream数据库优化了时间序列数据的快速写入和查询，这个方案能够提供最低的延迟。选项B涉及S3桶的通知、Lambda函数和Aurora数据库，这增加了处理链的复杂性和延迟。选项C虽然也使用了Flink和Timestream，但引入了一个额外的DataFirehose交付流，这可能会增加延迟。选项D使用AWSGlue书签从S3桶读取数据，这可能不是实时读取的最佳选择，因为Glue主要用于批量数据处理。综上所述，选项A提供了从数据处理到实时显示的最低延迟路径，因此是正确答案。