AWS Certified Solutions Architect – Professional (SAP-C02) — Question 435

A flood monitoring agency has deployed more than 10,000 water-level monitoring sensors. Sensors send continuous data updates, and each update is less than 1 MB in size. The agency has a fleet of on-premises application servers. These servers receive updates from the sensors, convert the raw data into a human readable format, and write the results to an on-premises relational database server. Data analysts then use simple SQL queries to monitor the data.

The agency wants to increase overall application availability and reduce the effort that is required to perform maintenance tasks. These maintenance tasks, which include updates and patches to the application servers, cause downtime. While an application server is down, data is lost from sensors because the remaining servers cannot handle the entire workload.

The agency wants a solution that optimizes operational overhead and costs. A solutions architect recommends the use of AWS IoT Core to collect the sensor data.

What else should the solutions architect recommend to meet these requirements?

Answer options

• A. Send the sensor data to Amazon Kinesis Data Firehose. Use an AWS Lambda function to read the Kinesis Data Firehose data, convert it to .csv format, and insert it into an Amazon Aurora MySQL DB instance. Instruct the data analysts to query the data directly from the DB instance.
• B. Send the sensor data to Amazon Kinesis Data Firehose. Use an AWS Lambda function to read the Kinesis Data Firehose data, convert it to Apache Parquet format, and save it to an Amazon S3 bucket. Instruct the data analysts to query the data by using Amazon Athena.
• C. Send the sensor data to an Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) application to convert the data to .csv format and store it in an Amazon S3 bucket. Import the data into an Amazon Aurora MySQL DB instance. Instruct the data analysts to query the data directly from the DB instance.
• D. Send the sensor data to an Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) application to convert the data to Apache Parquet format and store it in an Amazon S3 bucket. Instruct the data analysts to query the data by using Amazon Athena.

Correct answer: B

Explanation

Option B is correct because Amazon Kinesis Data Firehose, AWS Lambda, Amazon S3, and Amazon Athena represent a fully serverless, highly available, and cost-efficient architecture that minimizes operational overhead. Storing the data in Apache Parquet format on S3 and querying it with Athena optimizes query performance and significantly reduces costs compared to maintaining a relational database like Amazon Aurora (Options A and C). Using Amazon Managed Service for Apache Flink (Options C and D) is unnecessary and adds extra cost and complexity for simple data format conversion tasks that can be easily handled by Lambda.