vuthanhdatt's Second Brain

Associate-DEA-C01_28

13 min read

Questions and Answers

Question 4r5fcqVbLrOjfQLtuux9

Question

A company has a production AWS account that runs company workloads. The company’s security team created a security AWS account to store and analyze security logs from the production AWS account. The security logs in the production AWS account are stored in Amazon CloudWatch Logs. The company needs to use Amazon Kinesis Data Streams to deliver the security logs to the security AWS account. Which solution will meet these requirements?

Choices

  • A: Create a destination data stream in the production AWS account. In the security AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the production AWS account.
  • B: Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the security AWS account.
  • C: Create a destination data stream in the production AWS account. In the production AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the security AWS account.
  • D: Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the production AWS account.

Question KLgXUAqR0p6UmCGuHpBf

Question

A company uses Amazon S3 to store semi-structured data in a transactional data lake. Some of the data files are small, but other data files are tens of terabytes. A data engineer must perform a change data capture (CDC) operation to identify changed data from the data source. The data source sends a full snapshot as a JSON file every day and ingests the changed data into the data lake. Which solution will capture the changed data MOST cost-effectively?

Choices

  • A: Create an AWS Lambda function to identify the changes between the previous data and the current data. Configure the Lambda function to ingest the changes into the data lake.
  • B: Ingest the data into Amazon RDS for MySQL. Use AWS Database Migration Service (AWS DMS) to write the changed data to the data lake.
  • C: Use an open source data lake format to merge the data source with the S3 data lake to insert the new data and update the existing data.
  • D: Ingest the data into an Amazon Aurora MySQL DB instance that runs Aurora Serverless. Use AWS Database Migration Service (AWS DMS) to write the changed data to the data lake.

Question 4ajoskCfp3cQI0udeXFx

Question

A data engineer runs Amazon Athena queries on data that is in an Amazon S3 bucket. The Athena queries use AWS Glue Data Catalog as a metadata table. The data engineer notices that the Athena query plans are experiencing a performance bottleneck. The data engineer determines that the cause of the performance bottleneck is the large number of partitions that are in the S3 bucket. The data engineer must resolve the performance bottleneck and reduce Athena query planning time. Which solutions will meet these requirements? (Choose two.)

Choices

  • A: Create an AWS Glue partition index. Enable partition filtering.
  • B: Bucket the data based on a column that the data have in common in a WHERE clause of the user query.
  • C: Use Athena partition projection based on the S3 bucket prefix.
  • D: Transform the data that is in the S3 bucket to Apache Parquet format.
  • E: Use the Amazon EMR S3DistCP utility to combine smaller objects in the S3 bucket into larger objects.

Question uQvw7iigkdZEguu48hkD

Question

A data engineer must manage the ingestion of real-time streaming data into AWS. The data engineer wants to perform real-time analytics on the incoming streaming data by using time-based aggregations over a window of up to 30 minutes. The data engineer needs a solution that is highly fault tolerant. Which solution will meet these requirements with the LEAST operational overhead?

Choices

  • A: Use an AWS Lambda function that includes both the business and the analytics logic to perform time-based aggregations over a window of up to 30 minutes for the data in Amazon Kinesis Data Streams.
  • B: Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to analyze the data that might occasionally contain duplicates by using multiple types of aggregations.
  • C: Use an AWS Lambda function that includes both the business and the analytics logic to perform aggregations for a tumbling window of up to 30 minutes, based on the event timestamp.
  • D: Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to analyze the data by using multiple types of aggregations to perform time-based analytics over a window of up to 30 minutes.

Question pV6eYyZ7owMPeqbYAtvw

Question

A company is planning to upgrade its Amazon Elastic Block Store (Amazon EBS) General Purpose SSD storage from gp2 to gp3. The company wants to prevent any interruptions in its Amazon EC2 instances that will cause data loss during the migration to the upgraded storage. Which solution will meet these requirements with the LEAST operational overhead?

Choices

  • A: Create snapshots of the gp2 volumes. Create new gp3 volumes from the snapshots. Attach the new gp3 volumes to the EC2 instances.
  • B: Create new gp3 volumes. Gradually transfer the data to the new gp3 volumes. When the transfer is complete, mount the new gp3 volumes to the EC2 instances to replace the gp2 volumes.
  • C: Change the volume type of the existing gp2 volumes to gp3. Enter new values for volume size, IOPS, and throughput.
  • D: Use AWS DataSync to create new gp3 volumes. Transfer the data from the original gp2 volumes to the new gp3 volumes.

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