Amazon DBS-C01 Online Practice Questions and Exam Preparation

Amazon DBS-C01 Online Questions & Answers

• Question 131:

  A company is planning to use Amazon RDS for SQL Server for one of its critical applications. The company's security team requires that the users of the RDS for SQL Server DB instance are authenticated with on-premises Microsoft Active Directory credentials.

  Which combination of steps should a database specialist take to meet this requirement? (Choose three.)

  A. Extend the on-premises Active Directory to AWS by using AD Connector.
  B. Create an IAM user that uses the AmazonRDSDirectoryServiceAccess managed IAM policy.
  C. Create a directory by using AWS Directory Service for Microsoft Active Directory.
  D. Create an Active Directory domain controller on Amazon EC2.
  E. Create an IAM role that uses the AmazonRDSDirectoryServiceAccess managed IAM policy.
  F. Create a one-way forest trust from the AWS Directory Service for Microsoft Active Directory directory to the on-premises Active Directory.
  C. Create a directory by using AWS Directory Service for Microsoft Active Directory.
  E. Create an IAM role that uses the AmazonRDSDirectoryServiceAccess managed IAM policy.
  F. Create a one-way forest trust from the AWS Directory Service for Microsoft Active Directory directory to the on-premises Active Directory.

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  Explanation/Reference:

• Question 132:

  A startup company in the travel industry wants to create an application that includes a personal travel assistant to display information for nearby airports based on user location. The application will use Amazon DynamoDB and must be able to access and display attributes such as airline names, arrival times, and flight numbers. However, the application must not be able to access or display pilot names or passenger counts.

  Which solution will meet these requirements MOST cost-effectively?

  A. Use a proxy tier between the application and DynamoDB to regulate access to specific tables, items, and attributes.
  B. Use IAM policies with a combination of IAM conditions and actions to implement fine- grained access control.
  C. Use DynamoDB resource policies to regulate access to specific tables, items, and attributes.
  D. Configure an AWS Lambda function to extract only allowed attributes from tables based on user profiles.
  B. Use IAM policies with a combination of IAM conditions and actions to implement fine- grained access control.

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  Explanation/Reference:

  https://aws.amazon.com/blogs/aws/fine-grained-access-control-for-amazon- dynamodb/

• Question 133:

  A company has applications running on Amazon EC2 instances in a private subnet with no internet connectivity. The company deployed a new application that uses Amazon DynamoDB, but the application cannot connect to the DynamoDB tables. A developer already checked that all permissions are set correctly.

  What should a database specialist do to resolve this issue while minimizing access to external resources?

  A. Add a route to an internet gateway in the subnet's route table.
  B. Add a route to a NAT gateway in the subnet's route table.
  C. Assign a new security group to the EC2 instances with an outbound rule to ports 80 and 443.
  D. Create a VPC endpoint for DynamoDB and add a route to the endpoint in the subnet's route table.
  D. Create a VPC endpoint for DynamoDB and add a route to the endpoint in the subnet's route table.

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  Explanation/Reference:

  https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/vpc- endpoints-dynamodb.html

• Question 134:

  A company is looking to migrate a 1 TB Oracle database from on-premises to an Amazon Aurora PostgreSQL DB cluster. The company's Database Specialist discovered that the Oracle database is storing 100 GB of large binary objects (LOBs) across multiple tables. The Oracle database has a maximum LOB size of 500 MB with an average LOB size of 350 MB. The Database Specialist has chosen AWS DMS to migrate the data with the largest replication instances. How should the Database Specialist optimize the database migration using AWS DMS?

  A. Create a single task using full LOB mode with a LOB chunk size of 500 MB to migrate the data and LOBs together
  B. Create two tasks: task1 with LOB tables using full LOB mode with a LOB chunk size of 500 MB and task2 without LOBs
  C. Create two tasks: task1 with LOB tables using limited LOB mode with a maximum LOB size of 500 MB and task 2 without LOBs
  D. Create a single task using limited LOB mode with a maximum LOB size of 500 MB to migrate data and LOBs together
  C. Create two tasks: task1 with LOB tables using limited LOB mode with a maximum LOB size of 500 MB and task 2 without LOBs

• Question 135:

  A company has a on-premises Oracle Real Application Clusters (RAC) database. The company wants to migrate the database to AWS and reduce licensing costs. The company's application team wants to store JSON payloads that expire after 28 hours. The company has development capacity if code changes are required.

  Which solution meets these requirements?

  A. Use Amazon DynamoDB and leverage the Time to Live (TTL) feature to automatically expire the data.
  B. Use Amazon RDS for Oracle with Multi-AZ. Create an AWS Lambda function to purge the expired data. Schedule the Lambda function to run daily using Amazon EventBridge.
  C. Use Amazon DocumentDB with a read replica in a different Availability Zone. Use DocumentDB change streams to expire the data.
  D. Use Amazon Aurora PostgreSQL with Multi-AZ and leverage the Time to Live (TTL) feature to automatically expire the data.
  A. Use Amazon DynamoDB and leverage the Time to Live (TTL) feature to automatically expire the data.

• Question 136:

  A company's applications store data in Amazon Aurora MySQL DB clusters. The company has separate AWS accounts for its production, test, and development environments. To test new functionality in the test environment, the company's development team requires a copy of the production database four times a day.

  Which solution meets this requirement with the MOST operational efficiency?

  A. Take a manual snapshot in the production account. Share the snapshot with the test account. Restore the database from the snapshot.
  B. Take a manual snapshot in the production account. Export the snapshot to Amazon S3. Copy the snapshot to an S3 bucket in the test account. Restore the database from the snapshot.
  C. Share the Aurora DB cluster with the test account. Create a snapshot of the production database in the test account. Restore the database from the snapshot.
  D. Share the Aurora DB cluster with the test account. Create a clone of the production database in the test account.
  D. Share the Aurora DB cluster with the test account. Create a clone of the production database in the test account.

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  Explanation/Reference:

  https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Managing.Clon e.html https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Managing.Clon e.html#Aurora.Managing.Clone.Cross-Account

• Question 137:

  A company is running a mobile app that has a backend database in Amazon DynamoDB. The app experiences sudden increases and decreases in activity throughout the day. The companys operations team notices that DynamoDB read and write requests are being throttled at different times, resulting in a negative customer experience.

  Which solution will solve the throttling issue without requiring changes to the app?

  A. Add a DynamoD3 table in a secondary AWS Region. Populate the additional table by using DynamoDB Streams.
  B. Deploy an Amazon ElastiCache cluster in front of the DynamoDB table.
  C. use on-demand capacity mode tor the DynamoDB table.
  D. use DynamoDB Accelerator (DAX).
  C. use on-demand capacity mode tor the DynamoDB table.

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  Explanation/Reference:

  Option C is correct because it solves the throttling issue without requiring changes to the app. On-demand capacity mode is a flexible billing option for DynamoDB that automatically accommodates your workload as it ramps up or down. With on- demand mode, you pay per request for the data reads and writes your application performs on your tables, and you don't need to specify how much read and write throughput you expect. On-demand mode can handle sudden increases and decreases in activity without throttling, as long as the request rate does not exceed the default table quotas1. To use on-demand mode, you only need to update the table settings in the AWS Management Console or by using the AWS SDK2. You don't need to modify any application logic, as on-demand mode is compatible with existing DynamoDB API calls.

• Question 138:

  A company has a web-based survey application that uses Amazon DynamoDB. During peak usage, when survey responses are being collected, a Database Specialist sees the ProvisionedThroughputExceededException error.

  What can the Database Specialist do to resolve this error? (Choose two.)

  A. Change the table to use Amazon DynamoDB Streams
  B. Purchase DynamoDB reserved capacity in the affected Region
  C. Increase the write capacity units for the specific table
  D. Change the table capacity mode to on-demand
  E. Change the table type to throughput optimized
  C. Increase the write capacity units for the specific table
  D. Change the table capacity mode to on-demand

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  Explanation/Reference:

  https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/switching.capacity mode.html

• Question 139:

  A company has a web application that uses Amazon API Gateway to route HTTPS requests to AWS Lambda functions. The application uses an Amazon Aurora MySQL database for its data storage. The application has experienced unpredictable surges in traffic that overwhelm the database with too many connection requests. The company needs to implement a scalable solution that is more resilient to database failures as quickly as possible.

  Which solution will meet these requirements MOST cost-effectively?

  A. Migrate the Aurora MySQL database to Amazon Aurora Serverless by restoring a snapshot. Change the endpoint in the Lambda functions to use the new database.
  B. Migrate the Aurora MySQL database to Amazon DynamoDB tables by using AWS Database Migration Service (AWS DMS). Change the endpoint in the Lambda functions to use the new database.
  C. Create an Amazon EventBridge rule that invokes a Lambda function. Code the function to iterate over all existing connections and to call MySQL queries to end any connections in the sleep state.
  D. Increase the instance class for the Aurora database with more memory. Set a larger value for the max_connections parameter.
  A. Migrate the Aurora MySQL database to Amazon Aurora Serverless by restoring a snapshot. Change the endpoint in the Lambda functions to use the new database.

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  Explanation/Reference:

  Correct Answer: A from Amazon documents: Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora MySQL that automatically starts up, shuts down, and scales capacity up or down based on your application's needs. Aurora Serverless is ideal for applications with unpredictable or intermittent traffic patterns that experience sudden spikes or drops in demand. Aurora Serverless also provides high availability and durability by replicating your data across multiple Availability Zones and continuously backing up your data to Amazon S3. Migrating the Aurora MySQL database to Amazon Aurora Serverless by restoring a snapshot will meet the requirements of implementing a scalable solution that is more resilient to database failures as quickly as possible. This solution will allow the company to benefit from the auto-scaling and high availability features of Aurora Serverless, which will handle the unpredictable surges in traffic and prevent connection issues. This solution will also be cost-effective, as the company will only pay for the database capacity that they use. The migration process will be simple and fast, as the company can use the AWS Management Console, the AWS CLI, or the RDS API to restore a snapshot of their existing Aurora MySQL database to an Aurora Serverless DB cluster, and then change the endpoint in the Lambda functions to use the new database. Therefore, option A is the correct solution to meet the requirements. Option B is not cost- effective because migrating the Aurora MySQL database to Amazon DynamoDB tables by using AWS DMS will incur additional time and cost, and may require significant code changes to adapt to a different data model and query language. Option C is not scalable because creating an EventBridge rule that invokes a Lambda function to end any connections in the sleep state will not address the root cause of the connection issues, which is the lack of database capacity to handle the traffic spikes. Option D is not scalable because increasing the instance class for the Aurora database with more memory and setting a larger value for the max_connections parameter will not provide auto-scaling or high availability, and may still result in connection issues if the traffic exceeds the provisioned capacity.

• Question 140:

  A retail company is about to migrate its online and mobile store to AWS. The company's CEO has strategic plans to grow the brand globally. A Database Specialist has been challenged to provide predictable read and write database performance with minimal operational overhead.

  What should the Database Specialist do to meet these requirements?

  A. Use Amazon DynamoDB global tables to synchronize transactions
  B. Use Amazon EMR to copy the orders table data across Regions
  C. Use Amazon Aurora Global Database to synchronize all transactions
  D. Use Amazon DynamoDB Streams to replicate all DynamoDB transactions and sync them
  A. Use Amazon DynamoDB global tables to synchronize transactions

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  Explanation/Reference:

  https://aws.amazon.com/dynamodb/features/

  With global tables, your globally distributed applications can access data locally in the selected regions to get single-digit millisecond read and write performance.

  Not Aurora Global Database, as per this link: https://aws.amazon.com/rds/aurora/global- database/?nc1=h_ls . Aurora Global Database lets you easily scale database reads across the world and place your applications close to your users.