Amazon Web Services marks4sure aws Certified Database Dbs-c01 Book by Persephone q162 vce pdf

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Exam Name:	AWS Certified Database - Specialty
Exam Code:	DBS-C01 Dumps
Vendor:	Amazon Web Services	Certification:	AWS Certified Database
Questions:	324 Q&A's	Shared By:	persephone

Question 24

An ecommerce company uses a backend application that stores data in an Amazon DynamoDB table. The backend application runs in a private subnet in a VPC and must connect to this table.

The company must minimize any network latency that results from network connectivity issues, even during periods of heavy application usage. A database administrator also needs the ability to use a private connection to connect to the DynamoDB table from the application.

Which solution will meet these requirements?

Options:

Use network ACLs to ensure that any outgoing or incoming connections to any port except DynamoDB are deactivated. Encrypt API calls by using TLS.

Create a VPC endpoint for DynamoDB in the application's VPC. Use the VPC endpoint to access the table.

Create an AWS Lambda function that has access to DynamoDB. Restrict outgoing access only to this Lambda function from the application.

Use a VPN to route all communication to DynamoDB through the company's own corporate network infrastructure.

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Question 25

A company wants to migrate its on-premises MySQL databases to Amazon RDS for MySQL. To comply with the company’s security policy, all databases must be encrypted at rest. RDS DB instance snapshots must also be shared across various accounts to provision testing and staging environments.

Which solution meets these requirements?

Options:

Create an RDS for MySQL DB instance with an AWS Key Management Service (AWS KMS) customer managed CMK. Update the key policy to include the Amazon Resource Name (ARN) of the other AWS accounts as a principal, and then allow the kms:CreateGrant action.

Create an RDS for MySQL DB instance with an AWS managed CMK. Create a new key policy to include the Amazon Resource Name (ARN) of the other AWS accounts as a principal, and then allow the kms:CreateGrant action.

Create an RDS for MySQL DB instance with an AWS owned CMK. Create a new key policy to include the administrator user name of the other AWS accounts as a principal, and then allow the kms:CreateGrant action.

Create an RDS for MySQL DB instance with an AWS CloudHSM key. Update the key policy to include the Amazon Resource Name (ARN) of the other AWS accounts as a principal, and then allow the kms:CreateGrant action.

Discussion

Question 26

A database specialist is launching a test graph database using Amazon Neptune for the first time. The database specialist needs to insert millions of rows of test observations from a .csv file that is stored in Amazon S3. The database specialist has been using a series of API calls to upload the data to the Neptune DB instance.

Which combination of steps would allow the database specialist to upload the data faster? (Choose three.)

Options:

Ensure Amazon Cognito returns the proper AWS STS tokens to authenticate the Neptune DB instance to the S3 bucket hosting the CSV file.

Ensure the vertices and edges are specified in different .csv files with proper header column formatting.

Use AWS DMS to move data from Amazon S3 to the Neptune Loader.

Curl the S3 URI while inside the Neptune DB instance and then run the addVertex or addEdge commands.

Ensure an IAM role for the Neptune DB instance is configured with the appropriate permissions to allow access to the file in the S3 bucket.

Create an S3 VPC endpoint and issue an HTTP POST to the database's loader endpoint.

Discussion

Answer:

B, E, F

Explanation:

Explanation:

Correct Answer: B, E, F

Explanation from Amazon documents:

To upload data faster to a Neptune DB instance from a .csv file stored in Amazon S3, the database specialist should use the Neptune Bulk Loader, which is a feature that allows you to load data from external files directly into a Neptune DB instance1. The Neptune Bulk Loader is faster and has less overhead than the API calls, such as SPARQL INSERT statements or Gremlin addV and addE steps2. The Neptune Bulk Loader supports both RDF and Gremlin data formats1.

To use the Neptune Bulk Loader, the database specialist needs to do the following13:

Ensure the vertices and edges are specified in different .csv files with proper header column formatting. This is required for the Gremlin data format, which uses two .csv files: one for vertices and one for edges. The first row of each file must contain the column names, which must match the property names of the graph elements. The files must also have a column named ~id for vertices and ~from and ~to for edges, which specify the unique identifiers of the graph elements1.
Ensure an IAM role for the Neptune DB instance is configured with the appropriate permissions to allow access to the file in the S3 bucket. This is required for the Neptune DB instance to read the data from the S3 bucket. The IAM role must have a trust policy that allows Neptune to assume the role, and a permissions policy that allows access to the S3 bucket and objects3.
Create an S3 VPC endpoint and issue an HTTP POST to the database’s loader endpoint. This is required for the Neptune DB instance to communicate with the S3 bucket without going through the public internet. The S3 VPC endpoint must be in the same VPC as the Neptune DB instance. The HTTP POST request must specify the source parameter as the S3 URI of the .csv file, and optionally other parameters such as format, failOnError, parallelism, etc1.

Therefore, option B, E, and F are the correct steps to upload the data faster. Option A is not necessary because Amazon Cognito is not used for authenticating the Neptune DB instance to the S3 bucket. Option C is not suitable because AWS DMS is not designed for loading graph data into Neptune. Option D is not efficient because curling the S3 URI and running the addVertex or addEdge commands will be slower and more costly than using the Neptune Bulk Loader.

Question 27

A large company is using an Amazon RDS for Oracle Multi-AZ DB instance with a Java application. As a part of its disaster recovery annual testing, the company would like to simulate an Availability Zone failure and record how the application reacts during the DB instance failover activity. The company does not want to make any code changes for this activity.

What should the company do to achieve this in the shortest amount of time?

Options:

Use a blue-green deployment with a complete application-level failover test

Use the RDS console to reboot the DB instance by choosing the option to reboot with failover

Use RDS fault injection queries to simulate the primary node failure

Add a rule to the NACL to deny all traffic on the subnets associated with a single Availability Zone