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NEW QUESTION: 1
Which two statements about the provisioning of Cisco VM-FEX DirectPath I/O mode are true?
(Choose two.)
A. To use Cisco VM-FEX DirectPath I/O mode, a virtual machine must have a dynamic vNIC and two static vNICs on the VIC adapter.
B. VMDirectPath mode prevents the use of VMware vMotion.
C. The VT-D feature on the ESX host server must be disabled before you can enable
VMDirectPath.
D. Enabling high performance turns on VMDirectPath mode.
E. VM-FEX standard mode is the same as VM-FEX high-performance mode.
Answer: A,D
Explanation:
Reference: http://www.cisco.com/c/en/us/solutions/collateral/data-center- virtualization/unifiedcomputing/vm_fex_best_practices_deployment_guide.html

NEW QUESTION: 2
The director of software development is concerned with recent web application security incidents, including the successful breach of a back-end database server. The director would like to work with the security team to implement a standardized way to design, build, and test web applications and the services that support them. Which of the following meets the criteria?
A. SANS
B. PHP
C. Ajax
D. OWASP
Answer: D
Explanation:
Explanation/Reference:
Reference: https://www.synopsys.com/software-integrity/resources/knowledge-database/owasp-top-
10.html

NEW QUESTION: 3

A. Option B
B. Option A
C. Option D
D. Option C
Answer: C

NEW QUESTION: 4
An enterprise company's data science team wants to provide a safe, cost-effective way to provide easy access to Amazon SageMaker. The data scientists have limited AWS knowledge and need to be able to launch a Jupyter notebook instance. The notebook instance needs to have a preconfigured AWS KMS key to encrypt data at rest on the machine learning storage volume without exposing the complex setup requirements.
Which approach will allow the company to set up a self-service mechanism for the data scientists to launch Jupyter notebooks in its AWS accounts with the LEAST amount of operational overhead?
A. Create an AWS CloudFormation template to launch a Jupyter notebook instance using the AWS::SaqeMaker::Notebooklnstance resource type with a preconfigured KMS key. Add a user-friendly name to the CloudFormation template. Display the URL to the notebook using the Outputs section.
Distribute the CloudFormation template to the data scientists using a shared Amazon S3 bucket.
B. Create an AWS CLI script that the data scientists can run locally. Provide step-by-step instructions about the parameters to be provided while executing the AWS CLI script to launch a Jupyter notebook with a preconfigured KMS key. Distribute the CLI script to the data scientists using a shared Amazon S3 bucket.
C. Create an AWS CloudFormation template to launch a Jupyter notebook instance using the AWS::SageMaker::Notebooklnstance resource type with a preconfigured KMS key. Simplify the parameter names, such as the instance size, by mapping them to Small, Large, and X-Large using the Mappings section in CloudFormation. Display the URL to the notebook using the Outputs section, then upload the template into an AWS Service Catalog product in the data scientist's portfolio, and share it with the data scientist's 1AM role.
D. Create a serverless front end using a static Amazon S3 website to allow the data scientists to request a Jupyter notebook instance by filling out a form. Use Amazon API Gateway to receive requests from the S3 website and trigger a central AWS Lambda function to make an API call to Amazon SageMaker that launch a notebook instance with a preconfigured KMS key for the data scientists. Then call back to the front-end website to display the URL to the notebook instance.
Answer: A