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NEW QUESTION: 1

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

NEW QUESTION: 2
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 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.
B. 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.
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 IAM 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: B

NEW QUESTION: 3
In your LAMP application, you have some developers that say they would like access to your logs. However, since you are using an AWS Auto Scaling group, your instances are constantly being re-created. What would you do to make sure that these developers can access these log files? Choose the correct answer from the options below Please select:
A. Give read-only access to your developers to the Apache servers.
B. Set up a central logging server that you can use to archive your logs; archive these logs to an S3 bucket for developer-access.
C. Give root access to your Apache servers to the developers.
D. Give only the necessary access to the Apache servers so that the developers can gain access to the log files.
Answer: B
Explanation:
One important security aspect is to never give access to actual servers, hence Option A.B and C are just totally wrong from a security perspective.
The best option is to have a central logging server that can be used to archive logs. These logs can then be stored in S3.
Options A,B and C are all invalid because you should not give access to the developers on the Apache se For more information on S3, please refer to the below link
https://aws.amazon.com/documentation/s3j
The correct answer is: Set up a central logging server that you can use to archive your logs; archive these logs to an S3 bucket for developer-access.
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