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Exam AWS Certified Machine Learning - Specialty topic 1 question 293 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 293
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A data scientist stores financial datasets in Amazon S3. The data scientist uses Amazon Athena to query the datasets by using SQL.

The data scientist uses Amazon SageMaker to deploy a machine learning (ML) model. The data scientist wants to obtain inferences from the model at the SageMaker endpoint. However, when the data scientist attempts to invoke the SageMaker endpoint, the data scientist receives SQL statement failures. The data scientist’s IAM user is currently unable to invoke the SageMaker endpoint.

Which combination of actions will give the data scientist’s IAM user the ability to invoke the SageMaker endpoint? (Choose three.)

  • A. Attach the AmazonAthenaFullAccess AWS managed policy to the user identity.
  • B. Include a policy statement for the data scientist's IAM user that allows the IAM user to perform the sagemaker:InvokeEndpoint action.
  • C. Include an inline policy for the data scientist’s IAM user that allows SageMaker to read S3 objects.
  • D. Include a policy statement for the data scientist’s IAM user that allows the IAM user to perform the sagemaker:GetRecord action.
  • E. Include the SQL statement "USING EXTERNAL FUNCTION ml_function_name'' in the Athena SQL query.
  • F. Perform a user remapping in SageMaker to map the IAM user to another IAM user that is on the hosted endpoint.
Show Suggested Answer Hide Answer
Suggested Answer: BCE 🗳️
by kyuhuck at Feb. 7, 2024, 10:25 a.m.
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Certified101
2 months ago
Selected Answer: ABE
Why on earth would you "update data scientist’s IAM USER that allows SageMaker to read S3 objects" - you cant update an IAM user to give a service access to another service? If this said "Sagemaker IAM role to access S3" then i would undertsand, but it doesnt say that. At the same time, giving AthenaFullAccess is not best practise and not least privalage. ill go with ABE
upvoted 1 times
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MultiCloudIronMan
7 months, 1 week ago
Selected Answer: ABC
(Option B). This is essential for invoking the endpoint1. (Option C). This ensures that the model can access the necessary data stored in S32. Option A). This grants the necessary permissions to query datasets using Athena
upvoted 1 times
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vkbajoria
1 year ago
Selected Answer: BCE
data scientist already was querying the athena plus invoking sagemaker endpoint issue would not solve. therefore, A is not a good choice
upvoted 1 times
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AIWave
1 year, 1 month ago
Selected Answer: BCE
A: NO - not needed as user already has Athena access (he is already querying Athena by SQL) B: Yes - sagemaker:InvokeEndpoint permission is needed to invoke endpoint C: Yes - needed for IAM user context to read S3 bucket D: No - sagemaker:GetRecord has no relevance in this question E: Yes - used to call an external function, in this case, the ML function deployed on the SageMaker endpoint, within the Athena SQL query F: No - irrelevant
upvoted 3 times
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rav009
1 year, 2 months ago
Selected Answer: ABE
ABE C is wrong. Why sagemaker need access S3? Sagemaker receive data and request via the endpoint.
upvoted 2 times
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Untamables
1 year, 2 months ago
Selected Answer: ABE
https://docs.aws.amazon.com/athena/latest/ug/querying-mlmodel.html https://docs.aws.amazon.com/athena/latest/ug/machine-learning-iam-access.html
upvoted 2 times
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kyuhuck
1 year, 2 months ago
Selected Answer: BCE
The correct combination of actions to enable the data scientist's IAM user to invoke the SageMaker endpoint is B, C, and E, because they ensure that the IAM user has the necessary permissions, access, and syntax to query the ML model from Athena. These actions have the following benefits: B: Including a policy statement for the IAM user that allows the sagemaker:InvokeEndpoint action grants the IAM user the permission to call the SageMaker Runtime InvokeEndpoint API, which is used to get inferences from the model hosted at the endpoint1.
upvoted 2 times
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