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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 All Questions

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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 topic 1 question 89 discussion

Exam question from Amazon's AWS Certified Machine Learning Engineer - Associate MLA-C01
Question #: 89
Topic #: 1
[All AWS Certified Machine Learning Engineer - Associate MLA-C01 Questions]

An ML engineer needs to encrypt all data in transit when an ML training job runs. The ML engineer must ensure that encryption in transit is applied to processes that Amazon SageMaker uses during the training job.

Which solution will meet these requirements?

  • A. Encrypt communication between nodes for batch processing.
  • B. Encrypt communication between nodes in a training cluster.
  • C. Specify an AWS Key Management Service (AWS KMS) key during creation of the training job request.
  • D. Specify an AWS Key Management Service (AWS KMS) key during creation of the SageMaker domain.
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Suggested Answer: B 🗳️
by chris_spencer at March 11, 2025, 1:50 p.m.
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aws_Tamilan
2 weeks, 5 days ago
Selected Answer: B
🔑 Keyword: Encrypt data in transit during SageMaker training ✅ Correct Answer: B. Encrypt communication between nodes in a training cluster. Why? Encryption in transit refers to securing data as it moves between components of the SageMaker training infrastructure (e.g., between nodes in a distributed training job). SageMaker automatically encrypts communication between nodes using TLS 1.2 in multi-node training clusters. Why Others Are Wrong? ❌ A. "Batch processing" is not relevant to SageMaker training jobs. ❌ C. AWS KMS is used for encrypting data at rest, not for securing in-transit data. ❌ D. SageMaker domain encryption is for Studio environments, not training jobs.
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ygn4ei
1 month ago
Selected Answer: B
this is it
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