Google Professional Machine Learning Engineer Question 403
Select 3Google Cloud PlatformYour company is deploying a machine learning application that processes large amounts of sensitive customer data. The application must run across both an on-premises data center and Google Cloud to comply with data residency requirements while maximizing scalability. Which strategies should you implement to ensure secure and efficient deployment in this hybrid environment?
- A
Use Anthos to manage and orchestrate workloads across on-premises and Google Cloud environments.
- B
Encrypt data at rest and in transit using Cloud Key Management Service (KMS).
- C
Migrate all sensitive data to Google Cloud to simplify management and security.
- D
Leverage a dedicated interconnect or VPN for secure communication between on-premises and Google Cloud.
- E
Run separate machine learning models for on-premises and cloud environments to avoid data movement.
Show answer and explanation
Correct answers: A, B, D
Explanation
In a hybrid environment, it's crucial to ensure secure communication, consistent workload management, and compliance with data residency requirements. Anthos provides unified management across environments, while encryption and secure connections via interconnect or VPN protect data integrity. Migrating all sensitive data to Google Cloud or running separate models would not meet the scenario's requirements, as they either violate compliance or increase operational complexity.
- A. Correct.
Anthos is designed to manage hybrid and multicloud environments, providing consistent management and orchestration for workloads across on-premises and Google Cloud.
- B. Correct.
Encrypting data at rest and in transit ensures data security and compliance with regulations, especially in hybrid environments where data crosses boundaries.
- C. Incorrect.
Migrating all sensitive data to Google Cloud would violate the data residency requirements outlined in the scenario and isn't feasible in a hybrid strategy.
- D. Correct.
A dedicated interconnect or VPN ensures secure and reliable communication between on-premises and Google Cloud, which is critical for hybrid workloads.
- E. Incorrect.
Running separate machine learning models for on-premises and cloud increases complexity and may lead to inconsistent results, making it an inefficient strategy for this scenario.