Correct Answer: Vertex AI Model Registry
Model Registry is a central repository where you can manage the lifecycle of your ML models, including versioning, deployment, and aliasing....
Correct Answer
Vertex AI Model Registry
Why This Answer Is Correct
Model Registry is a central repository where you can manage the lifecycle of your ML models, including versioning, deployment, and aliasing.
This question evaluates your knowledge of Vertex AI — a core concept tested in Professional Cloud Architect. Understanding Vertex AI is essential for designing scalable, secure, and cost-effective cloud architectures. Mastery of this topic will help you answer scenario-based questions confidently on exam day.
Your organization uses Anthos to manage clusters both on-premises and on Google Cloud. You want to apply a consistent set of security policies and configurations across all clusters automatically. Which tool should you use?
A large organization wants to manage its cloud infrastructure using a 'GitOps' approach where changes to the environment are driven by pull requests. Which GCP service natively supports this model for K8s?
You are deploying a global microservices application. You want to ensure that traffic is encrypted between services (mTLS) and that you have fine-grained visibility into service-to-service communication. Which solution is most appropriate?
Your company is building an AI-powered chatbot that needs to understand sentiment and extract entities from customer feedback in 50 different languages. Which combination of pre-trained APIs should you use?
Your organization is migrating a massive Hadoop/Spark cluster to Google Cloud. They want to maintain their existing Hive scripts and HDFS storage patterns with minimal changes. Which service is the best fit?