PROFESSIONAL-CLOUD-ARCHITECT Question #358: Real Exam Question with Answer & Explanation

Question

Your employer is a financial services company that recently acquired a popular fintech startup. The startup's core application is a monolithic Python application running on a managed instance group of Compute Engine virtual machines with a single, large PostgreSQL database. Your development team struggles with slow deployment cycles, and the monolithic design of the startup's core application makes it difficult to integrate new. ML-powered fraud detection models. You need a long-term strategy that improves developer agility and positions the company to leverage Google Cloud's advanced data and AI capabilities for future innovations. What should you do?

Options

• ADeploy the ML fraud detection model to a Vertex AI endpoint. Create a REST API for the model
• BContainerize the application, deploy it to Google Kubernetes Engine (GKE), and migrate the
• CPropose a phased, event-driven migration to a microservices architecture. Use Pub/Sub for
• DMigrate the PostgreSQL database to Cloud SQL for PostgreSQL. Replicate the data into

Explanation

A phased, event-driven migration to microservices decouples the monolithic application, enabling faster, independent deployments and significantly improving developer agility. Using Pub/Sub allows scalable, asynchronous communication between services, while deploying fraud detection models on Vertex AI integrates Google Cloud’s advanced AI capabilities in a flexible, future-ready architecture without requiring a disruptive full rewrite upfront.

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