An enterprise logistics corporation is modernizing an aging on-premises inventory tracking… — Google Cloud Professional Cloud Architect

An enterprise logistics corporation is modernizing an aging on-premises inventory tracking system to resolve severe technical debt. The current workload consists of a legacy monolithic web application running on custom-configured Linux virtual machines (VMs) and a single-region $15\text{ TB}$ PostgreSQL database. Over years of operation, manual server configurations have caused severe configuration drift, while custom deployment scripts frequently break during release cycles.

The leadership team wants to migrate the system to Google Cloud over an upcoming weekend maintenance window. The primary objectives are to minimize ongoing server maintenance overhead, avoid unnecessary infrastructure costs, and prevent data exfiltration from staging storage buckets by authorized users. The organization already operates an active $10\text{ Gbps}$ Partner Interconnect link to Google Cloud with abundant available bandwidth.

Which TWO architectural patterns should the Cloud Architect recommend to address the technical debt and fulfill the migration requirements? (Select TWO)

Migrate the relational workload to Cloud SQL for PostgreSQL and establish continuous data replication using Database Migration Service (DMS) prior to final cutover.Answer
B
Migrate the database to Cloud Spanner to ensure multi-region horizontal scaling and global synchronous replication for the inventory system.
Refactor the application into lightweight container images deployed to Cloud Run, and enforce a VPC Service Controls perimeter around Cloud Storage data landing buckets.Answer
D
Order a Google Cloud Transfer Appliance to physically transport the initial $15\text{ TB}$ database snapshot offline to Google Cloud prior to cutover.

Answer

The architect should select Cloud SQL for PostgreSQL with Database Migration Service for database migration, and deploy containerized application workloads to Cloud Run guarded by VPC Service Controls for storage perimeter protection.

Migrating to Cloud SQL for PostgreSQL via Database Migration Service (DMS) enables continuous online database replication over the existing

10\text{ Gbps}

Interconnect, minimizing cutover downtime while removing self-managed VM database technical debt. Simultaneously, containerizing the application onto serverless Cloud Run eliminates VM configuration drift, while VPC Service Controls protect Cloud Storage landing buckets against data exfiltration by enforcing security boundaries that IAM alone cannot guarantee.

Step-by-Step Solution

Analyze database migration strategy based on database size, network capacity, and target managed service.

15\text{ TB}

dataset over a

10\text{ Gbps}

dedicated line takes approximately 3.5 to 5 hours to transfer online. Database Migration Service (DMS) to Cloud SQL for PostgreSQL is the optimal managed approach.

Cloud SQL eliminates relational VM infrastructure management debt, while DMS enables initial online snapshot migration followed by low-downtime continuous replication.

Evaluate compute modernization strategy to address manual VM configuration drift.

Containerizing stateless web endpoints and hosting them on Cloud Run removes OS maintenance and infrastructure overhead without needing Kubernetes management.

Cloud Run provides serverless container execution that directly resolves manual configuration drift and reduces operational overhead.

Evaluate security controls against data exfiltration risks.

VPC Service Controls must be implemented around Cloud Storage landing buckets.

IAM roles control resource access permissions, but only VPC Service Controls establish network perimeters that prevent authorized users from exfiltrating data outside approved Google Cloud project boundaries.

Key Concept

Managing cloud migration debt by balancing serverless/managed service adoption (Cloud Run and Cloud SQL) against operational overhead and over-engineering anti-patterns.

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