Ngân hàng đề — Google Professional Cloud Architect

Your organization operates multiple production services on Google Cloud. Some teams deploy updates manually, while others maintain long-lived VM instances with manual configuration changes. Leadership wants to improve operational excellence, reduce variance between environments, and ensure that deployments are predictable, repeatable, and auditable. Which approach best aligns with the operational excellence principles of the Google Cloud Well-Architected Framework?

An e-commerce platform expects a significant increase in traffic during its seasonal sale events. The platform requires a database solution that supports high transaction throughput, low latency, and scales automatically to handle unpredictable workloads. Security is critical, as the platform processes sensitive customer data, and compliance with data residency requirements is mandatory. Which solution would best meet these requirements?

As a cloud architect, you are designing a complex deployment scenario for a client that involves using an unmanaged instance group with an active instance and a standby instance in different zones. You are required to use a regional persistent disk and a network load balancer in front of the instances. How do you ensure that in the event of a failure, traffic will be redirected to the standby instance?

Your company has multiple regional analytics teams across North America, Europe, and Asia. Each region uses its own data warehouse, but executives want to standardize KPIs globally using Looker. You are tasked with designing a solution that ensures centralized modeling, governed metrics, and consistency, while allowing regional teams to explore their data independently. What should you do?

A global e-commerce company operates a platform that must be available 24/7 with minimal downtime, even in the event of regional outages. The platform handles sensitive customer data and needs to comply with strict data protection regulations. The company’s current infrastructure is hosted on Google Cloud, and they are considering implementing a disaster recovery (DR) plan to ensure business continuity in case of a failure in their primary region.

The company’s business requirements include:

• Recovery Point Objective (RPO) of less than 1 hour.

• Recovery Time Objective (RTO) of less than 15 minutes.

• Data residency compliance in multiple regions.

• Cost-effectiveness of the DR solution.

• Ability to handle peak loads in the event of a failover.

Which DR solution should the company implement?

To leverage Cloud Pub/Sub messages within your App Engine application, you find that the Cloud Pub/Sub API is currently disabled. In order to enable your application to utilize Cloud Pub/Sub, you plan to authenticate it to the API using a service account. What measures should you take to ensure seamless usage of Cloud Pub/Sub by your application?

Your team is designing a critical Google Cloud-based application that must support rapid feature delivery, minimal downtime, and a clear operational responsibility model. According to the Operational Excellence pillar of the Well-Architected Framework, which approach best aligns with recommended practices?

A financial services company requires a highly available and resilient application that serves users globally. The application handles sensitive financial transactions and must comply with strict regulatory requirements, including data residency. The company wants to deploy the application in multiple regions to ensure minimal downtime in case of a regional failure. However, the company is also concerned about the costs associated with maintaining a multi-region architecture and seeks to optimize costs while ensuring compliance and availability. Which design should you recommend for the disaster recovery solution?

A mission-critical application runs on several virtual machines in on-premise data center and needs to be migrated to GCP. As a cloud architect, you need to prepare a migration strategy. The company wants to benefit from Lift and Shift approach, and this application needs to be scaled automatically and efficiently based on the CPU utilization. What do you recommend?

You are designing a cloud infrastructure for a financial analytics platform that processes large datasets in real-time. The platform needs to scale automatically based on the volume of incoming data, which can vary significantly throughout the day. The architecture includes Compute Engine instances for data processing, BigQuery for data analysis, and Cloud Storage for data archival. The platform has experienced intermittent failures during peak loads due to quota limitations, causing delays in data processing. You must design a solution that ensures the platform remains elastic and resilient to sudden spikes in demand while adhering to Google Cloud's quota and limit policies. Which of the following design choices best addresses the elasticity requirements while managing quota limits effectively?