Google Cloud-Digital-Leader - Google Cloud Digital Leader exam

Tensor Processing Units (TPUs) are a type of purpose-built hardware designed specifically to accelerate machine learning workloads, particularly those involving TensorFlow. TPUs provide significant speed and performance improvements over general-purpose CPUs and even GPUs when running complex ML models.

Option C: TPUs is correct because TPUs (Tensor Processing Units) are optimized to accelerate the training of machine learning models developed with TensorFlow, providing faster performance compared to other hardware.

Cloud Identity and Access Management (IAM) helps customers to define fine-grained access policies and precisely control access to Google Cloud-hosted data.

Cloud Debugger is a feature of Google Cloud Platform that lets you inspect the state of an application, at any code location, without stopping or slowing down the running app. Cloud Debugger makes it easier to view the application state without adding logging statements.

Digital transformation refers to the use of new technologies to fundamentally change how an organization operates, interacts with customers, and delivers value. It includes changes to business processes, culture, and customer experiences to better adapt to market dynamics and leverage new digital capabilities.

Option A: Digital transformation is correct because it involves using new technologies to drive changes in business processes, customer experiences, and organizational culture to stay competitive in a rapidly changing market.

A Greenfield approach is a brand-new implementation , where companies then add their needed configurations and customizations. This approach provides a clean slate to start from, does not carry over needless customizations and technical debt, and provides a solid foundation for business process re-engineering.

A greenfield deployment is the design, installation and configuration of computer infrastructure where none existed before, for example, in a new office. In contrast, a brownfield deployment is an upgrade or addition to existing infrastructure using legacy components.

The correct answer is A. The refactored application is more efficient and scalable. Here's why:

Context of the Question: The organization wants to refactor its application into a microservices architecture when migrating to the cloud.

Google Cloud Product Relevance:

Microservices architecture breaks down applications into smaller, independent services that can be developed, deployed, and scaled independently. This increases efficiency and scalability, as each microservice can be scaled according to its needs without affecting the entire application.

Google Cloud provides tools such as Kubernetes Engine (GKE) for container orchestration, Anthos for managing microservices across hybrid and multi-cloud environments, and Cloud Run for deploying containerized applications efficiently.

Why Not Other Options:

B. No code changes will be required: Refactoring to microservices often requires significant code changes to decouple services.

C. This migration pattern provides the fastest path to the cloud: Refactoring to microservices is a complex process that typically takes more time compared to a "lift-and-shift" migration.

D. The application will become PCI-DSS compliant by default: Compliance with PCI-DSS (Payment Card Industry Data Security Standard) depends on specific security controls, not on using microservices architecture.

Google Cloud Digital Leader References:

For more information on microservices and cloud-native architectures, refer to the Google Cloud Microservices documentation.