The correct answer is C. Kubernetes Engine. Here's why:
* Context of the Question: The organization needs to operate multiple workloads in containers with full control over how these workloads are configured.
* Google Cloud Product Relevance:
* Google Kubernetes Engine (GKE) is a fully managed service that allows organizations to run, deploy, and manage containerized applications using Kubernetes. GKE provides full control over workload configuration, including resource allocation, scaling, networking, and security policies.
* With GKE, the organization can use Kubernetes features such as custom resource definitions, namespaces, and pod configurations to achieve the desired level of control over their workloads.
* Why Not Other Options:
* A. Cloud Functions: Cloud Functions is a serverless compute service for running event-driven functions and does not provide control over containerized workloads.
* B. Compute Engine: Compute Engine provides virtual machines (VMs), which are not specific to containerized workloads. It requires more management compared to GKE.
* D. Cloud Run: Cloud Run is a managed service for running containers but abstracts much of the configuration details to simplify deployment. It does not offer as much control over workload configuration as GKE.
Google Cloud Digital Leader References:
* Refer to the Google Kubernetes Engine documentation for more details on managing containerized workloads.

Folders for a related group of projects are the recommended approach.
-> A flat structure under the organization node is possible on Google Cloud, but it is not recommended. It becomes tougher to manage.
-> Projects cannot have sub-projects; there can only be resources within Projects.
Reference link- https://cloud.google.com/resource-manager/docs/cloud-platform-resource-hierarchy

Organizations can scale in the cloud by paying for what they use, when they use it.

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.

Graphical user interface, text, application Description automatically generated

https://cloud.google.com/compute/docs/instances/signing-up-committed-use-discounts