Cloud-Digital-Leader Google Cloud Digital Leader exam Free Practice Exam Questions (2025 Updated)

The Organization resource is the root node of the Google Cloud resource hierarchy and all resources that belong to an organization are grouped under the organization node. This provides central visibility and control over every resource that belongs to an organization.

Reference link- https://cloud.google.com/resource-manager/docs/cloud-platform-resource-hierarchy

Security Health Analytics and Web Security Scanner detectors generate vulnerabilities findings that are available in Security Command Center. Your ability to view and edit findings is determined by the Identity and Access Management (IAM) roles and permissions you are assigned. For more information about IAM roles in Security Command Center.

Reference link:-

https://cloud.google.com/security-command-center/docs/concepts-vulnerabilities-findings

Because containers can compartmentalize applications which enables parts to be edited in isolation.

Reference link- https://cloud.google.com/learn/what-are-containers

Choose the Standard network service tier. While Premium tier is the default for all egress traffic and offers the highest performance, when cost is a consideration. Standard tier is the more economical.

https://cloud.google.com/blog/products/networking/networking-cost-optimization-best-practices

Explanation

Cloud Spanner: "Fully managed relational database with unlimited scale, strong consistency, and up to 99.999% availability."

The idea of the Sustained Use discount is that the longer you run a VM instance in any given month, the bigger discount you will get from the list price.

Store the information in Secret Manager is a secure and convenient storage system for API keys, passwords, certificates, and other sensitive data. Secret Manager provides a central place and single source of truth to manage access, and audit secrets across Google Cloud.

https://cloud.google.com/secret-manager

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.

Virtual machines - you can install customized OS

Containers - about applications

Virtualization enables you to run multiple operating systems on the hardware of a single physical server, while containerization enables you to deploy multiple applications using the same operating system on a single virtual machine or server. Serverless computing would be no OS required and the open source operating system allows the use of code that is freely distributed and available to anyone and for commercial purposes such as Linux and Free BSD.

The correct answer is B. Switch from batch processing to stream processing. Here's why:

Context of the Question: The organization processes sales data at the end of every month and wants to make near real-time decisions to improve accuracy and agility.

Google Cloud Product Relevance:

Stream processing allows data to be processed as it arrives, enabling real-time analytics and faster decision-making. This would allow the organization to analyze sales trends continuously rather than waiting for monthly batch jobs to complete.

Google Cloud services like Dataflow support both batch and stream processing, allowing for the transformation and analysis of data in real-time.

Why Not Other Options:

A. Filter the data so reports are generated faster: Filtering data may speed up reporting slightly but does not enable near real-time decision-making.

C. Process batch reports weekly instead of monthly: Processing weekly instead of monthly still doesn't provide the near real-time insights the organization needs.

D. Change from a relational database to a NoSQL database: This change might improve scalability or flexibility but does not directly address the need for real-time data processing.

Google Cloud Digital Leader References:

Refer to Google Cloud Dataflow documentation to learn about stream processing capabilities.

https://en.wikipedia.org/wiki/TensorFlow TensorFlow is a free and open-source software library for machine learning and artificial intelligence. Developer Google Brain Team

To follow Site Reliability Engineering (SRE) principles, the recommended approach when introducing a new system, like an image recognition login system, is to minimize risk and test in a controlled environment. SRE emphasizes progressive rollouts and monitoring to ensure reliability, stability, and security.

Option A: Roll out the new system to a subset of employees to test it out is the correct answer because this aligns with SRE practices, such as:

Canary Releases: Deploying a new feature to a small group of users (subset of employees) allows the organization to test the system in a real-world environment with minimal risk. This practice helps identify any potential issues, gather feedback, and monitor system behavior without impacting the entire organization.

Gradual Rollouts: SRE encourages gradual rollouts to detect and mitigate any failures early, reducing the blast radius in case of a malfunction or security issue. This ensures the reliability of the system while maintaining service quality.

Monitoring and Observability: Rolling out to a subset allows for comprehensive monitoring and collection of metrics to ensure the system performs as expected. If issues arise, they can be quickly identified and resolved before a wider deployment.

Option B: Roll out the new system to all employees to collect as much data as possible is not advisable under SRE principles because it poses a higher risk of widespread failure or security issues.

Option C: Avoid rolling out the new system because it may have security flaws and Option D: Avoid rolling out the new system because it may violate privacy policy are also incorrect in the context of SRE. While security and privacy are crucial, outright avoidance does not align with SRE practices. Instead, risk is managed through controlled rollouts, testing, and monitoring.