Pass the Google Cloud Certified Cloud-Digital-Leader Questions and answers with ExamsMirror

Compute Engine provides machine type recommendations to help you optimize the resource utilization of your virtual machine (VM) instances. These recommendations are generated automatically based on system metrics gathered by the Cloud Monitoring service over the previous 8 days. Use these recommendations to resize your instance’s machine type to use the instance’s resources more efficiently. This feature is also known as rightsizing recommendations

Reference link- https://cloud.google.com/compute/docs/instances/apply-machine-type-recommendations-for-instances

Compute Engine provides graphics processing units (GPUs) that you can add to your virtual machines (VMs). You can use these GPUs to accelerate specific workloads on your VMs such as machine learning and data processing.

https://cloud.google.com/compute/docs/gpus

A relational database offers the functionality of storing transactional data, which can then be accessed electronically. Relational databases store structured data that can be organized in tables with defined relationships between them. This makes them well-suited for transactional data, such as inventory data, that needs to be accessed and updated frequently.

The correct answer is B. Machine learning. Here’s why:

Context of the Question: The question describes an application that can diagnose medical conditions based on images submitted by users. This is a task typically handled by machine learning (ML) models, specifically those focused on image recognition and classification.

Google Cloud Product Relevance:

Machine learning (ML) is the correct service because it refers to the use of Google Cloud's AI/ML capabilities, which include services such as AutoML Vision and Vertex AI. These tools can build and deploy machine learning models specifically for image recognition tasks, such as identifying medical conditions from images.

AutoML Vision is designed to create custom ML models with minimal ML expertise, making it suitable for diagnosing medical conditions from images.

Vertex AI allows for training, evaluating, and deploying ML models, including complex models for medical image diagnostics.

Why Not Other Options:

A. App Engine: App Engine is a platform-as-a-service (PaaS) used for building and deploying web applications, not specifically for ML or image recognition tasks.

C. Cloud Logging: Cloud Logging is used to store, search, analyze, and monitor log data and events. It does not have any capabilities related to diagnosing medical conditions or image recognition.

D. Cloud Profiler: Cloud Profiler is a performance analysis tool for applications running in production. It helps identify bottlenecks and optimize resource usage but has no relevance to image diagnosis or machine learning.

Google Cloud Digital Leader References:

For more information on Machine Learning with Google Cloud, refer to the Google Cloud documentation on AutoML Vision and Vertex AI.

Understanding the basic principles and applications of Google Cloud’s ML services is crucial for the Google Cloud Digital Leader exam, which emphasizes knowing how different services solve business challenges.

The correct answer is C. Cloud SQL. Here's why:

Context of the Question: The organization needs a cost-effective, transactional database for an e-commerce application serving customers in a single region. A transactional database is needed to handle online transactions with ACID (Atomicity, Consistency, Isolation, Durability) properties.

Google Cloud Product Relevance:

Cloud SQL is a fully managed relational database service for MySQL, PostgreSQL, and SQL Server. It is cost-effective, supports transactional workloads, and is suitable for applications with regional data residency requirements. This makes it ideal for an e-commerce application that only serves customers in a single region.

Why Not Other Options:

A. Cloud Spanner: Cloud Spanner is a globally distributed, strongly consistent database designed for large-scale, mission-critical applications. It is more expensive and better suited for applications requiring global distribution and high availability across multiple regions.

B. Cloud Bigtable: Cloud Bigtable is a NoSQL wide-column database designed for low-latency, high-throughput workloads, such as analytics. It does not support ACID transactions, making it unsuitable for transactional workloads like an e-commerce application.

D. BigQuery: BigQuery is a fully managed data warehouse designed for large-scale analytics. It is not suitable for transactional database needs.

Google Cloud Digital Leader References:

For more details on Cloud SQL, refer to the Cloud SQL documentation in the Google Cloud platform.