Google Cloud Digital Leader Exam Dumps & Practice Test Questions
Question 1
Your company is migrating to Google Cloud and needs to move several terabytes of data from on-premises file servers to Google Cloud Storage. The migration must be automated and overseen by Google. The company also plans to use its existing Dedicated Interconnect connection for the transfer.
Which service should you use?
A. Storage Transfer Service
B. Migrate for Anthos
C. BigQuery Data Transfer Service
D. Transfer Appliance
Correct Answer : A
Explanation:
The Storage Transfer Service is the ideal solution for moving large volumes of data from on-premises systems to Google Cloud Storage. It allows for automated and scheduled data transfer, and it can work with an existing Dedicated Interconnect connection to facilitate high-speed, secure transfers. This service is designed for transferring data from on-premises file servers to Google Cloud Storage and is managed by Google, making it the most appropriate choice.
B. Migrate for Anthos - Migrate for Anthos is used for migrating virtual machines and workloads to Google Kubernetes Engine (GKE), not for transferring data to Cloud Storage. It’s intended for containerized workloads, not for moving file data.
C. BigQuery Data Transfer Service - The BigQuery Data Transfer Service is used to transfer data into BigQuery, Google Cloud's analytics data warehouse, from a variety of sources. It is not designed for moving file data to Cloud Storage.
D. Transfer Appliance - The Transfer Appliance is a physical device used for transferring large volumes of data to Google Cloud Storage when network bandwidth is insufficient. It’s useful for very large data sets but is not necessary when you already have an existing Dedicated Interconnect connection for faster network transfers.
A. Storage Transfer Service is the best service for automating the migration of large amounts of data to Google Cloud Storage.
Question 2
Your organization wants to derive insights from operational data while minimizing costs by paying only for storage and actual queries run. Which Google Cloud solution is best suited as a data analytics warehouse?
A. Cloud SQL
B. Dataproc
C. Cloud Spanner
D. BigQuery
Correct Answer : D
Explanation:
BigQuery is Google Cloud's fully-managed, serverless data warehouse that allows for real-time analytics and scalable data processing. It is cost-effective because you only pay for the storage used and the queries executed, which directly addresses the organization's need to minimize costs while deriving insights from operational data. BigQuery is ideal for organizations that require a highly scalable, low-maintenance data warehouse solution for running complex queries over large datasets.
A. Cloud SQL - Cloud SQL is a fully-managed relational database service, but it is more suited for transactional databases rather than large-scale analytics. It is not designed as a data warehouse solution for complex analytical workloads at the scale of BigQuery.
B. Dataproc - Dataproc is a managed Spark and Hadoop service that can be used for big data processing and analytics. While it is useful for large-scale data processing, it is not a traditional data warehouse. It requires more management and is not as serverless or cost-efficient as BigQuery for query-based analytics.
C. Cloud Spanner - Cloud Spanner is a globally distributed relational database service that provides high availability and strong consistency. While it’s great for transactional systems, it is not optimized for analytics workloads, and the cost structure may not be as efficient as BigQuery for the use case described.
D. BigQuery is the best solution for cost-efficient data analytics in Google Cloud, where you only pay for storage and the queries you run, making it ideal for deriving insights from operational data.
Question 3
You are deploying a container-based application in Google Cloud that is expected to become increasingly complex. It must support detailed traffic controls between containers and advanced scaling capabilities.
Which platform should you choose?
A. Google Kubernetes Engine cluster
B. App Engine
C. Cloud Run
D. Compute Engine
Answer: A
Explanation:
When deploying container-based applications that need advanced scaling and traffic control, the ideal platform is Google Kubernetes Engine (GKE). GKE is specifically designed to manage containerized applications at scale and provides powerful features like automated scaling, load balancing, and detailed network policies between containers. It uses Kubernetes, an open-source orchestration platform, which allows you to control traffic, define policies, and manage resources efficiently across a cluster of containers. This makes it a great fit for complex applications that require flexibility and advanced features.
Option A, Google Kubernetes Engine cluster, is the best option for the requirements mentioned in the question. It allows you to manage and scale your containerized applications seamlessly while providing robust network policies and traffic control.
Option B, App Engine, is a fully managed platform for deploying web applications, but it doesn't offer the granular traffic controls and complex scaling capabilities that Kubernetes provides for containerized applications.
Option C, Cloud Run, is another fully managed service that handles containers, but it is more suitable for stateless applications and does not offer the same level of traffic control or advanced scaling options as GKE.
Option D, Compute Engine, provides virtual machines but lacks the native orchestration and traffic management features available in Kubernetes, making it less suitable for complex containerized applications compared to GKE.
Therefore, the correct answer is A, Google Kubernetes Engine cluster.
Question 4
Which Google Cloud service provides actionable recommendations to address security threats and compliance gaps, helping organizations strengthen their overall security?
A. Google Cloud Firewalls
B. Security Command Center
C. Cloud Deployment Manager
D. Google Cloud Armor
Answer: B
Explanation:
The Security Command Center (SCC) is the Google Cloud service that provides actionable recommendations to improve security posture and address security threats and compliance gaps. It provides a centralized view of security and compliance across Google Cloud resources and services. SCC offers insights into potential vulnerabilities, misconfigurations, and risks within your Google Cloud environment and provides recommendations to help remediate them. This helps organizations strengthen their security by proactively addressing security threats and compliance concerns.
Option B, Security Command Center, is the correct choice, as it helps identify and mitigate security risks, vulnerabilities, and compliance issues.
Option A, Google Cloud Firewalls, focuses on network security by defining rules to control inbound and outbound traffic to virtual machines and other resources. While firewalls are crucial for securing your environment, they do not provide the broader set of recommendations for overall security and compliance like SCC does.
Option C, Cloud Deployment Manager, is a service for managing infrastructure as code and automating the deployment of resources but does not provide security-related recommendations.
Option D, Google Cloud Armor, is primarily a service designed to protect applications from DDoS (Distributed Denial of Service) attacks and is more focused on perimeter defense, not on providing recommendations for addressing security threats or compliance gaps.
Thus, the correct answer is B, Security Command Center.
Question 5
Which Google Cloud product offers a unified platform for deploying and managing applications across hybrid and multi-cloud environments, while integrating with other Google Cloud services?
A. Google Kubernetes Engine
B. Virtual Private Cloud
C. Compute Engine
D. Anthos
Correct Answer : D
Explanation:
Anthos is Google Cloud's platform for managing and deploying applications across hybrid and multi-cloud environments. It provides a unified interface that allows organizations to run and manage applications in their on-premises data centers, on Google Cloud, and even across other cloud providers. Anthos integrates seamlessly with other Google Cloud services and is designed to provide flexibility, scalability, and consistency in application deployment across diverse environments.
A. Google Kubernetes Engine - Google Kubernetes Engine (GKE) is a managed Kubernetes service, and while it can be part of a multi-cloud strategy, it is primarily designed to manage containerized applications in Google Cloud, not across hybrid or multi-cloud environments in the way that Anthos does.
B. Virtual Private Cloud - Virtual Private Cloud (VPC) is a networking service that enables you to create and manage a private network within Google Cloud. It is not a platform for deploying or managing applications across multiple cloud environments.
C. Compute Engine - Compute Engine provides virtual machines (VMs) in Google Cloud, which is useful for running applications but does not offer a unified platform for managing hybrid or multi-cloud environments, unlike Anthos.
D. Anthos is the correct answer, as it provides the unified platform for deploying and managing applications across hybrid and multi-cloud environments.
Question 6
You’re building a global online banking platform. Data consistency in every transaction is essential, and the system must scale with increasing data volumes. Which database offering should you use?
A. Cloud SQL
B. Cloud Storage
C. Firestore
D. Cloud Spanner
Correct Answer : D
Explanation:
Cloud Spanner is the ideal choice for a global online banking platform that requires strong consistency across transactions and the ability to scale as data volumes grow. Cloud Spanner is a globally distributed relational database service that offers ACID transactions, horizontal scalability, and strong consistency. It is designed for high availability and high performance at scale, making it well-suited for mission-critical applications like banking, where data consistency is crucial.
A. Cloud SQL - Cloud SQL is a fully-managed relational database service that is great for transactional databases, but it may not scale horizontally in the same way as Cloud Spanner. While Cloud SQL provides consistency, it is generally more suitable for smaller-scale applications compared to the scale and consistency required for a global banking platform.
B. Cloud Storage - Cloud Storage is an object storage service, typically used for storing unstructured data like files, images, and backups. It is not suitable for transactional systems, where data consistency in every transaction is essential.
C. Firestore - Firestore is a NoSQL document database that is great for web and mobile applications requiring real-time syncing and flexibility. While Firestore offers scalability, it does not provide the same level of ACID transactional consistency across global data as Cloud Spanner.
D. Cloud Spanner is the best option for building a global online banking platform where data consistency and scalability are critical.
Question 7
Your company needs a cost-efficient and secure storage solution for various file types like documents, images, and videos, with the ability to share access as needed. Which product should you choose?
A. Cloud Storage
B. Cloud SQL
C. Cloud Spanner
D. BigQuery
Answer: A
Explanation:
For a cost-efficient and secure storage solution for a variety of file types like documents, images, and videos, Cloud Storage is the ideal choice. Google Cloud Storage provides a scalable, durable, and secure solution for storing and retrieving files of any type. It offers features like fine-grained access control, versioning, and integration with other Google Cloud services. This makes it perfect for storing unstructured data (like documents, images, and videos) and sharing access securely as needed.
Option A, Cloud Storage, is the most appropriate solution for this use case. It supports various storage classes for cost optimization, such as Standard, Nearline, Coldline, and Archive, making it ideal for different data access needs.
Option B, Cloud SQL, is a fully managed relational database service designed for structured data, such as transactional data. It is not suited for storing unstructured files like documents and videos.
Option C, Cloud Spanner, is a highly scalable relational database service but is designed for large-scale applications and structured data. It is not designed for file storage.
Option D, BigQuery, is a data analytics service that is designed for analyzing large datasets. It is not meant for file storage, but rather for querying structured data in real-time.
Therefore, the correct answer is A, Cloud Storage.
Question 8
You aim to predict website visitor behavior using machine learning. Your team has strong database experience but limited ML knowledge. Which Google Cloud tool would best allow your team to build ML models using familiar SQL-like queries?
A. BigQuery ML
B. LookML
C. TensorFlow
D. Cloud SQL
Answer: A
Explanation:
BigQuery ML allows users to build machine learning models directly within BigQuery using SQL-like queries. This is ideal for teams with strong database experience but limited machine learning knowledge, as they can leverage their familiarity with SQL while applying machine learning models to their data. BigQuery ML supports a variety of ML models, such as linear regression, logistic regression, k-means clustering, and time-series forecasting, and it integrates seamlessly with BigQuery's data analytics capabilities.
Option A, BigQuery ML, is the best choice as it enables teams to build machine learning models without needing to have deep knowledge of ML frameworks. Using SQL syntax, your team can easily create and train models with minimal learning curve.
Option B, LookML, is a data modeling language used within Looker, a data analytics and business intelligence platform. It is not designed for building machine learning models and does not provide the capabilities needed for predicting website visitor behavior.
Option C, TensorFlow, is a powerful open-source machine learning framework. While it is highly versatile, it requires more advanced knowledge of machine learning and programming (typically in Python). It may not be the best fit for teams with limited ML knowledge.
Option D, Cloud SQL, is a managed relational database service. It does not provide tools for building or deploying machine learning models, and is better suited for structured data storage rather than machine learning model development.
Thus, the correct answer is A, BigQuery ML.
Question 9
You want to restrict access to a specific Cloud Storage bucket so only Canadian employees can view its contents. What’s the most effective way to enforce this policy?
A. Host the bucket in a Canada-based Google Cloud region
B. Use Google Cloud Armor to restrict access to Canadian IP addresses
C. Manually grant access to each Canadian employee
D. Create a group of Canadian employees and assign access to that group
Correct Answer : B
Explanation:
The most effective way to restrict access to a Cloud Storage bucket so that only Canadian employees can view its contents is by using Google Cloud Armor to restrict access to Canadian IP addresses. Cloud Armor provides application-level security, and using it to restrict access based on geographic IP addresses (in this case, Canada) ensures that only users in Canada can access the bucket. This method is effective because it allows for easy and scalable enforcement of the policy across all users, regardless of their individual credentials.
A. Host the bucket in a Canada-based Google Cloud region - Hosting the bucket in a Canada-based region limits the physical location of the data, but it does not enforce access control based on the user's location. Users outside Canada could still access the bucket if they have the correct permissions.
C. Manually grant access to each Canadian employee - While manually granting access would work, it is not scalable or efficient for a large organization. This method would require constant updates as employees join or leave, and it would be difficult to manage in the long term.
D. Create a group of Canadian employees and assign access to that group - Creating a group and assigning access is a good approach for managing access permissions. However, it does not specifically restrict access based on the geographic location of users. It could be used in conjunction with other access controls, but it wouldn't fully address the geographic restriction on its own.
B. Use Google Cloud Armor to restrict access to Canadian IP addresses is the most effective and scalable solution to restrict access to a Cloud Storage bucket based on geographic location.
Question 10
Your organization is building a web application that needs to respond to HTTP requests with low latency and scale automatically with traffic. You prefer a fully managed platform that doesn't require managing servers, and you plan to deploy containerized workloads.
Which Google Cloud service should you use?
A. App Engine
B. Cloud Functions
C. Cloud Run
D. Compute Engine
Correct Answer : C
Explanation:
Cloud Run is the best option for a web application that needs to respond to HTTP requests with low latency, automatically scale with traffic, and deploy containerized workloads. Cloud Run is a fully managed platform that runs containerized applications and scales automatically depending on the incoming traffic. It is designed for microservices and stateless applications, making it ideal for use cases where you don't want to manage servers or infrastructure.
A. App Engine - App Engine is a fully managed platform for building and deploying applications without managing infrastructure. However, it is not specifically optimized for containerized workloads, and its architecture is more focused on traditional app deployment (e.g., using standard environments like Python, Java, etc.), whereas Cloud Run is built for containerized workloads.
B. Cloud Functions - Cloud Functions is a serverless compute service designed to handle lightweight, event-driven functions. While it is a good option for handling individual events or functions, it is not designed for running full web applications or managing containerized workloads. Cloud Run is better suited for that use case.
D. Compute Engine - Compute Engine offers virtual machines (VMs) that provide full control over infrastructure. While this provides flexibility, it requires manual management of the VMs, scaling, and other components, which is not ideal for a fully managed platform where you prefer not to manage servers.
C. Cloud Run is the best choice because it offers the features you're looking for: automatic scaling, low-latency HTTP request handling, a fully managed environment, and the ability to deploy containerized workloads.
