Google CLOUD-DIGITAL-LEADER Online Practice Questions and Exam Preparation

Google CLOUD-DIGITAL-LEADER Online Questions & Answers

• Question 111:

  An organization wants to ensure that they grant users only the permissions they require to perform their job responsibilities. Which security principle describes this approach?

  A. Cyber resilience
  B. Zero-trust
  C. Least privilege
  D. Security by default
  C. Least privilege

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  The organization wants to ensure that users are granted only the permissions required for their job responsibilities, aligning with a specific security principle. Google Cloud Product Relevance: Why Not Other Options: Google Cloud Digital Leader References: Refer to Google Cloud IAM documentation for more information on implementing the principle of least privilege in Google Cloud.

• Question 112:

  An IoT platform is providing services to home security systems. They have more than a million customers, each with many home devices. Burglaries or child safety issues are concerns that the clients customers. Therefore, the platform has to respond very quickly in near real time. What could be a typical data pipeline used to support this platform on Google Cloud?

  A. Cloud Pub/Sub, Cloud Dataflow, Data Studio
  B. Cloud Functions, Cloud Dataproc, Looker
  C. Cloud Pub/Sub, Cloud Dataflow, BigQuery
  D. Cloud Functions, Cloud Dataproc, BigQuery
  A. Cloud Pub/Sub, Cloud Dataflow, Data Studio

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  Explanation Explanation/Reference: => Cloud Pub/Sub-Cloud Pub/Sub is the best to be the end-point for ingesting large amounts of data. It will grow as required, can stream data to downstream systems, and can also work with intermittently available backends. => Cloud Dataflow-supports streaming data and therefore is an appropriate option for processing the data that is ingested. => BigQuery-BigQuery also supports streaming data and its possible to do real time ana-lytics on it. => DataStudio-DataStudio and Looker are for visualization. They don't have any in-built analysis. => Cloud Functions-Cloud Functions is a useful serverless endpoint. However, Pub/Sub is better in this case because it can also retain messages for a set period if it was not possi-ble to deliver it first time. =>Cloud Dataproc-Cloud Dataproc is used for Hadoop/Spark workloads and won't be a good fit here.

• Question 113:

  Which of the following is/are true about Bare Metal Solutions?

  A. Enterprise-grade deployment platform
  B. All your existing investment in tooling and best practices will work as is
  C. Continue to run any version, and feature set, any database option, and any cus-tomizations (patchsets)
  D. All of the Above.
  D. All of the Above.

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  Bare Metal Solution for Oracle Bring your Oracle workloads to Google Cloud with Bare Metal Solution and jumpstart your cloud journey with minimal risk. Continue to run any version, any feature set, any database option, and any customizations (patchsets) Enterprise-grade deployment platform High availability with Oracle RAC Works with any application, any Oracle versions

• Question 114:

  An organization needs protection against distributed denial-of-service (DDoS) attacks. Which Google Cloud service should the organization use?

  A. Google Cloud Armor
  B. Cloud Build
  C. Cloud VPN
  D. Security Command Center
  A. Google Cloud Armor

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  Explanation Explanation/Reference: Google Cloud Armor is a service that provides protection against Distributed Denial-of-Service (DDoS) attacks. It offers a scalable web application firewall (WAF) that helps to defend against layer 3, 4, and 7 DDoS attacks, ensuring that applications remain available and responsive. Google Cloud Armor is correct because it is specifically designed to provide protection against DDoS attacks. References: Google Cloud Armor: DDoS Protection and WAF Features Google Cloud Security: Overview of DDoS Protection Services

• Question 115:

  In terms of Dockers and Kubernetes, which of the following statements are correct?

  A. Kubernetes uses Docker to deploy, manage, and scale containerized applications.
  B. Difference between Docker and Kubernetes relates to the role each play in con-tainerizing and running your applications
  C. Kubernetes can be used with or without Docker.
  D. All of the above.
  D. All of the above.

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  Kubernetes vs. Docker Often misunderstood as a choice between one or the other, Kubernetes and Docker are different yet complementary technologies for running containerized applications. Docker lets you put everything you need to run your application into a box that can be stored and opened when and where it is required. Once you start boxing up your applications, you need a way to manage them; and that's what Kubernetes does. Kubernetes is a Greek word meaning `captain' in English. Like the captain is responsible for the safe journey of the ship in the seas, Kubernetes is responsible for carrying and delivering those boxes safely to locations where they can be used. -Kubernetes can be used with or without Docker. -Docker is not an alternative to Kubernetes, so it's less of a "Kubernetes vs. Docker" question. It's about using Kubernetes with Docker to containerize your applications and run them at scale. -The difference between Docker and Kubernetes relates to the role each play in containerizing and running your applications. -Docker is an open industry standard for packaging and distributing applications in containers. -Kubernetes uses Docker to deploy, manage, and scale containerized applications.

• Question 116:

  The customer has applications that do data processing on-premise. They have been built using Ha-doop and Spark. What product should I use on Google Cloud?

  A. Dataproc
  B. Dataflow
  C. Dataprep
  D. Dataplex
  A. Dataproc

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  Explanation Explanation/Reference:Because Dataproc is used to run Hadoop/Spark workloads

• Question 117:

  An organization wants to analyze data in a data warehouse. How should they proceed?

  A. Import data into a semi-structured time-series database.
  B. Choose a system to store structured and semi-structured data that supports ad-hoc analysis and custom reporting.
  C. Copy unstructured data into a single large object store.
  D. Ensure data is stored in structured tables and rows to support transactional queries and relationships.
  B. Choose a system to store structured and semi-structured data that supports ad-hoc analysis and custom reporting.

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  To analyze data in a data warehouse, the organization should use a system that can handle both structured and semi-structured data while supporting ad-hoc analysis and custom reporting. A data warehouse like BigQuery is designed to efficiently store and query large amounts of structured and semi-structured data, allowing for flexible and real-time analytical queries. Choose a system to store structured and semi-structured data that supports ad-hoc analysis and custom reporting is correct because it aligns with the capabilities needed for effective data warehousing and analysis. References: Google Cloud BigQuery: Data Warehousing and Analysis Google Cloud Data Solutions: Ad-hoc Analysis and Reporting Tools

• Question 118:

  An organization stores its important industry data in a relational database

  They want to create a new revenue stream by enabling third parties to use that data in their applications

  Which cloud first approach should the organization choose?

  A. Offer chargeable downloads of archived data.
  B. Transfer data into a non-relational database
  C. Add third-party users to their database
  D. Expose data through a chargeable API
  D. Expose data through a chargeable API

• Question 119:

  An organization wants its users to validate a series of new features for their app. Why should they use App Engine?

  A. Because their app is containerized and enabled by microservices
  B. Because the updated app will only include new features
  C. To run different versions of the app for different users
  D. To run different versions of the app for the same user
  C. To run different versions of the app for different users

• Question 120:

  What according to you are NOT the key capabilities of In-App Messaging?

  A. Target messages accordingly to the change in the behavior pattern of the target audience.
  B. Creating customized and flexible alerts
  C. Increasing conversion for user-to-user sharing
  D. Sending relevant messages to the target audience
  C. Increasing conversion for user-to-user sharing

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  In-App Messaging Engage active app users with contextual messages. Firebase In-App Messaging helps you engage users who are actively using your app by sending them targeted and contextual messages that nudge them to complete key in-app actions-like beating a game level, buying an item, or subscribing to content.