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

Google CLOUD-DIGITAL-LEADER Online Questions & Answers

• Question 91:

  Your multinational organization has servers running mission-critical workloads on its premises around the world. You want to be able to manage these workloads consistently and centrally, and you want to stop managing infrastructure.

  What should your organization do?

  A. Migrate the workloads to a public cloud
  B. Migrate the workloads to a central office building
  C. Migrate the workloads to multiple local co-location facilities
  D. Migrate the workloads to multiple local private clouds
  A. Migrate the workloads to a public cloud

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  Only public cloud offers to centrally manage the infra. for Pvt cloud it may not be possible to get same Pvt Cloud provider across the globe.

• Question 92:

  An organization wants to scale their existing virtual machine architecture as quickly as possible. Why should the organization use VMware Engine?

  A. To archive virtual machine instances.
  B. To deploy custom APIs seamlessly.
  C. To migrate virtual machines to containers.
  D. To replatform virtual machines as they are.
  D. To replatform virtual machines as they are.

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  Explanation Explanation/Reference:VMware Engine helps migrate and run virtual machines in Google Cloud with minimal changes to the VM architecture. Description automatically generated with medium confidence https://cloud.google.com/learn/what-is-a-virtual-machine

• Question 93:

  An organization cannot afford to modernize their infrastructure but they want to process data from their legacy system in a modern platform hosted by a business partner What solution should the organization choose to make their data accessible?

  A. Compute Engine
  B. Anthos
  C. An application programming interlace
  D. Google Kubernetes Engine
  C. An application programming interlace

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  Explanation Explanation/Reference:

• Question 94:

  Your client has an on-premises data center. Due to technical limitations, they are unable to scale globally. They have decided to adopt the public cloud. However, they don't want to locked into any one vendor and, therefore, would like to work with multiple cloud providers. They have used open source container technologies and would like to continue using them.

  A. Cloud Run which supports containers and can scale in a serverless fashion
  B. Kubernetes that runs containers as their core workloads
  C. AppEngine Flexible Environment which supports containers
  D. Anthos that runs containers as their core workloads
  D. Anthos that runs containers as their core workloads

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  Explanation Explanation/Reference:Anthos unifies the management of infrastructure and applications across on-premises, edge, and in multiple public clouds with a Google Cloud-backed control plane for consistent operation at scale.

• Question 95:

  What cloud service model would you want to select if you want to solve a particular busi-ness problem by providing CRM services in the cloud to your enterprises?

  A. CaaS
  B. SaaS
  C. PaaS
  D. IaaS
  B. SaaS

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  SaaS Software as a Service (SaaS) provides you a complete product that is run and managed by the service provider. You worry only about using the software and not about infrastructure. SaaS provides the lowest level of flexibility and management control over the infrastructure. (Example: Google Gsuite and MS O365)

• Question 96:

  An organization is building advanced machine learning models in Google Cloud by using TensorFlow. They want to develop their models faster with purpose-built hardware. Which solution should the organization use?

  A. TPUs
  B. CPUs
  C. CPUs
  D. GPUs
  A. TPUs

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  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. 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. References: Google Cloud: TPUs Overview Google Cloud AI and Machine Learning Products: Accelerators for TensorFlow

• Question 97:

  Why should an organization consider the total cost of ownership (TCO) when moving from on-premises to the cloud?

  A. To evaluate error budget
  B. To understand service level availability
  C. To evaluate return on investment
  D. To calculate required compute power
  C. To evaluate return on investment

• Question 98:

  A customer has new applications to build that has to handle both batch data and streaming data. Which product should they choose?

  A. Dataprep
  B. Dataflow
  C. Dataproc
  D. Data Fusion
  B. Dataflow

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  Explanation Explanation/Reference:Dataflow is the managed version of Apache Beam. Beam = Batch + Stream. Unified stream and batch data processing that's serverless, fast, and cost-effective. Reference link-https://cloud.google.com/dataflow

• Question 99:

  A customer in the European Union region is very clear that their data should not go outside the Eu-ropean Union. Their end users are spread all over the European U. They have to choose a storage option that serves all the users within Asia via web browsers as quickly as possible. Which storage option will work for them?

  

  A. Cloud Storage with a single region that is known to be within the European U
  B. Cloud Filestore is connected to virtual machines which are guaranteed to be within the European U
  C. Cloud Storage with the multi-region option of European U
  D. Cloud Storage with the dual-region option of European U
  C. Cloud Storage with the multi-region option of European U

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  Multi-region option will use multiple datacenters that are within the European Union. More regions will also help with lower latency since users are spread across the European U. https://cloud.google.com/storage/docs/locations#considerations

• Question 100:

  A manufacturing organization has a large collection of images labeled as intact or defective parts. They want to use this data to build a simple solution to detect faulty parts on their production line. They have no data science expertise. Which solution should they use?

  A. Pre-trained APIs
  B. Document AI
  C. AutoML
  D. Discovery AI for Retail
  C. AutoML

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  The organization wants to build a solution to detect faulty parts on a production line using a large collection of labeled images (intact or defective parts). They do not have data science expertise, so they need a tool that simplifies the machine learning process. Google Cloud Product Relevance: Why Not Other Options: Google Cloud Digital Leader References: For more information on AutoML, refer to the AutoML Vision documentation.