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

Google CLOUD-DIGITAL-LEADER Online Questions & Answers

• Question 221:

  Your organization needs to establish private network connectivity between its on-premises network and its workloads running in Google Cloud. You need to be able to set up the connection as soon as possible.

  Which Google Cloud product or feature should you use?

  A. Cloud Interconnect
  B. Direct Peering
  C. Cloud VPN
  D. Cloud CDN
  C. Cloud VPN

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  To establish private network connectivity between your on-premises network and workloads running in Google Cloud, you should use Google Cloud VPN (Virtual Private Network). Google Cloud VPN allows you to securely connect your on-premises network to your virtual private cloud (VPC) network in Google Cloud. It enables encrypted communication over the public internet, providing a secure and private connection between your on-premises environment and your cloud resources.

• Question 222:

  An organization has collected petabytes of historical data. They need an advanced analysis solution that is fast, scalable, and fully managed. Which Google product or service should the organization use?

  A. BigQuery
  B. Cloud SQL
  C. Firestore
  D. Cloud Storage
  A. BigQuery

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  BigQuery is a fully managed, serverless data warehouse that is designed for large-scale data analysis. It is optimized for handling petabytes of data and provides fast query performance. It is scalable and supports advanced analytical queries, making it ideal for organizations that need to analyze massive amounts of historical data efficiently. BigQuery is correct because it is specifically designed for large-scale, advanced data analytics and is fully managed by Google Cloud. References: Google Cloud: BigQuery Product Overview Google Cloud BigQuery: Advanced Data Analysis Capabilities

• Question 223:

  An organization is transforming their raw data into a format that can be used to derive business insights Which step of the data value chain does this action represent?

  A. Data collection
  B. Data analysis
  C. Data processing
  D. Data storage
  C. Data processing

• Question 224:

  A customer is migrating there on-promises data analytics solution to Google Cloud. The current solution has a lot of data being read form and written to disk. The performance of this approach has occasionally been a bottleneck for a scale of operations that your cus-tomer has. The application is fault tolerant and can with stand machine going down fre-quently. In moving to Google Cloud they are asking your advice on any way to improve performance?

  A. Use Big Query Which has very fast data access and analysis
  B. Use Cloud Storage which can be central, scalable storage
  C. Use local SSDs with the VMs
  D. Use Persistent Disk with the VMs
  C. Use local SSDs with the VMs

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  Local SSDs are attached to the VM and have very high throughput. However, when the VM shuts down, The local SSD is also shut down, Since our Workload here is foult tolerant, than is not an issue.

• Question 225:

  Your organization runs a distributed application in the Compute Engine virtual machines. Your organization needs redundancy, but it also needs extremely fast communication (less than 10 milliseconds) between the parts of the application in different virtual machines.

  Where should your organization locate this virtual machines?

  A. In a single zone within a single region
  B. In different zones within a single region
  C. In multiple regions, using one zone per region
  D. In multiple regions, using multiple zones per region
  B. In different zones within a single region

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  Multi zone is also redundant within the region and it provides the lowest latency. Reference link: https://cloud.google.com/solutions/best-practices-compute-engine-region-selection

• Question 226:

  An international bank is looking for a serverless warehouse solution that lets them perform smart analytics Which Google Cloud product or service should the bank use?

  A. BigQuery
  B. Dataflow
  C. Compute Engine
  D. Cloud Spanner
  A. BigQuery

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  Explanation Explanation/Reference:The international bank should use Google Cloud's BigQuery service, which is a fully managed, serverless data warehouse that allows for high-speed analysis of large datasets. It provides a range of built-in functions for analytics and can easily integrate with other Google Cloud services.

• Question 227:

  Your organization needs to allow a production job to have access to a BigQuery dataset. The production job is running on a Compute Engine instance that is part of an instance group. What should be included in the IAM Policy on the BigQuery dataset?

  A. The Compute Engine instance group
  B. The project that owns the Compute Engine instance
  C. The Compute Engine service account
  D. The Compute Engine instance
  C. The Compute Engine service account

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  Explanation Explanation/Reference:When an identity calls a Google Cloud API, BigQuery requires that the identity has the appropriate permissions to use the resource. You can grant permissions by granting roles to a user, a group, or a service account. Reference link-https:// cloud.google.com/bigquery/docs/access-control

• Question 228:

  Your organization wants an economical solution to store data such as files, graphical images, and videos and to access and share them securely. Which Google Cloud product or service should your organization use?

  A. Cloud Storage
  B. Cloud SQL
  C. Cloud Spanner
  D. BigQuery
  A. Cloud Storage

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  Explanation Explanation/Reference:Google Storage is GCP's version of AWS Simple Storage Service (S3) and an S3 bucket would be equivalent to a Google Storage bucket across the two clouds

• Question 229:

  You are discussing scaling requirements with a gaming company. When the game launches, they are expecting incoming data surges of 2 million users or more during weekends and holidays. Their on-premise systems have had issues scaling and they want your advice on solving the issue. What do you recommend?

  A. Either Compute Engine VMs or Kubernetes nodes work, but it is better to keep a buffer of an extra 2 million users.
  B. We can deploy a Pub/Sub to ingest data which will grow to absorb demand and pass it on to other stages.
  C. We will allocate Compute Engine VMs estimating 80% capacity of 2 million users.
  D. We will allocate Kubernetes nodes estimating 80% capacity of 2 million users.
  B. We can deploy a Pub/Sub to ingest data which will grow to absorb demand and pass it on to other stages.

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  When there are huge surges in demand, it is preferable to use serverless technologies that automatically scale on demand. In this case, the key concern is data ingestion. Pub/Sub is a serverless system that can expand to absorb such demand.

• Question 230:

  Customer Managed Encryption Keys (CMEK) can be used for encrypting data inside Cloud BigTable, which of the following statements is/are correct. (Select two answer)

  A. Administrators can not rotate
  B. Not supported for instances that have clustered in more than one region.
  C. CMEK can only be configured at the cluster level.
  D. You can not use the same CMEK key in multiple projects
  B. Not supported for instances that have clustered in more than one region.
  C. CMEK can only be configured at the cluster level.

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  Customer-managed encryption keys for Cloud BigTable. By default, all the data at rest in Cloud Bigtable is encrypted using Google's default encryption. Bigtable handles and manages this encryption for you without any additional action on your part. If you have specific compliance or regulatory requirements related to the keys that protect your data, you can use customer-managed encryption keys (CMEK) for BigTable. Instead of Google managing the encryption keys that protect your data, your BigTable instance is protected using a key that you control and manage in Cloud Key Management Service (Cloud KMS). Features Security: CMEK provides the same level of security as Google's default encryption but provides more administrative control. Data access control: Administrators can rotate, manage access to, and disable or destroy the key used to protect data at rest in BigTable . Auditability: All actions on your CMEK keys are logged and viewable in Cloud Logging. Comparable performance: BigTable CMEK-protected instances offer comparable performance to BigTable instances that use Google default encryption. Flexibility: You can use the same CMEK key in multiple projects or instances or you can use separate keys, depending on your business needs.