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

Google CLOUD-DIGITAL-LEADER Online Questions & Answers

• Question 301:

  The Border Security Agency has hired your software services firm to build an application for them that will collect information about visas stamped on passports. You are given stamped images. You have to find out which country issued the visa and the period of validity. Pull out this data and put it into a database. Which of these applications would be suitable for that?

  A. Use Cloud Vision API-write code to identify the text blocks, copy the data, and store it
  B. Use TensorFlow-write code that will identify the type of visa and the bounding text blocks. Copy the data and then store it.
  C. Use AutoML-upload other images of visas and run the model creation process which will automatically identify the visas
  D. Use Data Labeling service-outsource the work of marking and extracting the in-formation to others.
  A. Use Cloud Vision API-write code to identify the text blocks, copy the data, and store it

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  Cloud Vision API allows you to programmatically identify images, text, etc. in the document. This would be the best option. https://cloud.google.com/vision

• Question 302:

  Which of the following statements is/are true about Google Cloud BigTable?

  A. It is not compatible with Hadoop.
  B. It Scales from Giga Byte to Peta Byte with No Downtime.
  C. It can not be used in Real-time Ad analytics and tracking thousands of IoT Devices Data.
  D. It is an enterprise-level Database that offers relational and non-relational features
  B. It Scales from Giga Byte to Peta Byte with No Downtime.

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  Cloud Bigtable A fully managed, scalable NoSQL database service for large analytical and operational workloads with up to 99.999% availability. -Consistent sub-10ms latency--handle millions of requests per second -Ideal for use cases such as personalization, ad tech, fintech, digital media, and IoT -Seamlessly scale to match your storage needs; no downtime during reconfiguration -Designed with a storage engine for machine learning applications leading to better predictions -Easily connect to Google Cloud services such as BigQuery or the Apache ecosystem

• Question 303:

  Your customer has a reporting tool that is only occasionally used by the leadership team. Usage of it is frequent-once a week, once a month, or once the quarter. They want to run this application in a cost-effective manner. What are the compute options available on Google Cloud which would be suitable? (Choose Two answer)

  A. Cloud Run
  B. Cloud App Engine Standard
  C. Compute Engine
  D. Kubernetes Engine
  A. Cloud Run
  B. Cloud App Engine Standard

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  Explanation Explanation/Reference:Since the use of the tool is infrequent/intermittent, you can choose to compute options that are serverless. Both Cloud Run and Cloud App Engine Standard are serverless options that can shut down to zero. Since cost-effectiveness is a requirement, this will not cost anything during the periods it is not used.

• Question 304:

  A retail organization is training a model to recommend products to customers for an ecommerce website. The model was trained on previous purchases, but did not include demographic information on each buyer. What dimension of the data is responsible for the model's poor performance?

  A. Validity
  B. Accuracy
  C. Timeliness
  D. Completeness
  D. Completeness

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  Completeness refers to the degree to which all necessary data is present and accounted for. In the context of machine learning, if a model is trained without including all relevant dimensions (such as demographic information in this case), it might lead to poor performance because it lacks important data needed to make accurate predictions. Completeness is correct because the lack of demographic information represents incomplete data. The absence of this data dimension could prevent the model from learning patterns that are influenced by demographic factors, thereby impacting its overall effectiveness. References: Google Cloud Documentation: Data Quality in Machine Learning Google Cloud AI Platform: Best Practices for Training Data Preparation

• Question 305:

  An organization has been struggling to make operations more efficient.

  What site reliability engineering (SRE) best practice should the organization follow to increase efficiency?

  A. Decrease over-reliance on data to make decisions.
  B. Assign exclusive production ownership to developers.
  C. Spend less time measuring outage impact.
  D. Focus on increasing toil automation.
  D. Focus on increasing toil automation.

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  Explanation Explanation/Reference:Toil refers to repetitive, manual operational work that does not provide long-term value and can be automated. By focusing on increasing toil automation, the organization can streamline operations, reduce manual intervention, and free up resources to focus on more strategic tasks. This approach improves efficiency by automating repetitive tasks, reducing human error, and allowing teams to focus on higher-value activities.

• Question 306:

  What is logging within the context of cloud technology?

  A. Writing application and operating system events as text
  B. Monitoring network and resource limitations
  C. Tracking source code across an organization
  D. Recording infrastructure and hardware expenditure
  A. Writing application and operating system events as text

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  Cloud Logging is a fully managed service that allows you to store, search, analyze, monitor, and alert on logging data and events from Google Cloud and Amazon Web Services

• Question 307:

  Your organization wants to migrate your on-premises environment to Google Cloud. The on-premises environment consists of containers and virtual machine instances. Which Google Cloud products can help to migrate the container images and the virtual machine disks?

  A. Compute Engine and Filestore
  B. Artifact Registry and Cloud Storage
  C. Dataflow and BigQuery
  D. Pub/Sub and Cloud Storage
  B. Artifact Registry and Cloud Storage

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  Artifact Registry: This service is designed to manage and store container images and other artifacts. You can use Artifact Registry to store and manage your container images, making it an ideal solution for migrating and managing your container workloads in Google Cloud. Cloud Storage: This service is suitable for storing and transferring large amounts of data, including virtual machine disk images. You can use Cloud Storage to upload and store VM disk images before importing them into Google Cloud's Compute Engine.

• Question 308:

  Your organization needs to plan its cloud infrastructure expenditures.

  Which should your organization do?

  A. Review cloud resource costs frequently, because costs change often based on use
  B. Review cloud resource costs annually as part of planning your organization's overall budget
  C. If your organization uses only cloud resources, infrastructure costs are no longer part of your overall budget
  D. Involve fewer people in cloud resource planning than your organization did for on-premises resource planning
  A. Review cloud resource costs frequently, because costs change often based on use

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  Review cloud resource costs frequently, because costs change often based on use because One need to know current usage/ trend for planning; While public cloud eliminates capex, and gets into pay as you go model, the usage pattern determines the cloud cost and hence needs to be measured frequently to enable better forecast

• Question 309:

  A customer has contacted you about migrating to Google Cloud. The customer would like to mi-grate their data from on premises as soon as possible. They don't have the budget to rewrite code, and they want the most direct route. What migration option should suggest to the customer?

  A. None, since the customer is not cloud native ready.
  B. Rip and Replace
  C. Lift and Shift
  D. Improve and Move
  C. Lift and Shift

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  Explanation Explanation/Reference:With Lift and Shift migrations, the customer could move workloads from a source environment to a target environment with few or no modifications or refactoring https://cloud.google.com/architecture/migration-to-gcp-getting-started

• Question 310:

  In terms of Cloud SQL for MySQL Features offered by Google Cloud Platform which of the statements is/are correct?

  A. Do not support Private IP (private service access).
  B. Customer data is encrypted on Google's internal networks and in database tables, temporary files, and backups.
  C. Do not Provide automated and on-demand backups and point-in-time recovery.
  D. None of the above
  B. Customer data is encrypted on Google's internal networks and in database tables, temporary files, and backups.

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  Cloud SQL for MySQL: Features -Fully managed MySQL Community Edition databases in the cloud. -Cloud SQL instances support MySQL 8.0, 5.7 (default), and 5.6, and provide up to 624 GB of RAM and 64 TB of data storage, with the option to automatically increase the storage size, as needed. -Create and manage instances in the Google Cloud Console. -Instances are available in the Americas, EU, Asia, and Australia. -Customer data is encrypted on Google's internal networks and in database tables, temporary files, and backups. -Support for secure external connections with the Cloud SQL Auth proxy or with the SSL/TLS protocol. -Support for private IP (private services access). -Data replication between multiple zones with automatic failover. -Import and export databases using mysqldump, or import and export CSV files. -Support for MySQL wire protocol and standard MySQL connectors. -Automated and on-demand backups and point-in-time recovery. -Instance cloning. -Integration with Google Cloud's operations suite logging and monitoring.