GOOGLE PROFESSIONAL-CLOUD-DATABASE-ENGINEER DUMP CHECK, NEW PROFESSIONAL-CLOUD-DATABASE-ENGINEER EXAM DISCOUNT

Google Professional-Cloud-Database-Engineer Dump Check, New Professional-Cloud-Database-Engineer Exam Discount

Google Professional-Cloud-Database-Engineer Dump Check, New Professional-Cloud-Database-Engineer Exam Discount

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As is known to us, the leading status of the knowledge-based economy has been established progressively. It is more and more important for us to keep pace with the changeable world and improve ourselves for the beautiful life. So the Professional-Cloud-Database-Engineer certification has also become more and more important for all people. Because a lot of people long to improve themselves and get the decent job. In this circumstance, more and more people will ponder the question how to get the Professional-Cloud-Database-Engineer Certification successfully in a short time.

To earn the Google Professional-Cloud-Database-Engineer Certification, candidates must pass a single exam that tests their knowledge and skills in designing, developing, and managing secure and scalable database solutions on the Google Cloud Platform. Professional-Cloud-Database-Engineer exam consists of multiple-choice questions and is administered online.

Google Professional-Cloud-Database-Engineer certification exam is a highly recognized certification in the IT industry. Google Cloud Certified - Professional Cloud Database Engineer certification exam provides professionals with the skills and knowledge to design, develop, and manage highly scalable, secure, and available databases on the Google Cloud Platform. Passing this certification exam demonstrates a high level of expertise in cloud database engineering, which can help professionals advance their careers and improve their job opportunities.

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To become a Google Cloud Certified Professional-Cloud-Database-Engineer, candidates must pass a two-hour computer-based exam that consists of multiple-choice and multiple-response questions. Professional-Cloud-Database-Engineer Exam is designed to test a candidate's ability to design, develop, and manage cloud-based databases on Google Cloud Platform. Candidates must have a strong understanding of database management, database security, and database performance tuning.

Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q57-Q62):

NEW QUESTION # 57
You recently launched a new product to the US market. You currently have two Bigtable clusters in one US region to serve all the traffic. Your marketing team is planning an immediate expansion to APAC. You need to roll out the regional expansion while implementing high availability according to Google-recommended practices. What should you do?

  • A. Maintain a target of 35% CPU utilization by locating:
    cluster-a in zone us-central1-a
    cluster-b in zone australia-southeast1-a
    cluster-c in zone europe-west1-d
    cluster-d in zone asia-east1-b
  • B. Maintain a target of 23% CPU utilization by locating:
    cluster-a in zone us-central1-a
    cluster-b in zone europe-west1-d
    cluster-c in zone asia-east1-b
  • C. Maintain a target of 23% CPU utilization by locating:
    cluster-a in zone us-central1-a
    cluster-b in zone us-central1-b
    cluster-c in zone us-east1-a
  • D. Maintain a target of 35% CPU utilization by locating:
    cluster-a in zone us-central1-a
    cluster-b in zone us-central2-a
    cluster-c in zone asia-northeast1-b
    cluster-d in zone asia-east1-b

Answer: D


NEW QUESTION # 58
Your organization has hundreds of Cloud SQL for MySQL instances. You want to follow Google-recommended practices to optimize platform costs. What should you do?

  • A. Use Query Insights to identify idle instances.
  • B. Run the Recommender API to identify overprovisioned instances.
  • C. Build indexes on heavily accessed tables.
  • D. Remove inactive user accounts.

Answer: B


NEW QUESTION # 59
You released a popular mobile game and are using a 50 TB Cloud Spanner instance to store game data in a PITR-enabled production environment. When you analyzed the game statistics, you realized that some players are exploiting a loophole to gather more points to get on the leaderboard. Another DBA accidentally ran an emergency bugfix script that corrupted some of the data in the production environment. You need to determine the extent of the data corruption and restore the production environment. What should you do? (Choose two.)

  • A. If the corruption is significant, use backup and restore, and specify a recovery timestamp.
  • B. If the corruption is insignificant, use backup and restore, and specify a recovery timestamp.
  • C. If the corruption is insignificant, perform a stale read and specify a recovery timestamp. Write the results back.
  • D. If the corruption is significant, use import and export.
  • E. If the corruption is significant, perform a stale read and specify a recovery timestamp. Write the results back.

Answer: A,C

Explanation:
https://cloud.google.com/spanner/docs/pitr#ways-to-recover
To recover the entire database, backup or export the database specifying a timestamp in the past and then restore or import it to a new database. This is typically used to recover from data corruption issues when you have to revert the entire database to a point-in-time before the corruption occurred.
This part describes significant corruption - A
To recover a portion of the database, perform a stale read specifying a query-condition and timestamp in the past, and then write the results back into the live database. This is typically used for surgical operations on a live database. For example, if you accidentally delete a particular row or incorrectly update a subset of data, you can recover it with this method.
This describes insignificant corruption case - E
https://cloud.google.com/spanner/docs/pitr https://cloud.google.com/spanner/docs/backup/restore-backup


NEW QUESTION # 60
You want to migrate an existing on-premises application to Google Cloud. Your application supports semi- structured data ingested from 100,000 sensors, and each sensor sends 10 readings per second from manufacturing plants. You need to make this data available for real-time monitoring and analysis. What should you do?

  • A. Deploy the database using Cloud Spanner.
  • B. Deploy the database using Bigtable.
  • C. Use BigQuery, and load data in batches.
  • D. Deploy the database using Cloud SQL.

Answer: C

Explanation:
Bigtable is a scalable, fully managed, and high-performance NoSQL database service that can handle semi- structured data and support real-time monitoring and analysis. Cloud SQL is a relational database service that does not support semi-structured data. BigQuery is a data warehouse service that is optimized for batch processing and analytics, not real-time monitoring. Cloud Spanner is a relational database service that supports semi-structured data with JSON data type, but it is more expensive and complex than Bigtable for this use case.


NEW QUESTION # 61
You support a consumer inventory application that runs on a multi-region instance of Cloud Spanner. A customer opened a support ticket to complain about slow response times. You notice a Cloud Monitoring alert about high CPU utilization. You want to follow Google-recommended practices to address the CPU performance issue. What should you do first?

  • A. Increase the number of processing units.
  • B. Decrease the number of processing units.
  • C. Modify the database schema, and add additional indexes.
  • D. Shard data required by the application into multiple instances.

Answer: A

Explanation:
In case of high CPU utilization like, mentioned in question, refer: https://cloud.google.com/spanner/docs/identify-latency-point#:~:text=Check%20the%20CPU%20utilization%20of%20the%20instance.%20If%20the%20CPU%20utilization%20of%20the%20instance%20is%20above%20the%20recommended%20level%2C%20you%20should%20manually%20add%20more%20nodes%2C%20or%20set%20up%20auto%20scaling. "Check the CPU utilization of the instance. If the CPU utilization of the instance is above the recommended level, you should manually add more nodes, or set up auto scaling." Indexes and schema are reviewed post identifying query with slow performance. Refer : https://cloud.google.com/spanner/docs/troubleshooting-performance-regressions#review-schema


NEW QUESTION # 62
......

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