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Google Professional-Cloud-Database-Engineer Exam is a certification exam offered by Google Cloud. It is designed for professionals who want to demonstrate their expertise in designing, developing, and managing database solutions on Google Cloud Platform. Google Cloud Certified - Professional Cloud Database Engineer certification is called Google Cloud Certified - Professional Cloud Database Engineer.

To become a Google Professional-Cloud-Database-Engineer, candidates must have a deep understanding of database management systems, including relational databases, NoSQL databases, and data warehousing solutions. They must also have experience in designing and implementing scalable and resilient database architectures using GCP's database services such as Cloud SQL, Cloud Spanner, and Bigtable. Additionally, candidates must have a good understanding of SQL and programming languages such as Java or Python.

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Because the Google Cloud Certified - Professional Cloud Database Engineer (Professional-Cloud-Database-Engineer) practice exams create an environment similar to the real test for its customer so they can feel themselves in the Google Cloud Certified - Professional Cloud Database Engineer (Professional-Cloud-Database-Engineer) real test center. This specification helps them to remove Google Cloud Certified - Professional Cloud Database Engineer (Professional-Cloud-Database-Engineer) exam fear and attempt the final test confidently.

Google Professional-Cloud-Database-Engineer certification exam consists of multiple-choice and multiple-select questions that assess a candidate's knowledge and skills in database design, data modeling, database migration, database administration, and database optimization. Professional-Cloud-Database-Engineer Exam evaluates a candidate's ability to design, implement, and manage highly available, scalable, and secure database solutions on Google Cloud Platform.

Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q90-Q95):

NEW QUESTION # 90
Your organization is running a critical production database on a virtual machine (VM) on Compute Engine. The VM has an ext4-formatted persistent disk for data files. The database will soon run out of storage space. You need to implement a solution that avoids downtime. What should you do?

Answer: C


NEW QUESTION # 91
Your company is migrating a legacy on-premises Oracle database to Cloud SQL for PostgreSQL.
As a part of the migration, you need to convert schema and other database code objects, such as procedures, functions, and triggers, from Oracle to PostgreSQL. The database migration needs to be accomplished with minimal application code changes and manual intervention. What is the Google-recommended approach you should do-

Answer: D

Explanation:
Use Database Migration Service's conversion workspace to auto-convert your Oracle schema and PL/SQL code into PostgreSQL DDL and PL/pgSQL. Then simply review and refactor any edge cases - this approach minimizes manual rewrites and keeps application changes to a minimum.


NEW QUESTION # 92
Your customer has a global chat application that uses a multi-regional Cloud Spanner instance.
The application has recently experienced degraded performance after a new version of the application was launched. Your customer asked you for assistance. During initial troubleshooting, you observed high read latency. What should you do?

Answer: D

Explanation:
Read statistics provide insight into how an application is using the database, and are useful when investigating performance issues.
https://cloud.google.com/spanner/docs/introspection/read-statistics


NEW QUESTION # 93
You need to perform a one-time migration of data from a running Cloud SQL for MySQL instance in the us-central1 region to a new Cloud SQL for MySQL instance in the us-east1 region. You want to follow Google-recommended practices to minimize performance impact on the currently running instance. What should you do?

Answer: A

Explanation:
https://cloud.google.com/sql/docs/mysql/import-export#serverless


NEW QUESTION # 94
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?

Answer: B

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 # 95
......

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