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Professional-Cloud-Database-Engineer–100% Free Reliable Test Forum | Authoritative Dumps Google Cloud Certified - Professional Cloud Database Engineer Vce
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The Google Professional-Cloud-Database-Engineer exam measures an individual's knowledge and skills in various areas, including database design, development, management, monitoring, and optimization. It also tests one's ability to use Google Cloud Platform services such as Cloud SQL, Cloud Spanner, Cloud Bigtable, and Cloud Datastore to build and manage cloud-based databases.
Earning the Google Professional-Cloud-Database-Engineer certification can be a valuable asset for professionals who work with databases on the Google Cloud Platform. It demonstrates to employers and clients that they have the skills and knowledge needed to design, manage, and optimize databases in a cloud environment, and can help them advance their careers in this field.
To prepare for the Professional-Cloud-Database-Engineer Exam, candidates should have a solid understanding of database concepts and technologies, as well as experience working with databases on the Google Cloud Platform. They should also be familiar with cloud computing concepts and technologies, such as virtualization, networking, and storage. Candidates can prepare for the exam by taking online courses, attending training sessions, and studying the official exam guide provided by Google.
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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q101-Q106):
NEW QUESTION # 101
You currently have a MySQL database running on Cloud SQL with a read replica in a different zone for non- mission critical analytics workloads. You want to enable high availability (HA) for the analytic workloads while keeping costs low. What should you do?
- A. Enable HA on the current read replica.
- B. Create a new MA Instance in a different region than the primary.
- C. Increase the size of the read replica Instance and enable MA.
- D. Create a new HA instance in the same zone db lie primary.
Answer: A
NEW QUESTION # 102
Your company is migrating the existing infrastructure for a highly transactional application to Google Cloud.
You have several databases in a MySQL database instance and need to decide how to transfer the data to Cloud SQL. You need to minimize the downtime for the migration of your 500 GB instance. What should you do?
- A. Create migration job using Database Migration Service.
Set the migration job type to Continuous, and allow the databases to complete the full dump phase and start sending data in change data capture (CDC) mode.
Wait for the replication delay to minimize, initiate a promotion of the new Cloud SQL instance, and wait for the migration job to complete.
Update your application connections to the new instance. - B. Use the mysqldump utility to manually initiate a backup of MySQL during the application maintenance window.
Move the files to Cloud Storage, and import each database into your Cloud SQL instance.
Continue to dump each database until all the databases are migrated.
Update your application connections to the new instance. - C. Create a Cloud SQL for MySQL instance for your databases, and configure Datastream to stream your database changes to Cloud SQL.
Select the Backfill historical data check box on your stream configuration to initiate Datastream to backfill any data that is out of sync between the source and destination.
Delete your stream when all changes are moved to Cloud SQL for MySQL, and update your application to use the new instance. - D. Create migration job using Database Migration Service.
Set the migration job type to One-time, and perform this migration during a maintenance window.
Stop all write workloads to the source database and initiate the dump. Wait for the dump to be loaded into the Cloud SQL destination database and the destination database to be promoted to the primary database.
Update your application connections to the new instance.
Answer: A
Explanation:
https://cloud.google.com/datastream/docs/overview.
NEW QUESTION # 103
Your project is using Bigtable to store data that should not be accessed from the public internet under any circumstances, even if the requestor has a valid service account key. You need to secure access to this data.
What should you do?
- A. Use Identity and Access Management (IAM) for Bigtable access control.
- B. Use VPC Service Controls to create a trusted network for the Bigtable service.
- C. Use Google Cloud Armor to add IP addresses to an allowlist.
- D. Use customer-managed encryption keys (CMEK).
Answer: B
Explanation:
"Users can define a security perimeter around Google Cloud resources such as Cloud Storage buckets, Bigtable instances, and BigQuery datasets to constrain data within a VPC and control the flow of data."
https://cloud.google.com/vpc-service-controls
NEW QUESTION # 104
Your company is developing a new global transactional application that must be ACID-compliant and have
99.999% availability. You are responsible for selecting the appropriate Google Cloud database to serve as a datastore for this new application. What should you do?
- A. Use Firestore.
- B. Use Cloud Spanner.
- C. Use Bigtable.
- D. Use Cloud SQL.
Answer: B
NEW QUESTION # 105
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 Cloud SQL.
- C. C.Deploy the database using Bigtable.
- D. Use BigQuery, and load data in batches.
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 dat a. 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 # 106
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