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Google Cloud Certified - Professional Cloud Database Engineer certification is an excellent way for IT professionals to demonstrate their expertise in cloud-based database management. It is a valuable credential for individuals seeking career advancement opportunities in the field of cloud computing. With this certification, individuals can demonstrate their knowledge and skills to potential employers and clients, making them stand out in a competitive job market.

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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 Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q162-Q167):

NEW QUESTION # 162
Your company wants to migrate an Oracle-based application to Google Cloud. The application team currently uses Oracle Recovery Manager (RMAN) to back up the database to tape for long-term retention (LTR). You need a cost-effective backup and restore solution that meets a 2-hour recovery time objective (RTO) and a 15-minute recovery point objective (RPO). What should you do?

A. Migrate the Oracle databases to Bare Metal Solution for Oracle, and store backups on tapes on-premises.
B. Migrate the Oracle databases to Bare Metal Solution for Oracle, and back up the Oracle databases to Cloud Storage using the Standard Storage class.
C. Migrate the Oracle databases to Compute Engine, and store backups on tapes on-premises.
D. Migrate the Oracle databases to Bare Metal Solution for Oracle, and use Actifio to store backup files on Cloud Storage using the Nearline Storage class.

Answer: D

Explanation:
https://www.actifio.com/solutions/cloud/google/

NEW QUESTION # 163
Your ecommerce website captures user clickstream data to analyze customer traffic patterns in real time and support personalization features on your website. You plan to analyze this data using big data tools. You need a low-latency solution that can store 8 TB of data and can scale to millions of read and write requests per second. What should you do?

A. Stream your data into BigQuery and use Dataproc and the BigQuery Storage API to analyze large volumes of data.
B. Deploy a Cloud SQL environment with read replicas for improved performance. Use Datastream to export data to Cloud Storage and analyze with Dataproc and the Cloud Storage connector.
C. Write your data into Bigtable and use Dataproc and the Apache Hbase libraries for analysis.
D. Use Memorystore to handle your low-latency requirements and for real-time analytics.

Answer: C

Explanation:
Start with the lowest tier and smallest size and then grow your instance as needed. Memorystore provides automated scaling using APIs, and optimized node placement across zones for redundancy. Memorystore for Memcached can support clusters as large as 5 TB, enabling millions of QPS at very low latency

NEW QUESTION # 164
You are responsible for designing a new database for an airline ticketing application in Google Cloud. This application must be able to:
- Work with transactions and offer strong consistency.
- Work with structured and semi-structured (JSON) data.
- Scale transparently to multiple regions globally as the operation
grows.
You need a Google Cloud database that meets all the requirements of the application. What should you do?

A. Use Firestore in Datastore mode.
B. Use a Bigtable instance with clusters in multiple regions.
C. Use Cloud Spanner in a multi-region configuration.
D. Use Cloud SQL for PostgreSQL with both cross-region read replicas.

Answer: C

NEW QUESTION # 165
You are migrating your 2 TB on-premises PostgreSQL cluster to Compute Engine. You want to set up your new environment in an Ubuntu virtual machine instance in Google Cloud and seed the data to a new instance. You need to plan your database migration to ensure minimum downtime. What should you do?

A. 1. Take a full export while the database is offline.
2. Create a bucket in Cloud Storage.
3. Transfer the dump file to the bucket you just created.
4. Restore the backup into the Google Cloud primary server.
B. 1. Take a full export while the database is online.
2. Create a bucket in Cloud Storage.
3. Transfer the dump file and write-ahead logs to the bucket you just created.
4. Restore the dump file into the Google Cloud primary server.
5. Create a recovery.conf file in the $PG_DATA directory.
6. Stop the source database.
7. Transfer the write-ahead logs to the bucket you created before.
8. Start the PostgreSQL service.
9. Wait until the Google Cloud primary server syncs with the running primary server.
C. 1. Take a full export while the database is offline.
2. Create a bucket in Cloud Storage.
3. Transfer the dump file to the bucket you just created.
4. Import the dump file into the Google Cloud primary server.
D. 1. Take a full backup while the database is online.
2. Create a bucket in Cloud Storage.
3. Transfer the backup to the bucket you just created.
4. Restore the backup into the Google Cloud primary server.
5. Create a recovery.conf file in the $PG_DATA directory.
6. Stop the source database.
7. Transfer the write ahead logs to the bucket you created before.
8. Start the PostgreSQL service.
9. Wait until Google Cloud primary server syncs with the running primary server.

Answer: D

Explanation:
https://cloud.google.com/architecture/migrating-postgresql-to-gcp

NEW QUESTION # 166
You need to migrate existing databases from Microsoft SQL Server 2016 Standard Edition on a single Windows Server 2019 Datacenter Edition to a single Cloud SQL for SQL Server instance. During the discovery phase of your project, you notice that your on-premises server peaks at around 25,000 read IOPS. You need to ensure that your Cloud SQL instance is sized appropriately to maximize read performance. What should you do?

A. Create a SQL Server 2019 Standard on Standard machine type with 4 vCPUs, 15 GB of RAM, and 800 GB of solid-state drive (SSD).
B. Create a SQL Server 2019 Standard on High Memory machine type with at least 16 vCPUs, 104 GB of RAM, and 200 GB of SSD.
C. Create a SQL Server 2019 Enterprise on High Memory machine type with 16 vCPUs, 104 GB of RAM, and 500 GB of SSD.
D. Create a SQL Server 2019 Standard on High Memory machine type with 16 vCPUs, 104 GB of RAM, and 4 TB of SSD.

Answer: B

NEW QUESTION # 167
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