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Google Professional-Cloud-Database-Engineer Exam Overview:

Certification Vendor:	Google Cloud
Exam Name:	Professional Cloud Database Engineer
Exam Number:	Professional-Cloud-Database-Engineer
Exam Duration:	120 minutes
Real Exam Qty:	50-60
Exam Price:	$200 USD (plus tax where applicable)
Related Certifications:	Google Cloud Certified - Professional Cloud Data Engineer Google Cloud Certified - Associate Cloud Engineer
Exam Format:	Multiple choice, Scenario-based questions, Multiple select
Passing Score:	Not publicly disclosed (pass/fail scaled scoring)
Available Languages:	English
Certificate Validity Period:	2 years
Recommended Training:	Google Cloud Skills Boost - Database Engineer Learning Path Google Cloud Database documentation
Exam Registration:	Cloud Database Engineer Certification Page Official Google Cloud Certification Portal
Sample Questions:	Google Professional-Cloud-Database-Engineer Sample Questions
Exam Way:	Online proctored or onsite test center exam
Pre Condition:	No formal prerequisites required. Recommended: ~5 years database/IT experience including ~2 years Google Cloud database experience.
Official Syllabus URL:	https://cloud.google.com/learn/certification/cloud-database-engineer

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q82-Q87):

NEW QUESTION # 82
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. Import the dump file into the Google Cloud primary server.
B. 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.
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. Restore the backup into the Google Cloud primary server.
D. 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.

Answer: B

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

NEW QUESTION # 83
You are designing a database strategy for a new web application. You plan to start with a small pilot in one country and eventually expand to millions of users in a global audience. You need to ensure that the application can run 24/7 with minimal downtime for maintenance. What should you do?

A. Use highly available Cloud SQL with multiple zones.
B. Use Cloud Spanner in a multi-region configuration.
C. Use Cloud Spanner in a regional configuration.
D. Use Cloud SQL with cross-region replicas.

Answer: C

NEW QUESTION # 84
Your application uses Cloud SQL for MySQL. Your users run reports on data that relies on near-real time; however, the additional analytics caused excessive load on the primary database. You created a read replica for the analytics workloads, but now your users are complaining about the lag in data changes and that their reports are still slow.You need to improve the report performance and shorten the lag in data replication without making changes to the current reports. Which two approaches should you implement? (Choose two.)

A. Disable replication on the primary instance, and set the flag for parallel replication on the primary instance. Re-enable replication and optimize performance by setting flags on the read replica.
B. Move your analytics workloads to BigQuery, and set up a streaming pipeline to move data and update BigQuery.
C. Disable replication on the read replica, and set the flag for parallel replication on the read replica. Re- enable replication and optimize performance by setting flags on the primary instance.
D. Create secondary indexes on the replica.
E. Create additional read replicas, and partition your analytics users to use different read replicas.

Answer: C,E

Explanation:
Replication lag and slow report performance. E is eliminated because using BigQuery would mean changes to the current reports. Report slowness could be the result of poor indexing or just too much read load (or both!).
Since excessive load is mentioned in the question, creating additional read replicas and spreading the analytics workload around makes B correct and eliminates A as a way to speed up reporting. That leaves the replication problem. Cloud SQL enables single threaded replication by default, so it stands to reason enabling parallel replication would help the lag. To do that you disable replication on the replica (not the primary), set flags on the replica and optionally set flags on the primary instance to optimize performance for parallel replication.
That makes C correct and D incorrect.https://cloud.google.com/sql/docs/mysql/replication/manage- replicas#configuring-parallel-replication

NEW QUESTION # 85
Your organization works with sensitive data that requires you to manage your own encryption keys. You are working on a project that stores that data in a Cloud SQL database. You need to ensure that stored data is encrypted with your keys. What should you do?

A. Connect to Cloud SQL using a connection that has SSL encryption.
B. Use customer-managed encryption keys with Cloud SQL.
C. Use Cloud SQL Auth proxy.
D. Export data periodically to a Cloud Storage bucket protected by Customer-Supplied Encryption Keys.

Answer: A

NEW QUESTION # 86
Your team recently released a new version of a highly consumed application to accommodate additional user traffic. Shortly after the release, you received an alert from your production monitoring team that there is consistently high replication lag between your primary instance and the read replicas of your Cloud SQL for MySQL instances. You need to resolve the replication lag. What should you do?

A. Edit the primary instance to add additional memory.
B. Identify and optimize slow running queries, or set parallel replication flags.
C. Edit the primary instance to upgrade to a larger disk, and increase vCPU count.
D. Stop all running queries, and re-create the replicas.

Answer: B

Explanation:
https://cloud.google.com/sql/docs/mysql/replication/replication-lag#optimize_queries_and_schema

NEW QUESTION # 87
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