Professional Cloud Database Engineer - Google Cloud Certified Exam Questions

A- Migrate to a higher-tier instance with more vCPUs.

B- Implement connection pooling to manage client connections efficiently.

C- Use database sharding to split the database across multiple instances.

D- Increase the instance’s storage to improve throughput.

E- Use read replicas to distribute read queries.

A- Shard data required by the application into multiple instances.

B- Modify the database schema, and add additional indexes.

C- Increase the number of processing units.

D- Analyze slow queries and optimize them.

A- Scheduled automated backups with daily frequency and point-in-time recovery enabled.

B- Creating a read replica and promoting it to the primary instance when required.

C- Using continuous backups through binary logging and point-in-time recovery enabled.

D- Exporting the database to a Cloud Storage bucket on a weekly basis and importing it back when required.

A- db-n1-standard-32 with 6 TB of HDD storage

B- db-n1-highmem-64 with 6 TB of SSD storage

C- db-n1-highmem-16 with 4 TB of SSD storage

D- db-n1-highmem-32 with 4 TB of SSD storage

A- Use Cloud Audit Logs to verify the status.

B- Monitor the Cloud Logging dashboard.

C- Perform the gcloud spanner operations list command.

D- Check the cloudspanner.googleapis.com/operations.log instance log.

A- Create a Bigtable instance, use Bigtable's import functionality to convert the schema and transfer data, and set up a reverse replication from Bigtable to the on-premises Cassandra database as a fallback.

B- Develop custom scripts to convert the Cassandra schema to Bigtable and transfer the data using Bigtable APIs, then create a reverse replication process from Bigtable to the on-premises Cassandra database as a fallback plan.

C- Use Cloud Data Fusion to convert the Cassandra schema and transfer the data to Bigtable, then create a Cloud Data Fusion pipeline to transfer the data back to the on-premises database as a fallback plan.

D- Utilize the Schema Conversion Tool (SCT) to convert the Cassandra schema for Bigtable, perform data transfer using Dataflow, and set up a reverse replication from Bigtable to the on-premises Cassandra database as a fallback.

A- db-n1-highmem-64 with 2 TB of SSD storage

B- db-n1-standard-32 with 2 TB of HDD storage

C- db-n1-highmem-32 with 2 TB of HDD storage

D- db-n1-standard-16 with 2 TB of SSD storage

A- Use scheduled maintenance windows to simulate disaster recovery scenarios on the production environment.

B- Introduce random failures to the production environment to test the resilience and recovery strategies in place.

C- Deploy a separate environment identical to the production environment and perform a disaster recovery test using real-time database replication.

D- Perform a full-scale test by shutting down the production database and simulating a disaster recovery scenario.

A- Write a script to analyze the PostgreSQL logs stored in Cloud Storage for slow query patterns and run it weekly.

B- Set up a custom Cloud Monitoring metric to track the pg_stat_activity view and alert for an unusual number of active queries.

C- Export logs to BigQuery in real-time using Datastream and create a scheduled query to look for performance anomalies.

D- Configure a Cloud Monitoring alert to trigger when the CPU utilization reaches 90%, as it may indicate performance issues.

A- Enable the Cloud SQL Admin API.

B- Ensure that you are using an external (public) IP address interface.

C- Check whether your service account has the proper IAM roles assigned to connect to the Cloud SQL instance.

D- Verify that the app.yaml value cloud_sql_instances contains the correct instance connection name.