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Google Professional-Cloud-Database-Engineer Exam Syllabus Topics:

Section	Weight	Objectives
Design innovative, scalable, and highly available cloud database solutions	32%	- Analyze variables for capacity and usage planning 1. Evaluate performance and cost tradeoffs 2. Solution sizing based on workload and requirements 3. Size compute and storage resources - Design for backup and recovery 1. Backup strategies 2. RTO and RPO design 3. Data import/export planning - Design for high availability and reliability 1. Replication strategies 2. Disaster recovery planning 3. High availability configurations - Design for security and compliance 1. Compliance requirements 2. Access control and IAM 3. Data encryption
Migrate data solutions	14%	- Implement migration and replication 1. Data replication methods 2. Migration tool selection 3. Schema conversion - Design migration strategies 1. Fall-back planning 2. Downtime requirements analysis - Validate and cut over migration 1. Cutover procedures 2. Data integrity verification
Deploy scalable and highly available databases in Google Cloud	20%	- Configure monitoring and alerting 1. Performance dashboards 2. Health checks and alerts - Implement high availability solutions 1. Read replicas deployment 2. Multi-region replication 3. Provision HA configurations - Automate deployment and scaling 1. Auto-scaling setup 2. Infrastructure as Code
Manage a solution that spans multiple database technologies	25%	- Optimize cost and performance 1. Scaling strategies 2. Automate operational tasks 3. Cost optimization - Manage database operations and maintenance 1. Updates and upgrades 2. Data lifecycle management 3. Index management - Determine connectivity and access management 1. User authentication and authorization 2. IAM policies and permissions - Configure monitoring and troubleshooting 1. Performance monitoring 2. Troubleshoot common issues 3. Query optimization

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q219-Q224):

NEW QUESTION # 219
Your e-learning platform runs on a Cloud SQL for PostgreSQL instance (16 VCPUs, 60 GB memory and 1TB SSD) serving users in North America. Your analytics team runs complex reporting queries that often consume 80% of CPU resources, causing slow response times for student transactions during peak hours. Current workload includes 8,000 transactions per second with 60% reads and 40% writes. The reporting queries involve JOIN operations across multiple large tables with millions of rows requiring highly efficient analytical processing. The platform also experiences sudden spikes in analytical reporting demand, requiring an elastic scaling of read capacity. You need to improve the query performance for your analytics team to run their reports efficiently without impacting transactional users. You also need to plan for future traffic growth.
What should you do-

A. Migrate to AlloyDB for PostgreSQL and upgrade the machine type of the primary instance to 32 vCPU. Create materialized views for common analytical queries.
B. Upgrade the Cloud SQL for PostgreSQL instance to db-n1-highmem-32and implement connection pooling with PgBouncerto handle increased load.
C. Migrate to AlloyDB for PostgreSQL with a 16 vCPU primary instance and enable columnar engine for analytical workloads, using read pools for query isolation.
D. Upgrade to Cloud SAL for PostgreSQL Enterprise Edition and route transaction and analytical queries to the primary instance.

Answer: C

Explanation:
Migrating to AlloyDB for PostgreSQL with the columnar engine is the best option for this mixed workload. The columnar engine accelerates analytical queries such as multi-table JOINs on large datasets, while the primary instance continues handling transactional traffic. Using read pools isolates analytical reporting from transactional operations and provides elastic scaling to handle sudden spikes in reporting demand. This ensures efficient reporting without degrading transactional performance and supports future growth.

NEW QUESTION # 220
Your retail organization is preparing for the holiday season. Use of catalog services is increasing, and your DevOps team is supporting the Cloud SQL databases that power a microservices-based application. The DevOps team has added instrumentation through Sqlcommenter. You need to identify the root cause of why certain microservice calls are failing. What should you do?

A. Watch the Cloud SQL recommenders for overprovisioned instances.
B. Watch Cloud Trace for application requests that are failing.
C. Watch the Cloud SQL instance monitor for CPU utilization metrics.
D. Watch Query Insights for long running queries.

Answer: D

NEW QUESTION # 221
You have a large Cloud SQL for PostgreSQL instance. The database instance is not mission-critical, and you want to minimize operational costs. What should you do to lower the cost of backups in this environment?

A. Select a different region to store your backups.
B. Set the automated backups to occur every other day to lower the frequency of backups.
C. Reduce the number of automated backups that are retained to two (2).
D. Change the storage tier of the automated backups from solid-state drive (SSD) to hard disk drive (HDD).

Answer: C

Explanation:
By default, for each instance, Cloud SQL retains seven automated backups, in addition to on-demand backups. You can configure how many automated backups to retain (from 1 to 365). We charge a lower rate for backup storage than for other types of instances. https://cloud.google.com/sql/docs/mysql/backup-recovery
/backups

NEW QUESTION # 222
Your organization is running a MySQL workload in Cloud SQL. Suddenly you see a degradation in database performance. You need to identify the root cause of the performance degradation.
What should you do?

A. Use Cloud Monitoring to monitor CPU, memory, and storage utilization metrics.
B. Use Cloud Debugger to inspect the state of an application.
C. Use Error Reporting to count, analyze, and aggregate the data.
D. Use Logs Explorer to analyze log data.

Answer: A

NEW QUESTION # 223
You are migrating an on-premises application to Google Cloud. The application requires a high availability (HA) PostgreSQL database to support business-critical functions. Your company's disaster recovery strategy requires a recovery time objective (RTO) and recovery point objective (RPO) within 30 minutes of failure. You plan to use a Google Cloud managed service. What should you do to maximize uptime for your application?

A. Deploy Cloud SQL for PostgreSQL in a regional configuration with HA enabled. Create a cross-region read replica, and promote the read replica as the primary node for disaster recovery.
B. Deploy Cloud SQL for PostgreSQL in a regional configuration with HA enabled. Take periodic backups, and use this backup to restore to a new Cloud SQL for PostgreSQL instance in another region during a disaster recovery event.
C. Migrate the PostgreSQL database to multi-regional Cloud Spanner so that a single region outage will not affect your application. Update the schema to support Cloud Spanner data types, and refactor the application.
D. Deploy Cloud SQL for PostgreSQL in a regional configuration. Create a read replica in a different zone in the same region and a read replica in another region for disaster recovery.

Answer: A

NEW QUESTION # 224
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