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

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q63-Q68):

NEW QUESTION # 63
You are building an application that allows users to customize their website and mobile experiences. The application will capture user information and preferences. User profiles have a dynamic schema, and users can add or delete information from their profile. You need to ensure that user changes automatically trigger updates to your downstream BigQuery data warehouse.
What should you do?

A. Use Firestore in Datastore mode, and store user profile data as a document. Update the user profile with preferences specific to that user and use the user identifier to query.
B. Use Firestore in Native mode, and store user profile data as a document. Update the user profile with preferences specific to that user and use the user identifier to query.
C. Use Cloud SQL, and create different tables for user profile data and user preferences from your recommendations model. Use SQL to join the user profile data and preferences
D. Store your data in Bigtable, and use the user identifier as the key. Use one column family to store user profile data, and use another column family to store user preferences.

Answer: B

NEW QUESTION # 64
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. Migrate to AlloyDB for PostgreSQL with a 16 vCPU primary instance and enable columnar engine for analytical workloads, using read pools for query isolation.
C. Upgrade to Cloud SAL for PostgreSQL Enterprise Edition and route transaction and analytical queries to the primary instance.
D. Upgrade the Cloud SQL for PostgreSQL instance to db-n1-highmem-32and implement connection pooling with PgBouncerto handle increased load.

Answer: B

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 # 65
You are migrating your data center to Google Cloud. You plan to migrate your applications to Compute Engine and your Oracle databases to Bare Metal Solution for Oracle. You must ensure that the applications in different projects can communicate securely and efficiently with the Oracle databases. What should you do?

A. Set up a Shared VPC, configure multiple service projects, and create firewall rules.
B. Set up Private Service Connect.
C. Set up Traffic Director.
D. Set up Serverless VPC Access.

Answer: A

NEW QUESTION # 66
You are designing for a write-heavy application. During testing, you discover that the write workloads are performant in a regional Cloud Spanner instance but slow down by an order of magnitude in a multi-regional instance. You want to make the write workloads faster in a multi-regional instance. What should you do?

A. Place the bulk of the read and write workloads closer to the default leader region.
B. Keep the total CPU utilization under 45% in each region.
C. Use staleness of at least 15 seconds.
D. Add more read-write replicas.

Answer: A

Explanation:
https://cloud.google.com/spanner/docs/instance-configurations#multi-region-best-practices Best practices For optimal performance, follow these best practices: Design a schema that prevents hotspots and other performance issues. For optimal write latency, place compute resources for write-heavy workloads within or close to the default leader region. For optimal read performance outside of the default leader region, use staleness of at least 15 seconds. To avoid single-region dependency for your workloads, place critical compute resources in at least two regions. A good option is to place them next to the two different read-write regions so that any single region outage will not impact all of your application. Provision enough compute capacity to keep high priority total CPU utilization under 45% in each region.

NEW QUESTION # 67
You host an application in Google Cloud. The application is located in a single region and uses Cloud SQL for transactional dat a. Most of your users are located in the same time zone and expect the application to be available 7 days a week, from 6 AM to 10 PM. You want to ensure regular maintenance updates to your Cloud SQL instance without creating downtime for your users. What should you do?

A. Create your database with one primary node and one read replica in the region.
B. Enable maintenance notifications for users, and reschedule maintenance activities to a specific time after notifications have been sent.
C. Configure your Cloud SQL instance with high availability enabled.
D. Configure a maintenance window during a period when no users will be on the system. Control the order of update by setting non-production instances to earlier and production instances to later.

Answer: D

Explanation:
Configure a maintenance window during a period when no users will be on the system. Control the order of update by setting non-production instances to earlier and production instances to later.

NEW QUESTION # 68
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