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

Section	Weight	Objectives
Topic 1: Design innovative, scalable, and highly available cloud database solutions	32%	- Design for security and compliance 1. Compliance requirements 2. Access control and IAM 3. Data encryption - 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. Data import/export planning 2. RTO and RPO design 3. Backup strategies - Design for high availability and reliability 1. Replication strategies 2. Disaster recovery planning 3. High availability configurations
Topic 2: Migrate data solutions	14%	- Design migration strategies 1. Fall-back planning 2. Downtime requirements analysis - Implement migration and replication 1. Schema conversion 2. Migration tool selection 3. Data replication methods - Validate and cut over migration 1. Cutover procedures 2. Data integrity verification
Topic 3: Deploy scalable and highly available databases in Google Cloud	20%	- Automate deployment and scaling 1. Infrastructure as Code 2. Auto-scaling setup - Implement high availability solutions 1. Multi-region replication 2. Read replicas deployment 3. Provision HA configurations - Configure monitoring and alerting 1. Health checks and alerts 2. Performance dashboards
Topic 4: Manage a solution that spans multiple database technologies	25%	- Determine connectivity and access management 1. IAM policies and permissions 2. User authentication and authorization - Configure monitoring and troubleshooting 1. Troubleshoot common issues 2. Query optimization 3. Performance monitoring - Optimize cost and performance 1. Cost optimization 2. Automate operational tasks 3. Scaling strategies - Manage database operations and maintenance 1. Updates and upgrades 2. Index management 3. Data lifecycle management

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q76-Q81):

NEW QUESTION # 76
Your organization is running a critical production database on a virtual machine (VM) on Compute Engine. The VM has an ext4-formatted persistent disk for data files. The database will soon run out of storage space. You need to implement a solution that avoids downtime. What should you do?

A. In the Google Cloud Console, increase the size of the persistent disk, and use the resize2fs command to extend the disk.
B. In the Google Cloud Console, create a new persistent disk attached to the VM, and configure the database service to move the files to the new disk.
C. In the Google Cloud Console, increase the size of the persistent disk, and use the fdisk command to verify that the new space is ready to use
D. In the Google Cloud Console, create a snapshot of the persistent disk, restore the snapshot to a new larger disk, unmount the old disk, mount the new disk, and restart the database service.

Answer: A

Explanation:
https://cloud.google.com/compute/docs/disks/resize-persistent-disk#resize_partitions

NEW QUESTION # 77
Your company is using a multi-region Spanner instance. The instance stores data from an application which does a lot of writes without reading the data. You are noticing a lot of latency regression. You want to reduce latency and improve performance. What should you do-

A. Increase the number of Spanner nodes.
B. Enable leader-aware routing in the client library.
C. Disable leader-aware routing in the client library.
D. Add additional indexes to the table.

Answer: B

Explanation:
Enabling leader-aware routing ensures that your write traffic is automatically sent to the database's designated leader region rather than being round-tripped across regions. For a write- heavy workload in a multi-region configuration, this change cuts out cross-region hops and lowers latency far more effectively than adding indexes or nodes.

NEW QUESTION # 78
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: B,E

NEW QUESTION # 79
You use Python scripts to generate weekly SQL reports to assess the state of your databases and determine whether you need to reorganize tables or run statistics. You want to automate this report but need to minimize operational costs and overhead. What should you do?

A. Create a Cloud Function, and call the Cloud Function from a Cloud Tasks queue.
B. Create a Cloud Function, and call the Cloud Function using Cloud Scheduler.
C. Create a Cloud Composer instance, and create a directed acyclic graph (DAG).
D. Create a VM in Compute Engine, and run a cron job.

Answer: B

Explanation:
Cloud Scheduler triggers actions at regular fixed intervals, whereas Cloud Tasks triggers actions based on how the individual task object is configured.
https://cloud.google.com/tasks/docs/comp-tasks-sched

NEW QUESTION # 80
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. 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.
B. 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.
C. 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.
D. 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.

Answer: D

Explanation:
The best answer is deploy an HA configuration and have a read replica you could promote to the primary in a different region

NEW QUESTION # 81
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