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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 high availability and reliability 1. Disaster recovery planning 2. High availability configurations 3. Replication strategies - Design for backup and recovery 1. Backup strategies 2. RTO and RPO design 3. Data import/export planning - Design for security and compliance 1. Compliance requirements 2. Access control and IAM 3. Data encryption - Analyze variables for capacity and usage planning 1. Size compute and storage resources 2. Evaluate performance and cost tradeoffs 3. Solution sizing based on workload and requirements
Topic 2: Manage a solution that spans multiple database technologies	25%	- Determine connectivity and access management 1. User authentication and authorization 2. IAM policies and permissions - Configure monitoring and troubleshooting 1. Query optimization 2. Performance monitoring 3. Troubleshoot common issues - Optimize cost and performance 1. Scaling strategies 2. Automate operational tasks 3. Cost optimization - Manage database operations and maintenance 1. Data lifecycle management 2. Updates and upgrades 3. Index management
Topic 3: Migrate data solutions	14%	- Design migration strategies 1. Downtime requirements analysis 2. Fall-back planning - Validate and cut over migration 1. Data integrity verification 2. Cutover procedures - Implement migration and replication 1. Schema conversion 2. Migration tool selection 3. Data replication methods
Topic 4: Deploy scalable and highly available databases in Google Cloud	20%	- Automate deployment and scaling 1. Auto-scaling setup 2. Infrastructure as Code - 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

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q99-Q104):

NEW QUESTION # 99
Your organization is running a low-latency reporting application on Microsoft SQL Server. In addition to the database engine, you are using SQL Server Analysis Services (SSAS), SQL Server Reporting Services (SSRS), and SQL Server Integration Services (SSIS) in your on-premises environment. You want to migrate your Microsoft SQL Server database instances to Google Cloud. You need to ensure minimal disruption to the existing architecture during migration. What should you do?

A. Migrate to Cloud SQL for SQL Server.
B. Migrate to Compute Engine.
C. Migrate to Google Kubernetes Engine (GKE).
D. Migrate to Cloud SQL for PostgreSQL.

Answer: D

NEW QUESTION # 100
Your Cloud SQL for PostgreSQL database supporting a financial application has been experiencing "deadlock detected" errors during end-of-month processing. You notice that CPU utilization spikes to 90% during these periods, and several long-running queries are consuming significant resources. You need to identify the specific queries causing the deadlocks and implement monitoring to solve similar issues before they cause application failures.
What should you do?

A. Implement connection pooling at the application layer to reduce the number of direct database connections and optimize shared_buffersand work_memparameters in Cloud SQL for PostgreSQL to improve query execution efficiency.
B. Increase the deadlock_timeoutparameter on the Cloud SQL for PostgreSQL instance. Export logs to Cloud Logging, and create log-based metrics to track deadlock occurrences.
C. Use Cloud SQL System Insights to identify long-running queries and number of deadlocks that occurred in the database. Enable a log_lock_waitsflag to determine if lock waits are causing poor performance. Set up Cloud Monitoring alerts for higher CPU utilization and connection count.
D. Optimize SQL queries by adding appropriate indexes to frequently accessed columns and rewriting complex joins to use LEFT JOINinstead of INNER JOIN, where applicable.

Answer: C

Explanation:
Cloud SQL System Insights helps you pinpoint the long-running and resource-heavy queries correlated with the deadlock periods and shows deadlock-related signals. Enabling log_lock_waits provides visibility into lock waits that typically precede or accompany deadlocks.
Cloud Monitoring alerts on CPU and connections gives proactive detection so you can investigate and remediate before the workload escalates into failures.

NEW QUESTION # 101
You want to migrate an existing on-premises application to Google Cloud. Your application supports semi- structured data ingested from 100,000 sensors, and each sensor sends 10 readings per second from manufacturing plants. You need to make this data available for real-time monitoring and analysis. What should you do?

A. Use BigQuery, and load data in batches.
B. Deploy the database using Bigtable.
C. Deploy the database using Cloud Spanner.
D. Deploy the database using Cloud SQL.

Answer: A

Explanation:
Bigtable is a scalable, fully managed, and high-performance NoSQL database service that can handle semi- structured data and support real-time monitoring and analysis. Cloud SQL is a relational database service that does not support semi-structured data. BigQuery is a data warehouse service that is optimized for batch processing and analytics, not real-time monitoring. Cloud Spanner is a relational database service that supports semi-structured data with JSON data type, but it is more expensive and complex than Bigtable for this use case.

NEW QUESTION # 102
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. Change the storage tier of the automated backups from solid-state drive (SSD) to hard disk drive (HDD).
C. Set the automated backups to occur every other day to lower the frequency of backups.
D. Reduce the number of automated backups that are retained to two (2).

Answer: C

NEW QUESTION # 103
Your company is shutting down their on-premises data center and migrating their Oracle databases using Oracle Real Application Clusters (RAC) to Google Cloud. You want minimal to no changes to the applications during the database migration. What should you do?

A. Migrate the Oracle databases to Bare Metal Solution for Oracle.
B. Migrate the Oracle databases to Cloud Spanner.
C. Migrate the Oracle databases to Compute Engine.
D. Migrate the Oracle databases to Cloud SQL.

Answer: A

Explanation:
This answer is correct because Bare Metal Solution for Oracle is a service that provides dedicated physical servers and networking infrastructure for running Oracle databases on Google Cloud1. Bare Metal Solution for Oracle supports Oracle RAC, which is a cluster database that provides high availability, scalability, and performance for Oracle workloads2. By using Bare Metal Solution for Oracle, you can migrate your Oracle databases with minimal to no changes to the applications, and you can leverage the native Google Cloud services and interconnectivity1.

NEW QUESTION # 104
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