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

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q186-Q191):

NEW QUESTION # 186
You are managing a small Cloud SQL instance for developers to do testing. The instance is not critical and has a recovery point objective (RPO) of several days. You want to minimize ongoing costs for this instance. What should you do?

A. Take no backups, and turn off transaction log retention.
B. Take one manual backup per day, and turn off transaction log retention.
C. Turn on automated backup, and turn off transaction log retention.
D. Turn on automated backup, and turn on transaction log retention.

Answer: C

Explanation:
https://cloud.google.com/sql/docs/mysql/backup-recovery/backups

NEW QUESTION # 187
You run a toy sales ecommerce application on Spanner. The application contains details about the various product listings such as name, category, description, and review(s). Your leadership wants to enable customers to ask free-form questions about the product catalog. You want to implement this functionality in the easiest, quickest, and least expensive way possible.
What should you do?

A. Register an existing Generative AI Vertex model in Spanner. Use the ML.PREDICTfunction to supply the model with a user query along with the product information in a SQL query. Return the response back to the application.
B. Create, train and deploy a custom ML model(s). Fetch toy details from Spanner and invoke ML predictions from the application layer to return the response.
C. Create a Spanner full-text search index. Find the product information or review against the user's question in a SQL query. Return the response back to the application.
D. Generate vector embeddings for product information in Spanner. Find the vector with the smallest distance between the users' query and existing product information or review by using the EUCLIDEAN_DISTANCE()function in Spanner. Return the closest product information or review.

Answer: A

Explanation:
Registering an existing Vertex AI generative model in Spanner and calling it with ML.PREDICT lets you implement free-form Q&A directly from SQL without building custom ML pipelines, generating/maintaining embeddings, or deploying your own model - making it the quickest and lowest-effort approach while keeping the solution cost-effective by reusing a managed model.

NEW QUESTION # 188
Your company is shutting down their data center and migrating several MySQL and PostgreSQL databases to Google Cloud. Your database operations team is severely constrained by ongoing production releases and the lack of capacity for additional on-premises backups. You want to ensure that the scheduled migrations happen with minimal downtime and that the Google Cloud databases stay in sync with the on-premises data changes until the applications can cut over. What should you do? (Choose two.)

A. Use replication from an external server to migrate the databases to Cloud SQL.
B. Use Database Migration Service to migrate the databases to Cloud SQL.
C. Use an external read replica to migrate the databases to Cloud SQL.
D. Use a read replica to migrate the databases to Cloud SQL.
E. Use a cross-region read replica to migrate the databases to Cloud SQL.

Answer: A,D

NEW QUESTION # 189
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 Cloud Trace for application requests that are failing.
B. Watch the Cloud SQL recommenders for overprovisioned instances.
C. Watch the Cloud SQL instance monitor for CPU utilization metrics.
D. Watch Query Insights for long running queries.

Answer: D

NEW QUESTION # 190
You are choosing a database backend for a new application. The application will ingest data points from IoT sensors. You need to ensure that the application can scale up to millions of requests per second with sub-10ms latency and store up to 100 TB of history. What should you do?

A. Use Firestore, and rely on automatic serverless scaling.
B. Use Bigtable, and add nodes as necessary to achieve the required throughput.
C. Use Memorystore for Memcached, and add nodes as necessary to achieve the required throughput.
D. Use Cloud SQL with read replicas for throughput.

Answer: B

Explanation:
https://cloud.google.com/memorystore/docs/redis/redis-overview

NEW QUESTION # 191
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