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

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

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q135-Q140):

NEW QUESTION # 135
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 Error Reporting to count, analyze, and aggregate the data.
B. Use Cloud Debugger to inspect the state of an application.
C. Use Logs Explorer to analyze log data.
D. Use Cloud Monitoring to monitor CPU, memory, and storage utilization metrics.

Answer: D

NEW QUESTION # 136
Your application follows a microservices architecture and uses a single large Cloud SQL instance, which is starting to have performance issues as your application grows. in the Cloud Monitoring dashboard, the CPU utilization looks normal You want to follow Google-recommended practices to resolve and prevent these performance issues while avoiding any major refactoring. What should you do?

A. Use many smaller Cloud SQL instances.
B. Increase the storage size for the instance.
C. Use Cloud Spanner instead of Cloud SQL.
D. Increase the number of CPUs for your instance.

Answer: A

Explanation:
https://cloud.google.com/sql/docs/mysql/best-practices#data-arch

NEW QUESTION # 137
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 the Cloud SQL instance monitor for CPU utilization metrics.
C. Watch Query Insights for long running queries.
D. Watch Cloud Trace for application requests that are failing.

Answer: C

Explanation:
https://cloud.google.com/blog/topics/developers-practitioners/introducing-sqlcommenter-open-source-orm-auto-instrumentation-library

NEW QUESTION # 138
Your organization deploys a high-volume, low-latency sensor data ingestion system. Resilience is crucial, and the workload is expected to grow significantly over time. You need to design a database tier on Google Cloud to ensure faster performance and high availability, while following Google-recommended practices. What should you do-

A. Deploy a single-region Bigtable instance and increase the nodes to maximize data durability.
B. Deploy a single-zone Bigtable cluster and optimize the application code for maximum write throughput.
C. Provision a multi-zone Bigtable cluster, configure replication, perform an application stress-test, and set up performance monitoring.
D. Deploy multiple Bigtable clusters, shard data manually across them, and set up the application logic for fault tolerance.

Answer: C

Explanation:
Provisioning a multi-zone Cloud Bigtable cluster gives you zonal failover for high availability and lets Bigtable's built-in replication optimize throughput and latency as ingest load grows.
Performing an application stress test validates cluster sizing under peak writes, and ongoing performance monitoring ensures you can scale nodes proactively - all matching Google's best practices.

NEW QUESTION # 139
You are setting up a Bare Metal Solution environment. You need to update the operating system to the latest version. You need to connect the Bare Metal Solution environment to the internet so you can receive software updates. What should you do?

A. Set up a Cloud NAT gateway on the Compute Engine VM.
B. Set up Cloud NAT service.
C. Setup a static external IP address in your VPC network.
D. Set up bring your own IP (BYOIP) in your VPC.

Answer: A

Explanation:
https://cloud.google.com/bare-metal/docs/bms-setup#bms-access-internet-vm-nat

NEW QUESTION # 140
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