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

Section	Objectives
Topic 1: Migrate data solutions to Google Cloud	- Database migration strategies 1. Online vs offline migration tools (e.g., Database Migration Service) 2. Lift-and-shift vs re-platforming
Topic 2: Ensure reliability, performance, and optimization	- Performance optimization 1. Indexing, query optimization, and caching strategies 2. Workload tuning across database services - Security and compliance 1. Encryption at rest and in transit 2. IAM roles and access control
Topic 3: Manage a database solution spanning multiple systems	- Operational database management 1. Backup and restore strategies 2. Capacity planning and scaling 3. Monitoring and performance tuning
Topic 4: Design scalable and highly available database solutions	- Design for high availability and disaster recovery 1. Regional vs multi-regional architectures 2. Replication strategies and failover design - Select appropriate database services (relational, NoSQL, analytical) 1. Firestore and document database patterns 2. Cloud SQL vs AlloyDB vs Spanner selection criteria 3. Bigtable use cases and schema design

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q126-Q131):

NEW QUESTION # 126
An analytics team needs to read data out of Cloud SQL for SQL Server and update a table in Cloud Spanner. You need to create a service account and grant least privilege access using predefined roles. What roles should you assign to the service account?

A. roles/cloudsql.editor and roles/spanner.admin
B. roles/cloudsql.viewer and roles/spanner.databaseUser
C. roles/cloudsql.instanceUser and roles/spanner.databaseUser
D. roles/cloudsql.client and roles/spanner.databaseReader

Answer: B

NEW QUESTION # 127
You are designing a database strategy for a new web application. You plan to start with a small pilot in one country and eventually expand to millions of users in a global audience. You need to ensure that the application can run 24/7 with minimal downtime for maintenance. What should you do?

A. Use Cloud Spanner in a regional configuration.
B. Use Cloud SQL with cross-region replicas.
C. Use Cloud Spanner in a multi-region configuration.
D. Use highly available Cloud SQL with multiple zones.

Answer: A

Explanation:
https://docs.google.com/forms/d/e/1FAIpQLSfZ77ZnuUL0NpU-bOtO5QUkC0cnRCe5YKMiubLXwfV3abBqkg/viewform

NEW QUESTION # 128
Your ecommerce website captures user clickstream data to analyze customer traffic patterns in real time and support personalization features on your website. You plan to analyze this data using big data tools. You need a low-latency solution that can store 8 TB of data and can scale to millions of read and write requests per second. What should you do?

A. Stream your data into BigQuery and use Dataproc and the BigQuery Storage API to analyze large volumes of data.
B. Write your data into Bigtable and use Dataproc and the Apache Hbase libraries for analysis.
C. Use Memorystore to handle your low-latency requirements and for real-time analytics.
D. Deploy a Cloud SQL environment with read replicas for improved performance. Use Datastream to export data to Cloud Storage and analyze with Dataproc and the Cloud Storage connector.

Answer: B

Explanation:
Start with the lowest tier and smallest size and then grow your instance as needed. Memorystore provides automated scaling using APIs, and optimized node placement across zones for redundancy. Memorystore for Memcached can support clusters as large as 5 TB, enabling millions of QPS at very low latency

NEW QUESTION # 129
Your rapidly growing ecommerce company is migrating their analytics workloads to AlloyDB for PostgreSQL. You anticipate a significant increase in reporting queries as the business scales.
You need a read pool strategy to scale your analytics operations in anticipation of future growth while minimizing costs. What should you do-

A. Change the instance sizes of the read nodes in the read pool.
B. Begin with minimal read pools and iteratively expand or shrink them based on real-time load monitoring to optimize resource allocation.
C. Direct all complex, long-running analytics queries to the primary instance, and only use read pools for short, frequent reports.
D. Assign all reporting queries to a single, large read pool to maximize the combined compute resources available for analytics.

Answer: B

Explanation:
Start with a small read-pool footprint and then scale it up or down as your query volume and performance needs evolve.
* Cost-efficient: You only pay for the read nodes you actually need at any given time, avoiding over-provisioning.
* Elastic scaling: Monitor your query latency and throughput, then add or remove read nodes to match the workload profile (e.g. heavy sales events vs. normal traffic).
* Minimal ops overhead: AlloyDB makes it simple to resize your read pool via the console or gcloud, so you can automate based on Cloud Monitoring alerts.

NEW QUESTION # 130
Your company is migrating from an on-premises database to a single-region Spanner instance.
The current database supports 40,000 reads each second, and 7,000 writes each second, at 1- KB row sizes at peak. You need to determine the most cost-effective size for the Spanner instance to handle the equivalent current workload. What should you do-

A. Select a 4-node Spanner instance.
B. Recommend a multi-region Spanner instance.
C. Select a 6-node Spanner instance.
D. Select a 1-node Spanner instance.

Answer: A

Explanation:
A single Spanner node (1-000-PU) in a regional SSD configuration can handle up to ~22-500 reads/sec and ~3-500 writes/sec for 1-KB rows. To support 40-000 reads/sec and 7-000 writes/sec, you need at least two nodes (2×22-500-=-45-000 reads; 2×3-500-=-7-000 writes). Of the provided options, a 4-node instance is the smallest choice that exceeds both the read and write requirements, making it the most cost-effective available SKU.

NEW QUESTION # 131
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