試験内容はベンダーの方針変更とともに更新されるため、教材の鮮度が学習効果を左右します。JPNTestのProfessional-Cloud-Database-Engineer問題集は購入後365日間無料で更新され、2026年時点のGoogle Cloud Certified - Professional Cloud Database Engineerの出題内容にも対応しています。

Google Professional-Cloud-Database-Engineer 試験概要:

Google Professional-Cloud-Database-Engineer 試験シラバストピック:

Google Cloud Certified - Professional Cloud Database EngineerのQ&A

Google Cloud Certified - Professional Cloud Database Engineer 認定 Professional-Cloud-Database-Engineer 試験問題：

問題 #1

Your e-learning platform runs on a Cloud SQL for PostgreSQL instance (16 VCPUs, 60 GB memory and 1TB SSD) serving users in North America. Your analytics team runs complex reporting queries that often consume 80% of CPU resources, causing slow response times for student transactions during peak hours. Current workload includes 8,000 transactions per second with 60% reads and 40% writes. The reporting queries involve JOIN operations across multiple large tables with millions of rows requiring highly efficient analytical processing. The platform also experiences sudden spikes in analytical reporting demand, requiring an elastic scaling of read capacity. You need to improve the query performance for your analytics team to run their reports efficiently without impacting transactional users. You also need to plan for future traffic growth.
What should you do-

A. Migrate to AlloyDB for PostgreSQL and upgrade the machine type of the primary instance to 32 vCPU. Create materialized views for common analytical queries.
B. Upgrade the Cloud SQL for PostgreSQL instance to db-n1-highmem-32and implement connection pooling with PgBouncerto handle increased load.
C. Upgrade to Cloud SAL for PostgreSQL Enterprise Edition and route transaction and analytical queries to the primary instance.
D. Migrate to AlloyDB for PostgreSQL with a 16 vCPU primary instance and enable columnar engine for analytical workloads, using read pools for query isolation.

問題 #2

Your DevOps team is using Terraform to deploy applications and Cloud SQL databases. After every new application change is rolled out, the environment is torn down and recreated, and the persistent database layer is lost. You need to prevent the database from being dropped. What should you do?

A. Use point-in-time-recovery (PITR) to recover the database.
B. Rerun terraform apply.
C. Set Terraform deletion_protection to true.
D. Create a read replica.

問題 #3

Your organization has a ticketing system that needs an online marketing analytics and reporting application. You need to select a relational database that can manage hundreds of terabytes of data to support this new application. Which database should you use?

A. Cloud SQL
B. Bigtable
C. Cloud Spanner
D. BigQuery

問題 #4

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

問題 #5

You are deploying a new Cloud SQL instance on Google Cloud using the Cloud SQL Auth proxy.
You have identified snippets of application code that need to access the new Cloud SQL instance. The snippets reside and execute on an application server running on a Compute Engine machine. You want to follow Google-recommended practices to set up Identity and Access Management (IAM) as quickly and securely as possible. What should you do?

A. For the application server, set up a common shared user account.
B. For each application code, set up a common shared user account.
C. For each application code, set up a dedicated user account.
D. For the application server, set up a service account.

解説：