Professional-Cloud-Database-Engineer出題範囲 & Professional-Cloud-Database-Engineer日本語版問題解説

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

SectionObjectives
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
        Ensure reliability, performance, and optimization- Security and compliance
        • 1. Encryption at rest and in transit
          • 2. IAM roles and access control
            - Performance optimization
            • 1. Indexing, query optimization, and caching strategies
              • 2. Workload tuning across database services
                Migrate data solutions to Google Cloud- Database migration strategies
                • 1. Lift-and-shift vs re-platforming
                  • 2. Online vs offline migration tools (e.g., Database Migration Service)
                    Design scalable and highly available database solutions- 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
                          - Design for high availability and disaster recovery
                          • 1. Replication strategies and failover design
                            • 2. Regional vs multi-regional architectures

                              >> Professional-Cloud-Database-Engineer出題範囲 <<

                              Professional-Cloud-Database-Engineer日本語版問題解説 & Professional-Cloud-Database-Engineer技術試験

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                              Google Cloud Certified - Professional Cloud Database Engineer 認定 Professional-Cloud-Database-Engineer 試験問題 (Q134-Q139):

                              質問 # 134
                              Your team uses thousands of connected IoT devices to collect device maintenance data for your oil and gas customers in real time. You want to design inspection routines, device repair, and replacement schedules based on insights gathered from the data produced by these devices. You need a managed solution that is highly scalable, supports a multi-cloud strategy, and offers low latency for these IoT devices. What should you do?

                              正解：A

                              解説：
                              This scenario has BigTable written all over it - large amounts of data from many devices to be analysed in realtime. I would even argue it could qualify as a multicloud solution, given the links to HBASE. BUT it does not support SQL queries and is not therefore compatible (on its own) with Looker. Firestore + Looker has the same problem. Spanner + Data Studio is at least a compatible pairing, but I agree with others that it doesn't fit this use-case - not least because it's Google-native. By contrast, MongoDB Atlas is a managed solution (just not by Google) which is compatible with the proposed reporting tool (Mongo's own Charts), it's specifically designed for this type of solution and of course it can run on any cloud.


                              質問 # 135
                              You are running a mission-critical application on a Cloud SQL for PostgreSQL database with a multi-zonal setup. The primary and read replica instances are in the same region but in different zones. You need to ensure that you split the application load between both instances. What should you do?

                              正解：B


                              質問 # 136
                              Your company wants to migrate its MySQL, PostgreSQL, and Microsoft SQL Server on-premises databases to Google Cloud. You need a solution that provides near-zero downtime, requires no application changes, and supports change data capture (CDC). What should you do?

                              正解：B

                              解説：
                              Simplify migrations to the cloud. Available now for MySQL and PostgreSQL, with SQL Server and Oracle migrations in preview.
                              * Migrate to Cloud SQL and AlloyDB for PostgreSQL from on-premises, Google Cloud, or other clouds
                              * Replicate data continuously for minimal downtime migrations
                              * Serverless and easy to set up


                              質問 # 137
                              You need to issue a new server certificate because your old one is expiring. You need to avoid a restart of your Cloud SQL for MySQL instance. What should you do in your Cloud SQL instance?

                              正解：C

                              解説：
                              https://cloud.google.com/sql/docs/sqlserver/configure-ssl-instance#server-certs


                              質問 # 138
                              You are designing the backup and recovery strategy of a Cloud SQL for MySQL database that serves a write heavy application. You need to be able to restore the database to any point in time within the past five days while minimizing the performance impact of database backups. What should you do-

                              正解：D

                              解説：
                              Enabling automated backups with point-in-time recovery lets Cloud-SQL capture full backups plus binary logs so you can restore to any second in the last five days. Scheduling the daily snapshot during off-peak hours keeps backup I/O from impacting your write-heavy workload, and setting both backup and log retention to five days meets your recovery window.


                              質問 # 139
                              ......

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