Google Professional Cloud Database Engineer Practice Exam
Google Professional Cloud Database Engineer Practice Exam
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1,396 Learners
What’s Included
No. of Questions299
AccessImmediate
Access DurationLife Long Access
Exam DeliveryOnline
Test ModesPractice, Exam
Google Professional Cloud Database Engineer Practice Exam
A Professional Cloud Database Engineer comes with two years of specific Google Cloud expertise along with a total of five years of experience in both databases and IT. This professional is responsible for the design, establishment, administration, and resolution of issues within Google Cloud databases utilized by applications for data storage and retrieval. Furthermore, they are expected to adeptly convert both business and technical needs into efficient and economical database solutions. The Professional Cloud Database Engineer examination evaluates your proficiency in:
Creating scalable and consistently accessible cloud database solutions.
Managing solutions capable of spanning across various database platforms.
Executing data solution migrations.
Implementing scalable and consistently accessible databases within the Google Cloud platform.
Recommended Experience:
5 years of combined database and IT experience, with at least 2 years of practical involvement in utilizing Google Cloud database solutions.
Who should take the exam?
The exam is the best fit for:
Database administrators (DBAs)
Data engineers
Developers
IT professionals
Exam Details
Exam Name: Professional Cloud Database Engineer
Exam Questions: 50-60
Time Duration: 2 hours
Exam Language: English
Google Professional Cloud Database Engineer Exam Course Outline
The Exam covers the given topics -
Section 1: Understand the Design scalable and highly available cloud database solutions (42%)
1.1 Analyze relevant variables to perform database capacity and usage planning. Activities include:
Given a scenario, perform solution sizing based on current environment workload metrics and future requirements
Evaluate performance and cost tradeoffs of different database configurations (machine types, HDD versus SSD, etc.)
Size database compute and storage based on performance requirements
1.2 Evaluate database high availability and disaster recovery options given the requirements. Activities include:
Evaluate tradeoffs between multi-region, region, and zonal database deployment strategies
Given a scenario, define maintenance windows and notifications based on application availability requirements
Plan database upgrades for Google Cloud-managed databases
1.3 Determine how applications will connect to the database. Activities include:
Design scalable, highly available, and secure databases
1.4 Evaluate appropriate database solutions on Google Cloud. Activities include:
Differentiate between managed and unmanaged database services (self-managed, bare metal, Google-managed databases and partner database offerings)
Distinguish between SQL and NoSQL business requirements (structured, semi-structured, unstructured)
Analyze the cost of running database solutions in Google Cloud (comparative analysis)
Assess application and database dependencies
Section 2: Managing a solution that can span multiple database solutions (34%)
2.1 Determine database connectivity and access management considerations. Activities include:
Determine Identity and Access Management (IAM) policies for database connectivity and access control
Manage database users, including authentication and access
2.2 Configure database monitoring and troubleshooting options. Activities include:
Assess slow running queries and database locking and identify missing indexes
Monitor and investigate database vitals: RAM, CPU storage, I/O, Cloud Logging
Monitor and update quotas
Investigate database resource contention
Set up alerts for errors and performance metrics
2.3 Design database backup and recovery solutions. Activities include:
Given SLAs and SLOs, recommend backup and recovery options (automatic scheduled backups)
Configure export and import data for databases
Design for recovery time objective (RTO) and recovery point objective (RPO)
2.4 Optimize database cost and performance in Google Cloud. Activities include:
Assess options for scaling up and scaling out.
Scale database instances based on current and upcoming workload
Define replication strategies
Continuously assess and optimize the cost of running a database solution
2.5 Determine solutions to automate database tasks. Activities include:
Perform database maintenance
Assess table fragmentation
Schedule database exports
Section 3: Learn about migrating data solutions (14%)
3.1 Design and implement data migration and replication. Activities include:
Develop and execute migration strategies and plans, including zero downtime, near-zero downtime, extended outage, and fallback plans
Reverse replication from Google Cloud to source
Plan and perform database migration, including fallback plans and schema conversion
Determine the correct database migration tools for a given scenario
Section 4: Deploying scalable and highly available databases in Google Cloud (10%)
4.1 Apply concepts to implement highly scalable and available databases in Google Cloud. Activities include:
Provision high availability database solutions in Google Cloud
Test high availability and disaster recovery strategies periodically
Set up multi-regional replication for databases
Assess requirements for read replicas
Automate database instance provisioning
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Reviews
How learners rated this courses
4.8
(Based on 1104 reviews)
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Ryan Cooper
It covered all the key areas like Cloud SQL and Bigtable in a simple, clear way.
John Taylor
The questions were detailed and helped me understand how GCP databases really work.
Emily Parker
Great practice test with realistic examples — perfect for revising before the exam.
