Google Professional Cloud Database Engineer Practice Exam
Google Professional Cloud Database Engineer Practice Exam
About Google Professional Cloud Database Engineer Exam
A Professional Cloud Database Engineer is a database professional with two years of Google Cloud experience and five years of overall database and IT experience. The Professional Cloud Database Engineer designs, creates, manages, and troubleshoots Google Cloud databases used by applications to store and retrieve data. The Professional Cloud Database Engineer should be comfortable translating business and technical requirements into scalable and cost-effective database solutions.
Key Skills Covered
- Designing scalable and highly available cloud database solutions
- Managing database capacity, connectivity, and performance
- Implementing disaster recovery and high availability strategies
- Optimizing database cost and performance
- Migrating data across environments
- Automating database management tasks
Skills Acquired
- How to design secure, scalable, and efficient databases on Google Cloud
- Ways to configure and monitor cloud databases for performance and cost efficiency
- Best practices for database backup, recovery, and migration
- Understanding of multi-database solutions and high availability setups
Exam Details
- Exam Duration: 2 hours
- Exam Language: English
- Exam format: 50-60 multiple choice and multiple select questions
Course Outline
The Google Professional Cloud Database Engineer Exam covers the latest and updated exam topics -
Domain 1 - Design innovative, scalable, and highly available cloud database solutions (~32%)
1.1 Analyze relevant variables to perform database capacity and usage planning Considerations include:
- Perform solution sizing based on current environment workload metrics and future requirements
- Evaluate performance and cost tradeos of dierent database congurations (e.g., machine types, storage types)
- Size database compute and storage based on performance requirements
1.2 Evaluate database high availability and disaster recovery options given the requirements Considerations include:
- Evaluate tradeos between multi-regional, regional, and zonal database deployment strategies
- Dene maintenance windows and notications based on application availability requirements
1.3 Determine how applications will connect to the database Considerations include:
- Congure networking, key management, encryption, and security
- Justify the use of session pooler services
- Assess auditing policies for managed services
1.4 Evaluate appropriate database solutions on Google Cloud Considerations include:
- Dierentiate between managed and unmanaged database services (e.g., self-managed, bare metal, Google-managed, Google Cloud native and partner database oerings)
- Distinguish between SQL and NoSQL business requirements (e.g., structured, semi-structured, unstructured, vector)
- Analyze the cost of running database solutions in Google Cloud (comparative analysis)
- Assess application and database dependencies
- Identify solutions to support regulatory and compliance requirements
- Understand implications of organizational policies on database strategy
- Consider solutions that span multiple database technologies (e.g. federation,
- exports, hybrid deployments)
- Leverage database technologies to support generative AI and LLM use cases
Domain 2 - Manage a solution that can span multiple database technologies (~25%)
2.1 Determine database connectivity and access management considerations Considerations include:
- Determine Identity and Access Management (IAM) and policies for database connectivity and access control
- Manage database users including authentication and access
2.2 Congure database monitoring and troubleshooting options Considerations include:
- Assess slow running queries, database locking - identify missing indexes
- Monitor and investigate database vitals - RAM, CPU storage, I/O, and audit 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 Considerations include:
- Given requirements, recommend backup and recovery options (automatic scheduled backups)
- Congure export and import data for databases
- Design for RTO, RPO, and PITR
- Manage data retention
2.4 Optimize database cost and performance in Google Cloud Considerations include:
- Assess scaling up and scaling out options
- Scale database instances based on current and upcoming workload
- Dene replication strategies
- Continuously assess and optimize the cost of running a database solution
- Optimize queries for cost and performance
2.5 Automate common database tasks Considerations include:
- Perform database maintenance (e.g., rebuilding indexes, data exports)
- Schedule database exports
- Manage upgrades for Google Cloud-managed databases
- Monitor database SLA/SLOs
Domain 3 - Migrate data solutions (~23% of the exam)
3.1 Design and implement data migration and replication Considerations include:
- Develop and execute migration strategies and plans, including zero/near-zero downtime, extended outage, and fallback
- Reverse replication from Google Cloud to source
- Plan and perform database migration, including fallback plans and DDL/DML conversion
- Determine the correct database migration tools for a given scenario (e.g., databases hosted outside of Google Cloud)
Domain 4 - Deploy scalable and highly available databases in Google Cloud (~20%)
4.1 Apply concepts to implement scalable and highly available databases in Google Cloud. Considerations include:
- Provision highly available database solutions in Google Cloud
- Test high availability and disaster recovery strategies
- Set up multi-regional replication for databases
- Deploy and scale read replicas
- Automate database instance provisioning
- Congure monitoring for highly available databases
