


This give you mini questions covers main field of GCP database engineer exam, covers following topics:
Topic 1: Evaluate performance and cost trade offs of different database configurations/ Plan database upgrades for Google Cloud-managed databases
Topic 2: Provision high availability database solutions in Google Cloud/ Design scalable and highly available cloud database solutions
Topic 3: Determine the correct database migration tools for a given scenario/ Size database compute and storage based on performance requirements
Topic 4: Plan and perform database migration, including fallback plans and schema conversion/ Test high availability and disaster recovery strategies periodically
Topic 5: Distinguish between SQL and NoSQL business requirements/ Evaluate tradeoffs between multi-region, region, and zonal database deployment strategies
Topic 6: Apply concepts to implement highly scalable and available databases in Google Cloud/ Given a scenario, define maintenance windows and notifications based on application availability requirements
Topic 7: Analyze relevant variables to perform database capacity and usage planning/ Design scalable, highly available, and secure databases
Topic 8: Differentiate between managed and unmanaged database services/ Analyze the cost of running database solutions in Google Cloud
Topic 9: Reverse replication from Google Cloud to source/ Evaluate appropriate database solutions on Google Cloud
Topic 10: Manage database users, including authentication and access/ Continuously assess and optimize the cost of running a database solution
Topic 11: Design for recovery time objective (RTO) and recovery point objective (RPO)/ Assess slow running queries and database locking and identify missing indexes
Topic 12: Deploy scalable and highly available databases in Google Cloud/ Determine database connectivity and access management considerations
Topic 13: Automate database instance provisioning/ Determine how applications will connect to the database
Topic 14: Justify the use of session pooler services/ Given a scenario, perform solution sizing based on current environment workload metrics and future requirements