Professional-Cloud-Database-Engineer
Google Cloud Database ArchitectureProfessional Cloud Database Engineer Practice TestPractice designing, deploying, migrating, operating, scaling, and troubleshooting cost-effective database solutions for real application requirements. Do not choose a database by product popularityStart with workload behavior: relational or non-relational model,…
Professional-Cloud-Database-Engineer
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Professional Cloud Database Engineer Practice Test
Practice designing, deploying, migrating, operating, scaling, and troubleshooting cost-effective database solutions for real application requirements.
Do not choose a database by product popularity
Start with workload behavior: relational or non-relational model, transactions, consistency, query patterns, scale, latency, regional needs, availability, recovery targets, operational limits, compliance, and team capability. Only then compare Google Cloud database services.
A database decision matrix
Relational workloads
Evaluate Cloud SQL, AlloyDB, and Spanner according to compatibility, scale, availability, transaction, and operational requirements.
Non-relational workloads
Compare Firestore and Bigtable using access patterns, consistency, throughput, key design, latency, and application behavior.
Migration and modernization
Assess source compatibility, downtime, replication, validation, cutover, rollback, schema change, and long-term operating model.
Operational drills
- Design backups, point-in-time recovery, replicas, regional resilience, and a tested restoration procedure.
- Read query plans and metrics to separate database, application, network, and resource bottlenecks.
- Use IAM, database authentication, private connectivity, encryption, auditing, and secrets safely.
- Plan capacity, connection management, maintenance, upgrades, quotas, and cost controls.
- Choose migration tools and a cutover strategy based on acceptable downtime and data risk.