What's changed: Created Professional Cloud Database Engineer Chapter 2 (Domain 2 "Manage": access management and monitoring/troubleshooting = IAM/DB users, slow queries/locking/missing indexes, vitals/audit logs/Cloud Monitoring, quotas/contention/alerts; backup/recovery and optimization/automation = automatic scheduled backups/PITR/export/retention, scale up-out/read replicas/query optimization, index rebuilds/exports/upgrades/SLA-SLO automation).
2.1Access management and monitoring/troubleshooting
Understand IAM and policies for database connectivity/access control, managing user authentication/access, investigating slow queries/locking/missing indexes, monitoring vitals (RAM/CPU/storage/IO) and audit logging, quota management, resource contention, and alerts for errors and performance.
Operating multiple database technologies requires governing access and monitoring/troubleshooting—the core of day-to-day operations.
2.1.1Access management
Control database connectivity/access with IAM and policies, enforcing least privilege. Create/authenticate/authorize database users (DB-native or IAM-federated) and manage who can access which data. Map "connectivity/access control = IAM + policies" and "manage DB user authentication and privileges."
2.1.2Monitoring and troubleshooting
Isolate performance issues systematically: analyze slow queries, investigate locking (contention), and identify missing indexes. Monitor database vitals (RAM/CPU/storage/IO) and audit logs with Cloud Monitoring/Logging, and alert on error/performance thresholds. Monitor/update quotas and investigate resource contention. Map "slow query = suspect indexes/plan" and "monitor DB state = vitals + alerts."
Common: symptom → means. E.g., "a query is slow" = slow-query analysis, add missing indexes; "lots of waits" = investigate lock contention; "monitor DB state and alert" = vitals + Cloud Monitoring alerts; "who accessed" = audit logs; "connectivity/access control" = IAM + DB user management.
Watch the mix-ups: (1) For slow queries, suspect indexes/plan/locks in order. (2) Vitals monitoring (Monitoring) and audit logs (Logging) differ. (3) Get ahead of quota overruns by monitoring/updating them.
For analytics, also know BigQuery, a columnar serverless data warehouse. It aggregates petabyte-scale data with standard SQL, with storage and compute separated to scale independently. Separate operational (OLTP) Cloud SQL/Spanner from analytical (OLAP) BigQuery by role, and integrate/export to BigQuery for analysis as needed.
2.1.3Section summary
- Connectivity/access via IAM + policies + DB user management with least privilege
- For slow queries, suspect indexes/plan/locks; identify missing indexes
- Monitor vitals (RAM/CPU/IO) and audit logs with Cloud Monitoring/Logging and alert
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Quick check
(just a quick review)Q1. A specific query is slow. What should you suspect and address first?
Q2. To monitor DB vitals (RAM/CPU/storage/IO) and alert on thresholds, what do you use?
Q3. To control DB connectivity/access with least privilege, what do you use?
Q4. Transactions are waiting on each other and performance drops. What should you investigate?
Q5. To track who accessed/operated the database and when, what do you use?
Q6. To proactively prevent quota-exceeded errors, which is most appropriate?
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