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Chapter 1 · Designing scalable, highly available databases·v1.0.0·Updated 6/15/2026·~16 min

What's changed: Created Professional Cloud Database Engineer Chapter 1 (Domain 1 "Design": capacity and HA/DR = workload metrics/perf-cost/zonal-regional-multi-regional/maintenance windows/RTO-RPO-PITR; connectivity/access and DB choice = Cloud SQL Auth Proxy/private IP/CMEK/session poolers/audit, Cloud SQL/AlloyDB (vector/gen AI)/Spanner/Bigtable/Firestore, managed/SQL/NoSQL/vector).

1.2Connectivity, access, and choosing databases

Key points

Understand network connectivity, key management, encryption, and security for databases, using session poolers, auditing policies, and choosing the right database solution by managed/unmanaged, SQL/NoSQL/vector, cost, regulation, and generative AI/LLM support.

Databases must be connected securely and chosen to best fit the use case. Cover connectivity/access design and choosing the database solution.

1.2.1Connectivity, access, and security

Apps connect securely via Cloud SQL Auth Proxy (IAM auth/encryption) or private IP without exposing a public IP. Manage keys with Cloud KMS (CMEK), encrypting at rest/in transit. Reuse many connections with session poolers (connection pools) to avoid exhaustion. Track who-did-what with audit logs. Map "avoid public IP, secure connect = Auth Proxy/private IP" and "anti-exhaustion = session poolers."

1.2.2Choosing database solutions

RequirementChoice
Typical business RDBCloud SQL
High-perf PostgreSQL, vector/gen AIAlloyDB
Global strong-consistency RDBSpanner
Huge-scale low-latency NoSQLBigtable
Document NoSQLFirestore

Choose databases by requirements: structured/semi/unstructured/vector, SQL vs NoSQL, cost, regulation/compliance, and generative AI/LLM support (vector search, embeddings). Decide managed (Google-run) vs unmanaged (self/bare metal). For high-performance PostgreSQL with vector/gen AI, AlloyDB; global strong consistency = Spanner; huge-scale low-latency = Bigtable. Map "PostgreSQL with vector/gen AI = AlloyDB" and "managed reduces operational burden."

Exam point

Common: requirement → DB. E.g., "secure connect without public IP" = Cloud SQL Auth Proxy/private IP; "prevent connection exhaustion" = session poolers; "manage keys yourself" = CMEK (Cloud KMS); "global strong consistency" = Spanner; "high-perf PostgreSQL with vector/gen AI" = AlloyDB; "huge-scale low-latency" = Bigtable; "reduce ops burden" = managed.

Warning

Watch the mix-ups: (1) Do not confuse Cloud SQL (typical RDB)/AlloyDB (high-perf PostgreSQL, vector)/Spanner (global strong)/Bigtable (low-latency NoSQL). (2) Connect via Auth Proxy/private IP, avoiding public IP. (3) Use session poolers to avoid exhaustion under many connections.

Diagram of Cloud SQL Auth Proxy/private IP/CMEK/session poolers/audit and choosing Cloud SQL/AlloyDB (vector/gen AI)/Spanner/Bigtable/Firestore.
Connect securely; choose well

1.2.3Section summary

  • Secure connect = Cloud SQL Auth Proxy/private IP, CMEK; session poolers prevent exhaustion
  • DB choice = Cloud SQL/AlloyDB (vector/gen AI)/Spanner/Bigtable/Firestore by requirements
  • Decide by managed/unmanaged, SQL/NoSQL/vector, cost/regulation

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Quick check

(just a quick review)

Q1. You need a globally distributed, strongly consistent relational DB. Which is best?

Q2. For high-performance PostgreSQL-compatible with vector search/gen-AI use, which is best?

Q3. To connect to Cloud SQL securely with IAM auth/encryption without exposing a public IP, what do you use?

Q4. To prevent connection exhaustion under many app connections, what do you use?

Q5. For huge-scale, low-latency time series/IoT data, which is best?

Q6. To manage database encryption keys yourself, what do you use?

Check your understandingPractice questions for Chapter 1: Designing scalable, highly available databases