Question 1

What does Cloud SQL for PostgreSQL consulting include?

Accepted Answer

GCP-specific architecture: HA configuration (regional primary + standby, automatic failover), Cloud SQL vs AlloyDB decision for higher-performance Postgres workloads, IAM database authentication setup, Postgres extension management (pgvector, PostGIS, pg_partman, hypopg), Database Migration Service (DMS) cutover, parameter flag tuning, backup + PITR design, the Cloud-SQL-vs-AlloyDB-vs-self-managed economics. Written advisory deliverables.

Question 2

Cloud SQL vs AlloyDB — which fits?

Accepted Answer

Cloud SQL Postgres wins for: standard Postgres workloads, cost-sensitive deployments, exact Postgres community-edition compatibility (Cloud SQL runs upstream Postgres). AlloyDB wins for: Postgres workloads needing more performance (claims 4x faster transactional + 100x faster analytical vs standard Postgres), columnar engine for HTAP workloads, vector search workloads at scale, ML integration with Vertex AI. AlloyDB is significantly more expensive but worth it for performance-critical workloads. We model the workload + cost tradeoff before recommending.

Question 3

Cloud SQL Postgres vs RDS Postgres vs Aurora Postgres?

Accepted Answer

Cloud SQL: GCP-native, IAM-DB auth, integration with BigQuery + Dataflow + Pub/Sub. RDS Postgres: AWS-native with managed parameter groups + Blue/Green Deployments. Aurora Postgres: AWS-native with cluster storage + 15 read replicas + Global Database. Pick based on cloud commitment + workload-shape — for multi-cloud, all are viable. For specific feature requirements (Aurora's cluster storage, AlloyDB's columnar engine, RDS' Blue/Green), the choice narrows.

Question 4

Cloud SQL Postgres extensions — what's supported?

Accepted Answer

Cloud SQL Postgres supports ~75 extensions including pgvector, PostGIS, pg_partman, hypopg, pg_stat_statements, pg_trgm, postgres_fdw, hstore, tablefunc, citext, and more. TimescaleDB is supported on Cloud SQL Postgres. Some extensions need explicit shared_preload_libraries flags. Extensions requiring superuser or filesystem access aren't supported. We audit your extension dependencies against the Cloud SQL supported list early in any migration.

Question 5

IAM database authentication for Postgres — when worth it?

Accepted Answer

Cloud SQL Postgres supports IAM database authentication — clients authenticate using Google Cloud IAM tokens. Use cases: (a) eliminate password rotation overhead, (b) leverage existing GCP IAM groups for DB access, (c) audit DB access via Cloud Audit Logs at the IAM level. Limitations: token-fetch round-trip adds latency on short-lived connections. For Cloud Run / Cloud Functions with persistent connections, IAM auth is excellent. For high-churn connection patterns, password auth via Secret Manager rotation may be simpler.

Question 6

Database Migration Service for Postgres — what does it cover?

Accepted Answer

DMS for Postgres handles: on-prem Postgres → Cloud SQL, EC2/GCE Postgres → Cloud SQL, AWS RDS Postgres → Cloud SQL, Postgres → Cloud SQL within GCP, plus Postgres → AlloyDB. Continuous replication via logical replication enables near-zero-downtime cutover. Schema migration is via DMS schema-conversion + manual review for incompatibilities. We design the migration with DMS handling data movement plus application coordination for the cutover window.

Question 7

Self-managed → Cloud SQL Postgres — what's the playbook?

Accepted Answer

Standard sequence: (1) audit source Postgres version + extension dependencies + replication slot usage, (2) provision Cloud SQL Postgres with matching parameters, (3) configure DMS for continuous replication, (4) wait for backfill + replication lag to settle, (5) flip reads — observe error rate + latency, (6) quiesce writes briefly on source, (7) promote Cloud SQL, (8) cut application endpoints, (9) 24-48 hour soak with source replicated as rollback, (10) decommission source.

Cloud SQL for PostgreSQL Services