Step-by-Step Guide: Migrating MySQL Databases to Google Cloud SQL with Minimal Downtime

Downtime and data loss—these are the two risks architects mention most when discussing database migrations. Managed cloud backends like Google Cloud SQL mitigate operational headaches, but the migration process itself isn’t trivial, especially for production workloads.

Below, you’ll find a direct, detail-oriented process for moving MySQL databases (v5.6, v5.7, or v8.0) to Google Cloud SQL with near-zero downtime. Both dump/import and replication-based strategies are covered, with explicit attention paid to data integrity and operational realism.

Is Cloud SQL Worth the Move?

• Fully managed (maintenance, backups, minor version upgrades).
• Supports high availability and automated failover.
• Data encrypted in transit and at rest; integrates with VPC, IAM.
• Connection endpoints (private or public) support seamless migration and peering.

Migrating removes patching drudgery and makes high-availability features accessible even for smaller teams. But trade-offs exist: fine-grained tuning is limited, and some MySQL plugins/extensions aren’t supported.

Migration Workflow: Shortlist

1. Baseline source MySQL—maintenance and binlog config.
2. Deploy and secure a Cloud SQL instance.
3. Select migration methodology: logical dump/restore or change-data-capture via replication.
4. Cutover: reroute application traffic with managed downtime.
5. Verify end-state, clean up old hosts.

1. Prepare Source MySQL Environment

Maintenance and configuration on the source database are crucial for a smooth migration.

• Prune obsolete tables, defragment storage where feasible (OPTIMIZE TABLE).

• Confirm MySQL version—Google Cloud SQL supports 5.6, 5.7, 8.0 (as of 2024-06).

• Enable binary logging if using replication:

  [mysqld]
  log_bin        = mysql-bin
  binlog_format  = ROW
  server_id      = 1501
  expire_logs_days = 7  # Reduce only if disk is low; keep at least several days for safety.
  

  Typical gotcha: existing MySQL servers may be set to STATEMENT format—switching to ROW is critical, else you’ll see replication errors like:

  ERROR 1236 (HY000): Could not find first log file name in binary log index file
  

Restart MySQL. Verify with:

SHOW VARIABLES LIKE 'log_bin%';
SHOW VARIABLES LIKE 'binlog_format';

2. Provision Google Cloud SQL

• Create Instance: Use Google Cloud Console → SQL → Create Instance → MySQL (match source version as closely as possible).
• For production, set High Availability to ON (regional configuration); for test, standard is fine.
• Enable automatic backups and point-in-time recovery.
• Configure root password and network connectivity:
  • Private IP strongly preferred (enforceable via VPC peering).
  • Whitelist source DB and migration tool IPs if using public IP.

Side note: Cloud SQL disks are managed by GCP; tuning innodb_flush_log_at_trx_commit and similar low-level params is possible, but Google enforces some opinionated defaults. Document any needed overrides before migration.

3. Select Migration Method

Approach A: Dump & Restore
Simple, works well for DBs <100GB and tolerant to hours of downtime.

• Take a logical backup:

  mysqldump --single-transaction --quick --routines --triggers \
            -u admin -p  mydb > /tmp/mydb.sql
  

  (--single-transaction avoids table locks, as long as all tables are InnoDB.)

• Transfer SQL file to Cloud Storage:

  gsutil cp /tmp/mydb.sql gs://your-migration-bucket/
  

• Import into Cloud SQL:

  gcloud sql import sql <INSTANCE> gs://your-migration-bucket/mydb.sql --database=mydb
  

Expect downtime spanning backup + transfer + import. For multi-GB DBs, imports can throttle at 10–20 MB/s—budget accordingly.

Approach B: External Replication (Minimal Downtime, Production-Grade)

More complex, but actual downtime often reduced to <5 minutes.

1. Take a consistent snapshot

mysqldump --single-transaction --master-data=2 --routines --triggers \
          -u admin -p mydb > /tmp/snap.sql

--master-data=2 bookmarks binlog location for later replication start.

2. Import dump to Cloud SQL (as above).

3. Configure source for replication

• Create a replication user:

  CREATE USER 'cloudsql_replica'@'%' IDENTIFIED BY 'REDACTED';
  GRANT REPLICATION SLAVE ON *.* TO 'cloudsql_replica'@'%';
  FLUSH PRIVILEGES;
  

• Locate correct binlog coordinates in snap.sql:

  -- CHANGE MASTER TO MASTER_LOG_FILE='mysql-bin.000024', MASTER_LOG_POS=154;
  

4. In Google Cloud Console:

• Go to Cloud SQL → your instance → "External Replicas" → "Set up Replication".
• Specify source host, replication credentials, and binlog coordinates.
• Cloud SQL will connect as a read replica and sync all changes since the initial dump.

5. Watch replication lag:

SHOW SLAVE STATUS\G

or use Cloud Console monitoring.

6. Cut over application traffic:

• Schedule a brief maintenance window.
• Temporarily block writes on source (FLUSH TABLES WITH READ LOCK;), wait for Cloud SQL to catch up, then update application configs to target Cloud SQL endpoint.
• Release read lock, demote original source as needed.

Tip: Some teams reduce downtime to <30 seconds this way, but latent writes or skipped triggers might prolong it.

4. Switch Application Connectivity

Update all connection strings/secrets. Re-run integration tests and functional smoke tests. Monitor latency metrics—the Cloud VPN hop can introduce 2–10ms overhead compared to on-prem DBs.

• Gradually ramp live traffic while watching error logs.
• Known issue: older MySQL clients (pre-5.7) sometimes fail SSL/TLS negotiation with Cloud SQL. Upgrade client libraries if errors like SSL connection error: unknown error number appear.

5. Final Consistency Validation & Legacy Decom

• Compare table counts, row aggregates, checksums (e.g., pt-table-checksum from Percona Toolkit) between old and new.
• Audit error logs for straggler writes or missed binlogs.
• Leave source DB in read-only mode for a few days if rollback is plausible, then decommission or repurpose as analytics replica.

Extra: Useful Tools & Tips

Non-obvious tip: For databases >500GB or with >100k writes/hour, consider partitioning migration by schema or table and use parallel dump/import scripts to avoid throttling.

Summary

Migrating to Google Cloud SQL—not risk-free, but doable without long outages. Enabling ROW-based binlog, using replication for cutover, validating with rigorous checks: these steps ensure data consistency and service continuity.

Any edge case—unusual plugins, custom storage engines, super-large blobs—should be piloted in a test environment first. Database migrations rarely go 100% to plan; the real skill is in controlling the variables you can.

Questions about plugin incompatibility, binlog retention, or performance tuning are common. If they come up, be ready with references to recent Google Cloud docs and diagnostics from real migrations.