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Migration Playbook

Unified OLTP + Analytics on PostgreSQL→Separated OLTP (PostgreSQL) + OLAP (ClickHouse/Snowflake)

Medium complexityMedium riskAlways Possible

Duration Estimate

2–6 weeks

Migration Stages

6

Blocking Prerequisites

2

Confidence

Strong

Readiness Checklist(2 blocking, 4 advisory)

blocking
Team

Team at senior maturity level

This migration requires senior engineering maturity. The team should have hands-on experience with the relevant technologies and proven ability to execute complex system changes safely.

Guidance: Build team skills through learning modules before attempting this migration.

blocking
Monitoring

Production observability baseline established

Comprehensive metrics, logs, and traces must be in place before the migration starts. You need a clear baseline to detect regressions during and after each migration stage.

Guidance: Instrument key metrics (latency p99, error rate, throughput, resource utilization) on all affected components.

Process

Rollback plan documented and tested

Rollback feasibility for this migration is 'always'. Rollback is possible but may be complex, document the exact rollback steps and test them in a non-production environment.

Guidance: Run a full dry-run in a staging environment that mirrors production load characteristics.

Infrastructure

'clickhouse' provisioned and validated in target environment

'clickhouse' must be available, configured, and load-tested in the target environment before the migration stage that introduces it.

Guidance: Deploy 'clickhouse' with production-equivalent configuration. Run a smoke test under representative load.

Infrastructure

'kafka' provisioned and validated in target environment

'kafka' must be available, configured, and load-tested in the target environment before the migration stage that introduces it.

Guidance: Deploy 'kafka' with production-equivalent configuration. Run a smoke test under representative load.

Process

Migration trigger condition confirmed

Confirm that the actual trigger for this migration is present. Common triggers: Analytical queries (dashboards, reports, aggregations) consistently spike OLTP P99 latency; Buffer cache hit rate degrades during analytics windows: hot OLTP pages evicted by cold analytical scans; Query execution times for analytical queries exceed 10 seconds on data >100M rows.

Guidance: Validate the trigger with production metrics or benchmarks before committing to the migration timeline.

Migration Stages

1Analytics Workload AuditLow1 week

Identify all analytical queries running against OLTP database. Classify by user (BI team, scheduled reports, dashboard aggregations). Measure query frequency, duration, and OLTP impact (buffer cache eviction, lock contention).

Key tasks

  • ·Identify all analytical queries running against OLTP database. Classify by user (BI team, scheduled reports, dashboard aggregations). Measure query frequency, duration, and OLTP impact (buffer cache eviction, lock contention).
  • ·Validate rollback capability at this stage boundary before proceeding.

Exit criteria

  • ✓'Analytics Workload Audit' validated in production with no regression in key metrics

Rollback: possible at this stage

2OLAP Store ProvisioningLow2-3 weeks

Deploy ClickHouse or Snowflake. Define analytical schema (star schema or wide tables). Configure retention policy. Set up monitoring for query performance and storage cost.

Key tasks

  • ·Deploy ClickHouse or Snowflake. Define analytical schema (star schema or wide tables). Configure retention policy. Set up monitoring for query performance and storage cost.
  • ·Validate rollback capability at this stage boundary before proceeding.

Exit criteria

  • ✓'OLAP Store Provisioning' validated in production with no regression in key metrics

Rollback: possible at this stage

3Historical Data LoadMedium1-2 weeks

Export and load historical data from PostgreSQL to OLAP store. Validate row counts, data types, and query results against PostgreSQL source.

Key tasks

  • ·Export and load historical data from PostgreSQL to OLAP store. Validate row counts, data types, and query results against PostgreSQL source.
  • ·Validate rollback capability at this stage boundary before proceeding.

Exit criteria

  • ✓'Historical Data Load' validated in production with no regression in key metrics

Rollback: possible at this stage

4CDC Pipeline SetupMedium2-4 weeks

Deploy Debezium connector for PostgreSQL WAL streaming. Configure Kafka topic per table. Deploy OLAP store consumer. Validate replication lag and data accuracy.

Key tasks

  • ·Deploy Debezium connector for PostgreSQL WAL streaming. Configure Kafka topic per table. Deploy OLAP store consumer. Validate replication lag and data accuracy.
  • ·Validate rollback capability at this stage boundary before proceeding.

Exit criteria

  • ✓'CDC Pipeline Setup' validated in production with no regression in key metrics

Rollback: possible at this stage

5Analytics Traffic MigrationLow2-3 weeks

Point BI tools, scheduled reports, and dashboards at OLAP store. Validate query results match PostgreSQL source within expected lag window. Monitor OLTP buffer cache hit rate recovery.

Key tasks

  • ·Point BI tools, scheduled reports, and dashboards at OLAP store. Validate query results match PostgreSQL source within expected lag window. Monitor OLTP buffer cache hit rate recovery.
  • ·Validate rollback capability at this stage boundary before proceeding.

Exit criteria

  • ✓'Analytics Traffic Migration' validated in production with no regression in key metrics

Rollback: possible at this stage

6Analytics Index CleanupLow1 week

Drop indexes from OLTP database that existed solely for analytical queries. Verify write throughput improvement. Monitor for any missed queries still hitting OLTP.

Key tasks

  • ·Drop indexes from OLTP database that existed solely for analytical queries. Verify write throughput improvement. Monitor for any missed queries still hitting OLTP.
  • ·Validate rollback capability at this stage boundary before proceeding.

Exit criteria

  • ✓'Analytics Index Cleanup' validated in production with no regression in key metrics

Rollback: possible at this stage

Rollback Decision Points

After stage 6

Trigger: Final validation: confirm all success criteria are met within 24 hours of migration completion. If any success criterion fails, trigger rollback or remediation.

Procedure: If success criteria are not met within 24 hours, escalate to the architecture team. Decide between full rollback, partial rollback, or targeted remediation based on scope.

Recovery: 24–72 hours for full assessment and remediation

Success Criteria

  • ✓Target state 'Separated OLTP (PostgreSQL) + OLAP (ClickHouse/Snowflake)' is stable in production for 72+ hours with no regressions.
  • ✓p99 latency on all affected services is within acceptable range (≤110% of pre-migration baseline).
  • ✓Error rate is at or below pre-migration baseline.
  • ✓New components (clickhouse, kafka) are fully operational and monitored.

This migration playbook is derived from structured architecture knowledge. Duration estimates and risk levels are structural approximations based on documented migration complexity and operational risk, not measured execution data. Validate all stages against your specific system constraints before executing.