Preparing the next view without exposing private workflow data.
Performance engineering · Phased project
Keep the operations inbox fast as history grows
A fictional maintenance service lists open work orders beside years of closed history. A query that was cheap in a small demo now scans far more rows than it returns. Recreate the schema and synthetic workload locally; no customer database or supplied fixture is assumed.
Practice reading execution plans, balancing read and write cost, and validating performance without weakening tenant boundaries.
What the team gains
Create reproducible query diagnostics and reversible index or query proposals for an operational application.
Before you start
Create an isolated local database with tenants, work orders and assignment history.
Seed 200,000 synthetic work orders with documented skew and a repeatable random seed; record PostgreSQL version, settings and resource limits.
Delivery agreement
Ten tickets from workload definition to guarded migration. Estimates exclude database setup and predecessor tickets; all destructive data fixtures remain local and synthetic.
AI tools are welcome during implementation. Record assumptions, review the result, and verify its behavior.