Testing
pg-stress
Schema-aware PostgreSQL stress testing
pg-stress introspects PostgreSQL schemas, discovers relationships, generates realistic ORM and SQL load, and helps teams understand where a database will bend before production traffic proves it.
CLI examples
Inspect a database
pg-stress inspect --dsn $DATABASE_URLBuild the schema graph and workload plan.
Run a stress test
pg-stress run --profile oltpGenerate coordinated SQL and ORM load.
Summarize risks
pg-stress advise --run latestTurn test evidence into operational recommendations.
What it does
A focused workflow, not a generic platform pitch
Each product page follows the same template so the navigation scales while the content stays readable.
Discovers PostgreSQL schema relationships and table roles automatically.
Generates coordinated OLTP-style SQL and ORM workload patterns.
Turns workload results into AI-assisted recommendations for capacity and change safety.
Architecture diagram
pg-stress in the stack
Dark, monospace, and direct. The point is legibility, not decoration.
PostgreSQL
Schema, relationships, indexes, and live test target
Schema Graph
Classifies tables and discovers safe workload paths
Load Workers
Generate realistic SQL and ORM pressure
Advisor
Summarizes bottlenecks, risks, and next tuning steps
Key features
What makes this product useful in practice
The feature list stays product-specific while reusing the same card language across the site.
No hand-built schema config
Point it at a database and let the workload planner inspect the structure.
Realistic load patterns
Exercise relationships, hot tables, and transactional behavior instead of generic queries.
AI-powered advisory
Convert stress output into specific tuning, indexing, and rollout guidance.
Release confidence
Use repeatable tests before high-risk migrations, launches, or scaling events.
Use cases
Where teams get leverage
Simple, concrete use cases are more credible than broad category claims.
Pre-launch validation
Find pressure points before a traffic event or major release.
Migration rehearsal
Replay realistic pressure after schema, index, or infrastructure changes.
Capacity planning
Measure how the database behaves under controlled growth scenarios.
GitHub plus consulting
A clean split between GitHub evaluation and consulting rollout
Each repo should be useful on its own, with Burnside consulting available when teams want help turning it into a production workflow.
Open source
Schema introspection and workload generation
Docker-friendly local test environments
AI-advisory-ready output artifacts
Consulting
Custom workload modeling against production patterns
Release readiness reviews and tuning workshops
Ongoing test plans for platform teams
Call to action
Start building with pg-stress
Review the repo, then bring Burnside in when you want help applying it to a real PostgreSQL environment.