performance-testing

To run load testing and stress testing for a multi-tenant IdP server, you configure environment variables and execute the provided k6 scripts to target individual APIs and full E2E authentication flows, identifying system bottlenecks and validating scalability.

The best way to identify performance bottlenecks in IdP server deployments is through structured end-to-end stress testing using k6. This process pinpoints system limits across API, authentication, and token services within multi-tenant environments.

Yes, you need k6, Python 3, and the PostgreSQL client installed to perform IdP server scalability evaluations. These dependencies are required to execute the scripts that prepare tenants, generate test data, run tests, and analyze results.

To prepare test data for multi-tenant performance testing, you use the provided Python 3 and PostgreSQL client scripts to generate tenants and configure data. This setup ensures stable load testing as tenants and users grow.

Yes, k6 scripts can validate stable performance as multi-tenant users grow by applying load and scalability validation tests. This ensures the IdP server handles increasing tenants and users without performance degradation.

Stress testing fails to pinpoint system limits without structured scripts because it lacks the ability to prepare multi-tenant data and reproduce consistent load scenarios. The provided scripts ensure accurate bottleneck identification across API and token services.