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How an IT service provider optimized software delivery using QALIPSIS

What if every pull request caught performance regressions automatically?

About the company

A leading IT service provider building complex, high-demand applications for clients across finance, healthcare, and retail — managing dozens of active projects with distinct technology stacks and release cadences.
How an IT service provider optimized software delivery using QALIPSIS

Industry

IT Services

Key challenge

Resource-intensive, manual performance testing that detected bottlenecks too late in the development cycle; limited insight into root causes

Stack under test

Jenkins, GitHub Actions and technologies depending on client project

QALIPSIS deployment

Bootstrap project, Gradle plugin, CI/CD integration, JUnit reporting, email notifications

Challenges

Why are bottlenecks found only weeks before delivery?

  • Engineers ran load tests manually against staging in the final weeks before release.
  • Test scripts lived outside the codebase and quickly drifted from the application.
  • Reports showed aggregate failures but lacked detail to pinpoint the problem location.
  • Performance testing needed to become continuous and developer-owned, not a late gate.

Solution: how QALIPSIS was used

How to keep test scenarios in sync with the application?

  • Bootstrap project initialised each client project with the QALIPSIS test structure.
  • Scenarios written in Kotlin, stored in the same Git repository as application code.
  • Developers updated scenarios in the same commit as application changes.

How to automate execution in CI/CD pipelines?

  • Smoke tests ran as nightly builds; full suites ran weekly.
  • JUnit-format reports published as pipeline artefacts for every run.
  • Any breach of response-time or error-rate thresholds failed the build automatically.
  • Regressions introduced midweek were flagged by the next morning’s nightly build.

How to get actionable reporting across teams?

  • Per-step breakdowns showed which step failed and the type of error — execution or verification.
  • Email notifications on build failures alerted development, operations, and management.

Results

shorter testing cycles
cost reduction in testing
faster issue resolution
higher test frequency

Conclusion

Challenge

Manual performance testing detected bottlenecks too late, with test scripts drifting from the application and reports lacking root-cause detail.

Solution

QALIPSIS scenarios versioned alongside application code, executed through Gradle tasks in CI/CD pipelines with JUnit reporting and email notifications.

Gains

55% less testing time, 60% cost savings, 50% more test iterations, and regressions caught within hours instead of weeks before delivery.

More use cases to explore

Looking to streamline your software testing process and reduce costs?
Request a demo of QALIPSIS today!