Test Management

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gitlab3 min readCurated summary

Streamline test management with SmartBear QMetry GitLab component

The SmartBear QMetry GitLab Component automates the transfer of test results from GitLab CI/CD pipelines into QMetry Test Management Enterprise. By publishing JUnit, TestNG, and other supported results automatically, it removes manual uploads and provides a centralized, traceable view of testing. The integration helps teams accelerate release decisions while supporting compliance and audit requirements. ## Why Integrate GitLab with QMetry? - **Eliminate manual uploads:** Test results are transferred automatically after pipeline execution, reducing effort and preventing outdated or inconsistent records. - **Improve traceability:** Teams can connect requirements, test cases, executions, commits, builds, and pipelines in a single audit trail. - **Accelerate feedback:** QA teams, product managers, and stakeholders gain access to results immediately after tests finish. - **Support regulated development:** Centralized, versioned test records help organizations in aerospace, financial services, automotive, and medical-device industries demonstrate test coverage and compliance. - **Enable AI-driven insights:** QMetry can analyze execution history to identify flaky tests, predict failures, and suggest optimization opportunities. ## GitLab–SmartBear Integration - The component is part of a broader partnership connecting GitLab’s CI/CD and DevSecOps capabilities with SmartBear’s testing and quality-management tools. - The integration is intended for organizations that need centralized visibility across complex or regulated software-development lifecycles. - QMetry acts as the system of record for test planning, execution, tracking, and reporting. ## Requirements and Test Result Flow Before configuring the integration, teams need: - A GitLab project with automated tests that generate JUnit XML, TestNG XML, or another supported format. - A QMetry Test Management Enterprise account with API access enabled. - A QMetry API key with permission to upload test results. - An existing QMetry project. - Basic knowledge of GitLab CI/CD and `.gitlab-ci.yml`. - Optionally, a configured QMetry test suite for better organization. The automated flow is: - GitLab runs unit, integration, end-to-end, or other automated tests. - The tests generate result files. - The QMetry component runs as a pipeline job. - It reads the result files and uploads them to QMetry through the API. - QMetry processes the results for reporting and analysis. ## Obtaining QMetry API Credentials - Log in to QMetry Test Management Enterprise. - Open the user profile and navigate to **Settings** or **API Access**. - Generate a named API key, such as `GitLab CI/CD Integration`. - Grant the key write access for test-result uploads. - Copy the key immediately because it is displayed only once. - Record the QMetry instance URL, typically in the form `https://your-company.qmetry.com`. The API key should be treated like a password. It should not be committed to `.gitlab-ci.yml` or stored in plain text; GitLab CI/CD variables should be used to protect it. The component provides a practical way to make QMetry the centralized source of truth for pipeline testing. Organizations should secure the API credentials, configure the component in their GitLab pipeline, and continuously publish results so teams can improve visibility, traceability, and release confidence.

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tossOriginal article

Toss Income QA Platform: The Beginning (opens in new tab)

Toss's QA team developed an internal "QA Platform" to solve the high barrier to entry associated with using Swagger for manual testing and data setup. By transforming complex, multi-step API calls into a simple, button-based GUI, the team successfully empowered non-QA members to perform self-verification. This shift effectively moved quality assurance from a final-stage bottleneck to a continuous, integrated part of the development process, significantly increasing product delivery speed. ### Lowering the Barrier to Test APIs * Existing Swagger documentation was functionally complete but difficult for developers or planners to use due to the need for manual JSON editing and sequential API execution. * The QA Platform does not create new APIs; instead, it provides a GUI layer over existing Swagger Test APIs to make them accessible without technical documentation. * The system offers two distinct interfaces: "Normal Mode" for simplified, one-click testing and "Swagger Mode" for granular control over request bodies and parameters. ### From Manual Clicks to Automation and Management * Phase 1 focused on visual accessibility, allowing users to trigger complex data states via buttons rather than manual API orchestration. * Phase 2 integrates existing automation scripts into the platform, removing the need for local environment setups and allowing anyone to execute automated test suites. * The final phase aims to transition into a comprehensive Test Management System (TMS) tailored to the team's specific workflow, reducing reliance on third-party external tools. ### Redefining Quality as a Design Choice * By reducing the time and mental effort required to run a test, verification became a frequent, daily habit for the entire product team rather than a chore for the QA department. * Lowering the "cost" of testing replaced guesswork with data-driven confidence, allowing the team to move faster during development. * This initiative reflects a philosophical shift where quality is no longer viewed as a final checklist item but as a core structural element designed into the development lifecycle. The primary takeaway for engineering teams is that the speed of a product is often limited by the friction of its testing process. By building internal tools that democratize testing capabilities—making them available to anyone regardless of their technical role—organizations can eliminate verification delays and foster a culture where quality is a shared responsibility.