QA for Nanitor

Nanitor brings in DeviQA to set up the QA process for its CTEM platform.

1200+

Test cases created

90%

Test coverage

500+

Number of bugs logged

AI tools were integrated into the testing workflow, enabling faster test case creation, efficient test data generation, and richer bug reports. It also helped the team to streamline some routine tasks and focus on more critical processes.

About project

Nanitor is an enterprise-grade Continuous Threat Exposure Management (CTEM) platform that strengthens cybersecurity through refined visibility, real-time control, strategic prioritization, and comprehensive asset and issue management.

With Nanitor, organizations can proactively manage vulnerabilities, misconfigurations, patches, compliance, and software issues at a fraction of the cost and time.

Before DeviQA

There was no well-defined, formal quality control process
Testing was executed mostly in the UAT phase
The functionality wasn’t covered with tests
Bug reports often lacked sufficient context
AI wasn’t introduced in the testing process

With DeviQA

A Jira flow was refined to introduce the QA process into the development and release cycles.
- Release velocity increased by 30%
- Critical production bugs decreased by 25%
Testing shifted to the integration and staging phase.
- Overall testing time decreased by 40%
- Early defect detection increased by 80%
A test management tool and test suite were set up from scratch.
- Regression risk decreased by 80%
A bug-reporting culture was significantly improved.
- All tickets now include the necessary details (attachments, logs, etc.), and 100% of reports contain screenshots or videos
- Ticket reopen rate decreased by 80%
- Defect reproduction time decreased by 30%
Artificial intelligence was integrated into the testing process.
- Test case creation speed increased by 30%
- Test data generation is 60% faster

Our contribution

Team

1 manual QA engineer

Project length

Since 2022

Technologies and tools

Jira

Confluence

GitHub

Testmo

Slack

1Password

Sentry

Google Docs

Postman

Microsoft Dynamics 365

Microsoft Copilot

ChatGPT

Testcraft

Linux Terminal

Windows Command Line

MSSQL

PostgreSQL

Docker

Our engagement

Our QA specialist was tasked to set up the QA process, integrate it into the development and release cycles, reduce the number of bugs on prod, and improve issue tracking and reporting.

Key initiatives:

QA process and Jira flow optimization

The first major initiative was redesigning the Jira workflow. The new flow was implemented to seamlessly integrate the QA process into the broader development and release pipelines, ensuring smoother collaboration between teams and removing bottlenecks.

Test management tool and test suite setup

Functionality wasn’t covered with tests, so testing was performed through exploratory testing alone. A test management platform was set up to store, manage, and run test cases. This made it possible to create a set of tests for regular regression and smoke testing.

Testing approach optimization

All testing activities were moved to the staging environment, which made it possible to skip the UAT phase and reduce the risk of critical bugs slipping into production. This change also sped up release cycles by cutting down the number of hotfixes after deployment.

Bug reporting culture reconsideration

We implemented a unified standard for bug reporting. Now all bug reports have clear reproduction steps, clear expected results, and necessary attachments such as videos, screenshots, or logs. Altogether, this significantly improves the issue localization and resolution process.

Thanks to these initiatives, the QA process became more transparent, efficient, and aligned with development practices. Also, testing efforts became more focused, the quality of communication and issue reporting improved, and overall development cycles became faster and more reliable.

Services provided

Manual testing

Our QA engineer introduced a structured QA process into the development cycle. The Jira workflow was revised to integrate the QA process properly. All testing activities were moved to the staging environments. The bug reporting policy was standardized. In addition, a test suite was created from scratch to ensure good test coverage for each release. Also, the QA engineer implemented artificial intelligence tools to speed up task completion and make it even more efficient. All these changes led to improved collaboration, faster releases, and better product quality.

Dedicated QA team

Our QA engineer established a QA process from scratch, integrated it into the existing development process. He focused on improving test coverage and bug reporting, which had a direct positive impact on the product release cycles and product quality. Collaboration with developers, designers, and product owners allowed him to organize a clear testing process that fit the vision and requirements of the product.

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