DayBlink helped automate manual testing processes to accelerate development and enhance code quality.
Read the full case study here: Automated Test Suite for Enterprise Application Development
Introduction
A Fortune 500 telecom company struggled with inefficient manual testing processes that could not keep pace with its expanding software portfolio. These challenges resulted in defects slipping into production, negatively impacting user experience and delaying release cycles. The growing complexity of the software ecosystem placed increasing pressure on development, QA, and product teams, who faced difficulties in maintaining consistent quality assurance.
To address these challenges, DayBlink Consulting implemented an automated testing framework integrated into the CI/CD pipeline. By leveraging tools like Jest and PyTest, this solution validated both front-end and API layers, significantly improving code quality, reducing production risks, and freeing up teams to focus on strategic initiatives. This effort not only enhanced development velocity but also strengthened quality assurance practices, leading to a more reliable and scalable software ecosystem.
Problem
Manual testing processes could not keep up with the scale and complexity of the software portfolio.
As the portfolio of applications at a Fortune 500 telecom company expanded, the need to accelerate software development across the enterprise became critical. The existing testing processes, heavily reliant on manual efforts from developers, QA, and product teams, were increasingly inefficient and time-consuming. With many applications in development, manual testing could no longer keep pace with the scale and complexity of the software ecosystem, making it harder to identify and address bugs before deployment. This limitation not only delayed delivery timelines but also created a reactive environment where issues were often addressed after they had impacted production, increasing operational strain.
Defects occasionally slipped into production, leading to negative user experiences, reduced customer satisfaction, and reputational risks. Developers were frequently diverted from planned work to address urgent fixes, disrupting workflows and slowing innovation. The heavy reliance on manual testing also created inconsistencies in test execution, making it difficult to ensure comprehensive coverage across the software portfolio. Additionally, QA and product teams faced increasing difficulty in maintaining application stability while accommodating new features, further slowing the release cycle and compounding risks. The lack of a scalable, automated testing solution hindered the organization’s ability to adapt to market demands, missed opportunities for process optimization, and increased the overall cost of quality assurance efforts.
Solution
DayBlink Consulting implemented an automated testing framework tightly integrated into the CI/CD pipeline.
To address the client’s challenges, DayBlink Consulting developed a robust automated testing framework that seamlessly integrated into the CI/CD pipeline. A dedicated ‘Test’ stage was introduced within the pipeline to act as a pass/fail gate, ensuring that all code passed automated tests before deployment. This system automatically blocked deployments for any failed test case, maintaining code integrity and reliability throughout the development lifecycle.
For front-end testing, DayBlink Consulting leveraged Jest, a powerful testing tool compatible with the client’s React-based UI frameworks, including Material UI. This allowed for comprehensive validation of UI components through unit testing, snapshot testing, and function mocking. Common test scenarios, such as dynamic grid validations, were templatized to simplify the process for developers, enabling consistent and efficient testing across applications.
On the API layer, PyTest was employed to validate endpoints across a wide range of scenarios. A custom test harness was developed to automate input/output validation, ensuring consistent backend performance across the client’s diverse technologies. This solution ensured thorough testing of both front-end and backend layers, reducing the potential for defects to propagate through the system.
By combining these testing mechanisms and integrating them into the CI/CD pipeline, DayBlink Consulting delivered a scalable and reliable testing solution. The automated framework reduced the manual workload, minimized errors, and enhanced the overall quality assurance process for the client’s software portfolio.
This comprehensive solution provided seamless integration between front-end and backend testing, ensuring all application layers were validated thoroughly and efficiently. By automating these processes, DayBlink Consulting significantly reduced the manual workload and improved the overall quality of the client’s software.
Outcome
Automated testing transformed the client’s quality assurance practices, enhancing both efficiency and reliability.
The implementation of an automated testing framework revolutionized the client’s approach to software development and quality assurance. By achieving over 90% code coverage, the solution ensured thorough validation of critical components, significantly reducing the risk of defects entering production. The automation not only streamlined workflows but also alleviated the burden on QA and product teams, enabling them to redirect efforts toward high-value strategic initiatives such as innovation and user experience improvements.
The integration of over 1,000 test cases during the pilot phase underscored the solution’s scalability and rapid implementation capabilities. This foundation enabled dozens of application teams to release new features with greater speed and reliability, bolstering the organization’s agility in responding to market demands. Additionally, the framework fostered a culture of quality assurance by embedding testing best practices into the development lifecycle, ensuring sustainability and alignment with long-term goals. This transformation significantly enhanced development velocity, minimized risks, and improved the overall reliability of the client’s software ecosystem.