A US financial services company embarked on a modernization journey in Customer Account Management domain, replacing critical mainframe applications with Java and microservices-based architecture on Pivotal Cloud Foundry. This client partnered with Infosys to implement a continuous testing framework that delivers a high-quality product.
The application is responsible for managing the customer accounts including creation and maintenance of these accounts. It manages wide range of individual and organizational customer accounts by having tight integration with multiple downstream applications. It provides various services like synchronization through intraday and daily batch loads with the database, report generation, archival, and purging data on request and supporting downstream applications.
Key challenges
- Legacy mainframe applications with unstable environment and outdated technology
- High cost of quality due to low degree of automation possible and usage of licensed tools
- Complex regression testing requirements due to huge volumes of data from various upstream and downstream channels with different project schedules
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The Solution
Seamless continuous testing framework for a dual-shift DevOps Quality Engineering approach
- Multi-dimensional full-stack automation testing framework for test coverage across all layers (UI, API, and batch)
- UI testing implemented in Selenium, API testing in Parasoft SOAtest, and batch testing using Control-M tools
- BDD in-sprint automation framework complementing continuous testing approach, implemented using Cucumber and Java
- Zero-touch continuous testing pipeline leveraging Atlassian tools stack (Bitbucket, Bamboo, JIRA, and Zephyr)
- Adopted open source tools (Selenium, Cucumber, JMeter) with full stack SDET resources
- Integrated automation scripts with front-end channel application automation and updated the framework for better end-to-end test coverage across upstream and downstream applications
- 85% of test data was self-provisioned through a custom tool developed for mining masked production data. This helped in removing test data dependencies for automation execution.
- Implemented cloud testing best practices and implemented shift-left of performance testing as part of system testing phase
- Implemented blue-green deployment cycles with smoke testing, functional testing, scalability testing, and high availability testing
Transformed traditional ‘Quality Assurance’ to ‘Quality Engineering’
- Adoption of fit-for-purpose automation tools reducing the license cost
- Zero-touch continuous testing framework integrated with DevOps pipeline
- Shift-left in performance and scalability testing
- Test data provisioning and end-to-end test automation
- Scalable solution for easy integration with CI/CD pipeline
Benefits
US$1M+ overall cost reduction
100% schedule adherence, 100% automation of smoke testing scripts, and near 100% in-sprint automation
US$200K year-on-year savings as more applications are integrated
70% effort reduction and 30% improvement in test cycle time
