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Genrocket Case Study
技术
- 应用基础设施与中间件 - API 集成与管理
- 平台即服务 (PaaS) - 数据管理平台
- 分析与建模 - 实时分析
适用功能
- 质量保证
- 商业运营
用例
- 预测性维护
- 连续排放监测系统
服务
- 系统集成
- 软件设计与工程服务
挑战
The insurance company faced challenges with their traditional Test Data Management (TDM) platform, which was costly and complicated. The manual provisioning of test data became a bottleneck as they streamlined their software development process into a Continuous Integration and Continuous Delivery (CI/CD) pipeline using Jenkins. The TDM solution was too cumbersome to keep pace with the accelerated speed of development. They needed a more nimble process allowing testers to generate any kind of test data on-demand with a simple self-service provisioning model. The goal was to replace the TDM system and its centralized provisioning process with a more automated, cost-effective, and decentralized approach.
关于客户
The customer is a major insurance company diversified into various insurance categories, including life, health, accident, critical illness, dental, vision, disability, and related products such as annuities and retirement planning. Their insurance products cater to both individuals and families, as well as businesses and organizations. The company manages over 100 applications with complex data structures that require continuous testing to maximize quality and minimize time to market. They had been using a traditional Test Data Management (TDM) platform to provision test data for testing a variety of insurance applications. However, the TDM solution was proving to be costly and complicated, and manually provisioned test data had become a bottleneck as they streamlined their software development process into a Continuous Integration and Continuous Delivery (CI/CD) pipeline.
解决方案
GenRocket integrated its Test Data Generation (TDG) engine with the Jenkins CI/CD server and its automated test environment. The integration allowed for real-time synthetic test data generation into the CI/CD pipeline, enabling continuous end-to-end testing. The Jenkins pipeline starts and calls the GenRocket Engine using the GenRocket API, which then runs a test data Scenario to generate the data. The GenRocket Scenario specifies the type of patterned and conditioned test data needed and is based on a data model that represents the production data. Jenkins then consumes the test data and executes the appropriate test scripts. This process is seamless, easy to configure, and completely automated. Additionally, GenRocket Scenarios can be called via an automation framework like Selenium, and the GenRocket API can be used to modify GenRocket Scenarios in real-time for each test case. GenRocket can populate the required data sources in the format required by the test cases.
运营影响
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