Containers for Continuous Testing

Application development and testing has been revolutionised in the past several years with artifact and package repositories, enabling delivery of identical application environments in seconds. The use of Github, Jfrog and other repositories exploded with the introduction of Docker containers, and application development and testing now features containers and package repositories, as recognized best practices.

Enabling Truly Continuous Testing with Containerised Test Data Automation

The development and testing of databases, however, remains mired in outdated database refresh and delivery processes. Backups are restored to fixed database instances, that are typically shared between multiple developers or testers. Updating databases often requires a full business day. Problems in a production database environment are no faster. Once delivered, production debugging must be approached carefully to avoid making a mistake that could lead to the need for a refreshed environment.

Traditional test data provisioning is therefore no longer suitable for modern system development. Containerisation has created a situation in which testers must rapidly replace versioned components in their test environments, while retaining complex data relationships between shifting technologies. The deployed data must furthermore be diverse, compliant and compact, fulfilling all positive and negative scenarios in the smallest set of data possible. In a nutshell, continuous development and testing of databases requires test data solutions that provide versioned and interrelated data for intricate, ever updating technologies. Containerised Test Data Automation can help.

Curiosity was pleased to partner with Windocks, leaders in on demand delivery of test ready database environments, for a joint webinar on the 2^nd of February 2021, to present Development has moved on: Test data needs to catch up with containers, microservices and “the world of the API”. This webinar introduced database containers paired with virtualised databases, enabling on demand delivery of database environments for development and testing. Curiosity calls this Containerised Test Data Automation.

Containerised Test Data Automation?

Test data management needs to follow in the footsteps of development and embrace the world of containers and APIs, along with the pipelines which enable developers to deliver new software at speed. On 17^th of December 2020, Curiosity Software, creators of the Test Modeller, and Windocks, on demand database specialists, announced an integrated solution for delivering containerised test databases on demand. Integrating Test Data Automation with containerised, virtual data cloning, which in turn enabled containerised Test Data Automation:

Test Data Automation and Windocks: Containerised, automated test data.

The benefits of containerised Test Data Automation

Curiosity’s Test Data Automation, generates complete and compliant data on demand. This combines on-the-fly data masking and generation with rapid database cloning, producing virtual databases filled with rich test data. Fully versioned, virtual database cloning from Windocks then deploys the exact configuration of databases needed to test environments in seconds. This enables testers to test at the speed of system releases.

Windocks and Test Data Automation further provide intuitive web portals, allowing testers and developers to spin up the containerised data they need on demand. Adding data generation, masking and subsetting is as quick and simple as filling in fields in customisable web forms, spinning up the exact data sets required for rapid and rigorous testing. The rapid and re-usable test data jobs can further be exposed to CI/CD pipelines and test automation frameworks, resolving on-the-fly as tests are created and run.

Test Modeller not only enables containerised test data automation, it also has a range of other technologies that testers can take advantage of. Test Modeller analyses information from across the whole application development ecosystem, identifying and generating the tests that need running in-sprint. This enables testers to test continuously in three stages:

1. Inform: Test Modeller analyses data from all available sources, alerting test teams to changes that will impact the current release cycle.
2. Act: Test Modeller optimises test suites based on change and risk, identifying the tests that need running in-sprint.
3. Automate: Test Modeller automates the tasks needed to test in-sprint, including test generation, test data allocation, and test execution.

Its time testing embraces complete test automation, to match the speed of development. Containerised test data automation and other technologies powered by Test Modeller enables truly continuous testing.

The future of continuous testing

With containerised data, parallel test teams can quickly delete and restore the exact data configurations they need. Meanwhile, organisations retain full visibility and control, while enjoying the affordability of using virtual data instead of physical copies. Parallel test teams can finally leverage fresh containers, without slow data provisioning or complex configuration.

The future of continuous testing is automation. Test Data Automation enables rigorous testing that matches the speed of modern release cycles, through the introduction of containerised Test Data Automation.

Want to learn more about the integration between Test Data Automation and Windocks? Watch Development has moved on: Test data needs to catch up with containers, microservices and “The world of the API”. Now on demand.

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