The GenRocket platform was designed to scale Synthetic Test Data Automation across a global enterprise with hundreds to thousands of developers and testers needing test data for hundreds of applications in complex and interconnected environments. To maximize scalability, the GenRocket architecture is modular and adaptable and enables continuous feature enhancements and with new, innovative forms of intelligent automation.
GenRocket is the industry’s most advanced synthetic data platform with hundreds of intelligent data Generators, the most extensive library of output formatting Receivers, and the widest variety of test data project modeling methods for simulating any structured or unstructured data environment. The platform includes a multi-threaded, parallel processing architecture that maximizes speed, simplicity, and scalability.
The GenRocket architecture combines the modeling and design of test data in the cloud with distributed deployment and generation of synthetic data in the customer premise, and / or in a secure virtual test environments.
Test Data Projects are quickly modeled using 14 different tools and accurately reflect the data model of an underlying application, database or data feed. Test Data Projects can be organized, categorized, and versionsioned for use by different teams of developers & testers.
Test Data Cases are quickly designed in each Test Data Project to provide just about any test data including unit, component, integration, negative, permutation and load test data. All Test Data Cases are searchable through a centralized portal called G-Portal. Based on their permission level, any tester or developer can download Test Data Cases and integrate them into their test cases, ready for automated execution by the GenRocket Runtime.
The GenRocket Runtime can be launched by numerous automated methods so GenRocket can easily generate test data on-demand as part of any automation framework or CI/CD pipeline. The GenRocket Runtime and associated components can be deployed on individual tester and developer machines, on centrally located test automation servers, via a Maven Repository and even deployed via Containers.
Designed for Distributed Self Service
GenRocket is a distributed self-service platform that puts high-quality synthetic test data directly in the hands of developers and testers when they need it. That means any developer or tester anywhere in the world can browse G-Portal, select one or more Test Data Cases, integrate the Test Data Cases into their test cases, and generate the precise variety and volume of synthetic data they need on-demand. And if they don’t see a Test Data Case that meets their test case requirement, they can go to G-Portal to request a G-Case to be created by a small central team of trained Test Data Engineers.
With GenRocket, test data is instantly provisioned for any type of test once the rules for synthetic data generation are defined. To maximize the speed and efficiency of the data provisioning process, we developed a structured approach called The GenRocket Methodology. It provides a fast, repeatable, and predictable method for scaling the use of Synthetic Test Data Automation across organizations of any size.
The GenRocket Methodology
The GenRocket Methodology defines four key steps, or lifecycle stages, that go into developing Test Data Cases (what we call G-Cases) and managing their deployment across teams of software developers and testers. The following diagram illustrates these four important steps.
The GenRocket Methodology allows you to match the roles and expertise of your team members to the tasks they will perform in the GenRocket platform. The table below maps the four lifecycle stages with team member roles and the TDA (Test Data Automation) tasks they perform.
|Lifecycle Stage||Team Member Role||TDA Task|
|1. MODEL||Test Data Engineer||Model Test Data Projects for any application, database, or transaction set. Using GenRocket modeling tools, the data relationships are quickly established with referential integrity.|
|2. DESIGN||Test Data Engineer||Design Test Data Cases (G-Cases). GenRocket design tools are used to automate and accelerate the design of test data for any test case including test data for unit, integration, negative, edge case and load testing.|
|3. DEPLOY||Software Tester or Software Developer||Deploy Test Data Cases (G-Cases) into testing tools. Integrate G-Cases into test automation or software development tools to deliver on demand, real-time data for each test case.|
|4. MANAGE||Organization Admin or Test Data Engineer||Organize, categorize and version-control all Test Data Projects. Create and assign team permissions for access control to different Test Data Projects. Review activity and usage reports in G-Analytics.|
As you can see, the GenRocket Methodology is unlike the traditional TDM (Test Data Management) paradigm, or more recent Synthetic TDM variations of this traditional approach. Synthetic TDA (Test Data Automation) allows you to think differently about test data. In traditional TDM, DevOps teams are accustomed to the process of discovering, copying, masking, and subsetting production data. Often, the data must be reserved by team members for use with their specific test cases. And the process of searching for specific data values in a particular condition or “state” needed for specific test cases can be slow or impossible because production data does not contain all the data values needed for complete application testing such as unique data, negative data and all required permutations and combinations.
Test Data Automation: A Fast and Efficient Workflow
The following diagrams illustrate the GenRocket workflow for deploying Synthetic Test Data Automation for any application or database. The workflow starts with a small, well-trained group of GenRocket Test Data Engineers. This can be an informal team or a formalized Synthetic Test Data Center of Excellence (COE).
Let’s assume you’re developing an application that uses an Oracle database. During the MODEL stage, the Test Data Engineer will create a Test Data Project. There are 14 different ways to model a Test Data Project in GenRocket. For this example, let’s assume the Oracle database schema has been imported into GenRocket. The schema contains the metadata used to replicate the structure, attributes and relationships of the data tables needed for testing with full referential integrity.