SaaS Component Parity Checks for Replacement Behavior Validation
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Solution Overview
Problem
In software-as-a-service (SaaS) systems, validating the equivalent behavior of replacement components is challenging due to the impracticality of testing all permutations of customer customizations and configurations in a test environment, leading to potential unexpected changes and negative user experiences.
Innovation Solution
A system and method that utilizes a live production environment to validate new components by performing parity checks between existing and new components, capturing discrepancies in behavior without duplicating the SaaS system, thereby ensuring minimal impact on users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If QA testing is performed in a test environment to validate replacement components, then behavior equivalence can be checked, but the testing cannot cover all permutations of customer customizations and configurations leading to gaps in validation
Solution Approach 1:
The system performs preliminary parity checks by capturing request data and result data from both the first component and second component before the replacement is fully deployed. This advance validation in the live production environment allows comparison of behaviors across multiple customer instances with different customizations, configurations, and data patterns before the replacement component becomes the primary component, ensuring comprehensive coverage without needing to test all permutations in advance.
Solution Approach 2:
Instead of duplicating the SaaS system to create a separate test environment (the conventional approach), the patent inverts the approach by utilizing the live production environment itself for validation. The system captures data from actual customer instances in production and performs parity checks there, turning the production environment into a validation platform rather than treating it as too risky for testing.
2Reliability
If a separate test environment is created to validate replacement components, then testing can be performed, but it duplicates the SaaS system and requires maintaining extensive test cases increasing complexity and cost
Solution Approach 1:
The live production environment serves multiple functions: it is both the operational environment for serving customer requests and the validation environment for testing replacement components. The system simultaneously processes customer requests and captures data for parity checks, eliminating the need for a separate dedicated test environment and reducing infrastructure complexity while maintaining comprehensive validation capability.
Solution Approach 2:
Instead of creating a full duplicate of the SaaS system for testing purposes, the system creates a virtual copy by capturing request data and result data from the live environment. This data copying approach allows validation without physical duplication of infrastructure, reducing complexity while enabling comprehensive testing through data analysis and parity checks.
Data Source
AI summary
A system to validate behavior of a replacement component is disclosed. The system obtains first result data, the first result data being generated by performing a first request at a first component of a production environment. The system performs second request at a second component of the production environment to generate second result data. The system performs a parity check between the first result data and the second result data to determine an equivalence in behavior between the first request at the first component and the second request at the second component. The system generates discrepancy information indicating the equivalence in behavior between the first request at the first component and the second request at the second component based on the parity check. The system performs a third action based on the discrepancy information including storing the discrepancy information.