Support Software Update Supervision With Dynamic Non-Regression Testing
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Solution Overview
Problem
Existing methods for monitoring software updates in cloud computing environments with high frequency and strong security constraints are inadequate, failing to ensure non-regression and security during frequent updates.
Innovation Solution
A method and system for monitoring software updates in a service delivery infrastructure that includes dynamically updating non-regression test repositories, executing tests in a test environment analogous to the infrastructure, and approving updates only after successful completion of all associated non-regression tests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If regular updates are provided at high frequency in cloud computing infrastructure, then service functionality and security improvements are enhanced, but the risk of security breaches and functional regressions increases
Solution Approach 1:
The patent implements preliminary action by executing non-regression tests in a test environment before deploying updates to the production infrastructure. The system receives updates, determines their type, identifies impacted components, and runs comprehensive tests including security checks and non-regression tests on a copy of the infrastructure before approval. This preliminary validation ensures that updates do not introduce security breaches or functional regressions, resolving the contradiction between maintaining high security and implementing frequent updates.
2Reliability
If comprehensive non-regression tests are implemented for each update, then functional stability and security are ensured, but the time required for update deployment increases
Solution Approach 1:
The patent applies segmentation by dividing the testing process into distinct segments based on update types and impacted components. The system determines the type of each deployment command (e.g., kernel update, application update, configuration change) and identifies specific software components affected. Tests are then segmented and executed only for the relevant components rather than the entire infrastructure, reducing overall testing time while maintaining comprehensive coverage of affected areas.
Solution Approach 2:
The system implements dynamics by adaptively adjusting the testing scope and depth based on the characteristics of each update. The test repository is dynamically updated with new tests and modified existing tests based on the deployment command type and impacted components. This dynamic approach ensures that comprehensive tests are run when necessary while avoiding redundant testing for minor updates, thereby maintaining functional stability without excessive deployment time.
3Measurement precision
If a test environment analogous to the service delivery infrastructure is used, then accurate validation of updates is achieved, but the complexity of the monitoring system increases
Solution Approach 1:
The patent applies the copying principle by creating a test environment that is a copy or replica of the service delivery infrastructure. This test environment mirrors the production infrastructure's architecture, components, and configurations, allowing accurate validation of updates without affecting the actual service delivery. The system receives deployment commands, creates appropriate test environments, executes tests on these copies, and only approves updates after successful validation, thereby achieving high measurement precision while managing complexity through isolated testing.
Data Source
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AI summary
The invention relates to a method and system for monitoring updates to support software in a service delivery infrastructure. The method comprises, for a current deployment command, determining the command type and at least one software component impacted by the update, and, for each impacted software component, dynamically updating a current repository of non-regression tests (L7) to be performed and a repository (L6, Test-List-T(CDc)) of non-regression tests associated with said command type. The deployment is executed in a test environment, and then the non-regression tests of the current repository (L7) are executed. The deployment is approved upon successful completion of all non-regression tests of said current repository and all tests of the non-regression test repository associated with said deployment command type.