Smart Deployment Tool for Cloud Application Testing
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Solution Overview
Problem
The existing Continuous Integration/Continuous Deployment (CI/CD) pipeline process is time-consuming and redundant, requiring multiple deployments and lengthy wait times for developers to test and deploy code in Development (Dev) and User Acceptance Testing (UAT) environments, wasting precious time and reducing productivity in the software development lifecycle.
Innovation Solution
A method and system for optimizing application deployment in cloud-based environments by allowing direct deployment of user artifacts files onto a test environment, performing testing events, and transmitting successful files for pipeline deployment, thereby bypassing redundant CI/CD stages for each iteration, using a Smart Deployment Tool that processes executable and configuration files for efficient deployment and testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If CI/CD pipelines are used to deploy code to Dev and UAT environments, then code can be built, tested and deployed automatically, but the deployment process becomes time-consuming and redundant for multiple builds
Solution Approach 1:
The patent extracts the essential deployment functionality from the full CI/CD pipeline by creating a simplified direct deployment mechanism. Instead of running complete pipelines with all validation and scanning steps for every build, the system allows developers to directly deploy artifact files to test environments, extracting only the core deployment action while maintaining automation through the simplified pipeline.
Solution Approach 2:
The deployment process is segmented into different paths: the full CI/CD pipeline for initial code integration and validation, and a simplified direct deployment path for subsequent builds. This segmentation allows the system to use the lightweight direct deployment approach for iterative builds while reserving the heavy pipeline execution for necessary validation stages, thereby reducing overall deployment time.
2Reliability
If multiple CI/CD pipeline iterations are performed for each build, then comprehensive testing and validation can be performed, but redundant pipeline steps waste developer time
Solution Approach 1:
The system applies partial action by executing only the necessary pipeline steps for each deployment scenario. For iterative builds with small changes, the system performs partial validation rather than complete pipeline execution. The direct deployment mechanism allows developers to skip redundant pipeline iterations while still maintaining essential testing and validation through targeted execution of critical pipeline stages.
Solution Approach 2:
The simplified deployment pipeline incorporates feedback mechanisms that allow developers to provide input on which pipeline stages are necessary for their specific builds. This feedback loop enables the system to dynamically adjust the deployment process, executing only the validation steps needed for the current build while skipping redundant steps, thereby maintaining reliability without wasting developer time.
3Adaptability or versatility
If developers perform multiple builds to get code right, then functionality can be refined, but waiting time for deployment increases
Solution Approach 1:
The deployment system becomes dynamic by adapting its behavior based on the build context. For iterative builds with small changes, the system automatically selects the fast direct deployment path. For major builds requiring comprehensive validation, the system switches to the full CI/CD pipeline. This dynamic adaptation allows developers to refine functionality through multiple builds without experiencing consistent long waiting times, as the system optimizes the deployment process based on the specific build characteristics.
Data Source
AI summary
A solution for optimizing the deployment of applications in a cloud-based environment is provided. A method for optimizing the deployment of applications in a cloud-based environment is disclosed. The method is implemented by at least one processor. The method includes receiving at least one user artifacts file for direct deployment on a test environment. Next, the method includes deploying the at least one user artifacts file onto the test environment. Next, the method includes performing a set of testing events on artifacts included in the at least one user artifacts file. Thereafter, the method includes transmitting the at least one user artifacts file for pipeline deployment based on a successful result of the testing events.