Virtual Server Test Deployment for Code Validation
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Solution Overview
Problem
Traditional systems for managing virtual server resources risk widespread disruptions due to undiscovered errors in new code versions, leading to operational failures, increased costs, and user dissatisfaction when deployed without adequate testing under real user interactions.
Innovation Solution
A computer-implemented system for test deployment of computational code on virtual servers, which selects a test virtual server, uploads and initializes the code, receives performance measurements, calculates a test score, and stops the code if it exceeds set thresholds, ensuring minimal disruption to user experiences by comparing resource usage with baseline servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If computational code is mirrored across all virtual servers to standardize user experiences, then resource management is simplified and user experience consistency is improved, but the risk of widespread disruption increases when undiscovered errors in new code versions are deployed
Solution Approach 1:
The system segments the virtual server fleet into a control group (remainder servers) and a test group (single test server). This allows the new code to be tested on a isolated server before being mirrored to all servers, thus maintaining ease of management while reducing the risk of widespread disruption.
Solution Approach 2:
The system performs preliminary testing of the new computational code on a dedicated test server before deploying it to the production environment. This preliminary action allows undiscovered errors to be detected early, preventing them from causing widespread disruption across all servers.
2Adaptability or versatility
If new code versions are deployed to test virtual servers for validation, then the ability to test with real user interactions is improved, but the risk of deleterious impacts on user experiences increases if errors are not detected
Solution Approach 1:
The system applies local quality by creating a dedicated test server environment with specific characteristics (isolated from production traffic) that allows safe testing of new code. This local test environment has different quality attributes from production servers, enabling thorough testing without impacting user experiences.
Solution Approach 2:
The test server acts as an intermediary between code development and production deployment. It provides a controlled environment where new code can be validated with real user interactions while isolating potential failures from the production user base, thus preventing deleterious impacts.
3Measurement precision
If computational performance measurements are collected and analyzed to determine code deployment, then the precision of deployment decisions is improved, but the complexity of monitoring and evaluation increases
Solution Approach 1:
The system extracts the testing function from the production server environment by using a dedicated test server. This separation allows comprehensive performance measurements to be collected without the complexity of monitoring all production servers simultaneously, improving measurement precision while managing system complexity.
Data Source
AI summary
Methods and systems for test deployment of computational code on virtual servers are disclosed. In one embodiment, an exemplary method comprises receiving test computational code programmed to provide resources; selecting a test virtual server from a plurality of virtual servers; uploading the test computational code to the test virtual server; initializing the test computational code on the test virtual server; receiving computational performance measurements of the test virtual server and a remainder of the plurality of virtual servers; calculating a test score of the test virtual server based on the received computational performance measurements; and stopping the test computational code if the test score is outside a set range.


