Software Container Update Deployment with Idle Resource Testing
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Solution Overview
Problem
Modern computing systems face challenges in replicating live environment conditions for software testing and deploying software updates efficiently, often requiring full package downloads and causing significant downtime.
Innovation Solution
The system employs software containers to deploy and test updates, utilizing idle resources for testing and installing only necessary updates, with a deployment service managing resource allocation and switching between active and background containers to minimize downtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If software updates are deployed by downloading and installing entire software packages, then complete software updates can be deployed, but bandwidth is wasted and deployment time increases
Solution Approach 1:
The patent extracts only the necessary components from the complete software package for deployment. The container image includes only the specific software components that need to be updated, rather than deploying the entire software package. This extraction principle reduces bandwidth consumption while ensuring complete deployment of necessary updates.
Solution Approach 2:
The software package is segmented into discrete container images that can be deployed independently. Each container image represents a specific software component or service, allowing selective deployment of only the necessary segments rather than the complete package, thereby reducing bandwidth usage.
2Reliability
If software updates are deployed by downloading and installing entire software packages, then complete software updates can be deployed, but deployment time increases
Solution Approach 1:
The patent extracts only the necessary components from the complete software package for deployment. The container image includes only the specific software components that need to be updated, rather than deploying the entire software package. This extraction principle reduces deployment time while ensuring complete deployment of necessary updates.
Solution Approach 2:
Container images are prepared and validated in advance before deployment. The imaging process creates ready-to-deploy packages that can be quickly transferred and installed, eliminating the need for on-site assembly or configuration during deployment, thus reducing overall deployment time.
3Measurement precision
If testing environment replicates live environment conditions, then testing accuracy improves, but resource requirements and complexity increase
Solution Approach 1:
The patent uses container images that are identical copies of the production environment's software packages. These images are created from the same build process and contain the exact same components, ensuring testing accuracy without requiring a complex replicated infrastructure. The copying principle maintains fidelity while simplifying the testing setup.
Solution Approach 2:
The container image serves multiple functions: it is used both for testing and for production deployment. This universal artifact eliminates the need for separate testing and production environments, reducing overall system complexity while maintaining testing accuracy through faithful replication of production conditions.
4Reliability
If entire software packages are downloaded for updates, then all necessary components are available, but bandwidth is consumed unnecessarily
Solution Approach 1:
The patent extracts only the necessary components from the complete software package for deployment. The container image includes only the specific software components that need to be updated, rather than deploying the entire software package. This extraction principle reduces data transfer volume while ensuring complete deployment of necessary updates.
Solution Approach 2:
The container image is customized to include only the specific components needed for the particular deployment scenario. Each image has local quality tailored to its purpose, containing only the relevant software components rather than a universal complete package, thereby minimizing data transfer while ensuring completeness of necessary updates.
Data Source
AI summary
A system and method for software deployment, where the system and method include, at a deployment service, obtaining a software package and determining that a client device is ready to receive at least a portion of the software package. If the client device is ready, providing at least the portion of the software package to the client device, launching at least the provided portion of the software package as set of instructions executing in a test container, and performing a set of tests on the executing set of instructions in the test container. Based at least in part on results of performing the set of tests, determining whether to cause at least the provided portion of the software package to execute in an active container on the client device.