Multi-Tier Cloud Application Stack Update Mechanism
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Solution Overview
Problem
Updating a multi-tier application stack in a cloud network environment is burdensome due to large file sizes and the need for significant network resources and prolonged server downtime, which can disrupt services and complicate re-establishing dependencies.
Innovation Solution
A system that periodically checks a central server for updates, downloads and applies them to a new instance of the application stack, compares metadata between the current and new instances to identify differences, and serializes these differences for installation on the current instance, minimizing downtime and network burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the application stack is updated by overwriting the application image, then the update is applied, but the network resources are burdened and service interruption occurs
Solution Approach 1:
The patent segments the update process into multiple phases: creating a new instance, applying updates to the new instance, comparing metadata between old and new instances, and selectively migrating only the differences. This segmentation allows the system to avoid overwriting the entire application image, thereby reducing network resource consumption while maintaining service continuity through the new instance.
Solution Approach 2:
The patent performs preliminary actions by creating a new application instance before the old one is terminated. The new instance is fully updated and tested in advance, allowing the system to compare metadata and selectively migrate only the necessary changes. This preliminary action ensures service continuity while minimizing the network burden of transferring large application images.
2Ease of manufacture
If the application image is overwritten to apply updates, then the update is installed, but dependencies are destroyed and must be reestablished
Solution Approach 1:
The patent creates a copy (new instance) of the application rather than modifying the original. This new instance is updated with the latest version and dependencies. By comparing metadata between the old and new instances, the system identifies only the necessary changes to copy, preserving dependency relationships while achieving the update. This eliminates the need to manually reestablish dependencies.
Solution Approach 2:
The patent implements a feedback mechanism through metadata comparison between the old application instance and the new updated instance. This comparison provides information about which specific components and dependencies need to be migrated, allowing the system to selectively copy only the necessary elements. This feedback-driven approach simplifies the update process while maintaining dependency integrity.
3Reliability
If vendors are hired to update and test software components, then bugs are fixed and functionality is added, but the process is burdensome and requires prolonged server downtime
Solution Approach 1:
The patent performs update installation and metadata comparison in advance by creating a new instance with all updates applied. The metadata comparison identifies necessary changes before the old instance is terminated. This preliminary action allows the system to prepare the updated version without interrupting service, thereby reducing server downtime while maintaining high-quality bug fixes and functionality additions.
Solution Approach 2:
The patent uses the new instance as a template or model for the updated application. By copying the structure and metadata of the new instance to the old one (selectively migrating differences), the system ensures that all bug fixes and functionality additions are preserved. This copying approach maintains high reliability while minimizing the time the system needs to be taken offline.
4Adaptability or versatility
If complex application stacks are updated, then new features are added, but the file size is large (e.g., 1 terabyte) and network resources are heavily consumed
Solution Approach 1:
The patent extracts only the necessary differences between the old and new application instances through metadata comparison. Instead of transferring the entire large application image (e.g., 1 terabyte), the system identifies and extracts only the specific components, configurations, and dependencies that need to be updated. This extraction approach maintains full feature functionality while dramatically reducing network bandwidth consumption.
Solution Approach 2:
The patent segments the large application update into smaller, manageable components by comparing metadata and identifying individual elements that need to be migrated. This segmentation allows the system to transfer only the necessary portions of the update rather than the entire application stack, reducing network resource consumption while preserving all new features and functionality.
Data Source
AI summary
The present disclosure relates to automatically and periodically updating a multi-tier application stack in a cloud environment. More particularly, the present disclosure relates to systems and methods that access a central server to determine if new updates have been released, and when new updates have been released, automatically apply the new updates to an application environment with minimal network burden and service interruption.