Cloud Management System for Application Deployment
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Solution Overview
Problem
Traditional operation and maintenance modes of large-scale software systems, such as BSS/OSS, face high costs, low resource utilization, long service launch cycles, inefficient maintenance, and environmental concerns, necessitating a more efficient migration to cloud platforms without requiring software re-architecture.
Innovation Solution
A cloud infrastructure-based management system comprising an application scheduling deployment engine, deployment plug-in, and monitoring plug-in that obtains and responds to performance and load state data to generate deployment instructions for automatic configuration and monitoring of application instances, allowing for dynamic resource allocation and deployment adjustments without re-architecting existing software systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional silo system deployment mode is used, then software system can be deployed and maintained, but resource utilization rate is low and purchasing cost is high
Solution Approach 1:
The patent merges multiple application instances that were previously deployed on separate hardware resources into a shared cloud platform environment. Multiple applications share common infrastructure resources including compute, storage, and networking capabilities, thereby increasing resource utilization rates while reducing the total quantity of hardware resources that need to be purchased and maintained.
Solution Approach 2:
The cloud platform provides universal infrastructure that can serve multiple different applications simultaneously. The shared resources and services on the platform are designed to be multi-functional, supporting various application workloads with different requirements, thus improving resource utilization while avoiding the need to purchase dedicated resources for each application.
2Extent of automation
If MapReduce architecture is used for real time scheduling, then scheduling capability is improved, but software re-architecture and development are required
Solution Approach 1:
The patent introduces a cloud platform as an intermediary layer between the existing application systems and the underlying hardware infrastructure. This intermediary provides automated scheduling and resource management capabilities without requiring modifications to the application code or system architecture. The platform handles real-time scheduling requests through its own management mechanisms while presenting a standard interface to applications.
Solution Approach 2:
The patent segments the system into distinct layers: the existing application layer remains unchanged, while the cloud platform layer provides scheduling and resource management functions. This segmentation allows automated scheduling capabilities to be introduced without affecting or requiring re-architecture of the application software, maintaining system modularity and reducing complexity.
3Reliability
If service configuration is based on peak value, then service availability is ensured, but resource utilization rate cannot be fully optimized
Solution Approach 1:
The patent implements dynamic resource allocation on the cloud platform that can automatically adjust resource provisioning based on actual service demand rather than static peak-value configuration. The platform monitors service performance and resource utilization in real-time, dynamically allocating resources to maintain service availability while optimizing utilization rates by scaling resources up or down according to actual needs.
Solution Approach 2:
The cloud platform incorporates feedback mechanisms that continuously monitor service performance metrics and resource utilization levels. Based on this feedback, the platform automatically adjusts resource allocation to maintain service availability thresholds while optimizing resource utilization. The feedback loop enables the system to respond to changing conditions and avoid both over-provisioning and under-provisioning of resources.
Data Source
AI summary
The present invention discloses a cloud infrastructure-based management system and method for maintenance deployment of an application system. A cloud infrastructure-based method for maintenance and deployment of an application system, comprising: obtaining a scheduling deployment policy of an application; obtaining performance of an application instance or task processing state data of the application instance; and performing application scheduling deployment according to the scheduling deployment policy of the application and the performance of the application instance or the task processing state data of the application instance, generating a deployment instruction for the application instance, and completing deployment configuration of the application instance, wherein the deployment instruction comprises an application attribute and a range of attribute values. In this way, the present invention support automatic deployment of an application system, avoiding software re-architecture needed for the application system's migration deployment from a traditional system to a cloud platform.