Pre-configured Cloud Resource Pool for Fast Deployment
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Solution Overview
Problem
Current methods for large-scale cloud deployment are time-consuming, resource-intensive, and prone to errors, leading to slow deployment processes and potential service outages, with existing tools failing to efficiently manage and maintain cloud environments.
Innovation Solution
A method that utilizes a resource pool with pre-assembled and pre-configured resources, allowing for dynamic allocation based on real-time data, enabling efficient deployment and maintenance by decoupling installation and configuration, and allowing resources to self-upgrade, thereby reducing errors and service outages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional cloud deployment methods are used, then deployment can be completed, but the process is time-consuming and resource-intensive
Solution Approach 1:
The patent pre-assembles and pre-configures cloud resources in a resource pool before deployment is needed. This preliminary preparation allows resources to be readily available when deployment requests occur, significantly reducing deployment time without sacrificing completeness or quality of configuration.
Solution Approach 2:
The patent divides cloud resources into discrete, pre-configured units in a resource pool that can be independently selected and deployed. This segmentation allows for efficient resource allocation and faster deployment by enabling selective assembly of pre-prepared resource components rather than configuring everything from scratch.
2Reliability
If traditional deployment methods are used, then resources can be allocated, but the process is prone to errors and service outages
Solution Approach 1:
Resources are pre-configured and validated in the resource pool before actual deployment occurs. This advance preparation allows configurations to be tested and verified beforehand, reducing the likelihood of errors during deployment and minimizing service outages caused by configuration issues.
Solution Approach 2:
The system automatically manages resource allocation and deployment from the pre-configured resource pool, reducing manual intervention and associated human errors. The automated processes ensure consistent application of configurations and reduce the probability of deployment mistakes.
3Productivity
If a resource pool with pre-configured resources is used, then deployment efficiency is improved, but system complexity increases
Solution Approach 1:
The resource pool serves multiple functions: it stores pre-configured resources, manages resource metadata, handles allocation decisions, and supports deployment operations. This multi-functional approach consolidates what could be separate complex systems into a unified resource pool management framework, improving efficiency without proportionally increasing overall system complexity.
Data Source
AI summary
A deployment specification for implementing a requested cloud service is received by a server. A resource pool is queried by the server for available resources required by the deployment specifications. The resource pool includes a plurality of pre-configured resources for implementing one or more cloud services. A first resource required by the deployment specification is determined to be available within the resource pool. First resource metadata associated with the first resource is requested from a database. The resource metadata includes a resource identifier and a resource type of the first resource. The resource metadata associated with the first resource is received from the database. The first resource is deployed from the resource pool according to the deployment specification to implement the requested cloud service.