Automated Deployment Templates for Enterprise Computing Systems
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Solution Overview
Problem
The deployment of enterprise-class computing systems, such as ERP or CRM systems, is often lengthy and expensive due to system complexity, lack of automation, and the need for manual configuration, making it prohibitive to test or add new systems efficiently.
Innovation Solution
The implementation of automated deployment templates that include preconfigured binaries, configuration data, and application data, which can be rapidly deployed via a web-based marketplace, using a deployment template tool that automates the process, reducing deployment time from weeks or months to minutes or hours.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual configuration and installation processes are used for enterprise-class computing systems, then system complexity and configurability are maintained, but deployment time increases from minutes to weeks or months
Solution Approach 1:
The patent applies preliminary action by pre-configuring software systems into deployment templates that contain all necessary configuration data, application data, and binaries prepared in advance. This allows the system to be deployed rapidly when needed, eliminating the need for manual configuration during deployment while maintaining full configurability through the pre-prepared templates.
Solution Approach 2:
The patent uses copying by creating deployment templates that are replicable units containing complete system configurations. These templates can be copied and deployed across multiple platforms consistently, maintaining system complexity and configurability while enabling rapid deployment through automated template instantiation rather than manual setup.
2Productivity
If automated deployment templates are used to rapidly deploy software systems, then deployment time is reduced to minutes or hours, but system complexity and configurability may be limited
Solution Approach 1:
The patent applies segmentation by dividing the software system into modular deployment templates that can be independently configured and deployed. Each template contains specific configuration data, application data, and binaries that can be selectively assembled to meet different deployment requirements, maintaining both speed and configurability.
Solution Approach 2:
The patent implements dynamics by making deployment templates adaptable and configurable through parameters that can be adjusted during deployment. The templates are not static but can be dynamically configured to match specific platform requirements and user needs, preserving system complexity and configurability while enabling rapid automated deployment.
3Reliability
If entire software systems are deployed as single units, then deployment consistency is maintained, but deployment time and resource requirements increase significantly
Solution Approach 1:
The patent applies segmentation by breaking down entire software systems into smaller, manageable deployment templates. These segmented templates can be deployed independently and in parallel, maintaining deployment consistency through standardized template structures while significantly reducing deployment time and resource requirements compared to deploying entire systems as single units.
Data Source
AI summary
Various embodiments include at least one of systems, methods, and software for automated deployment of a deployment template to computing systems. Some embodiments include receiving a selection of a deployment template from an entity via a network, identifying platforms of the entity compatible with the compatibility information, receiving a selection of a target platform, validating the selected deployment template for deployment to the selected platform, and deploying the selected deployment template to the selected platform. The validation of the selected deployment template for deployment to the selected platform may include transmitting a validation data request to an agent that executes on the selected platform to obtain validation data related to at least one validation rule, receiving validation data in response to the validation data request, and applying the at least one validation rule to the received validation data to determine validation success or failure.