Scalable IT Deployment Platform for Cloud Autoscaling and Cost Modeling
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Solution Overview
Problem
Current IT deployment on public or private clouds is complex, time-consuming, and costly due to human error, inefficiencies in resource allocation, and difficulty in estimating true costs, especially for customized desktop environments, and lacks proactive performance monitoring.
Innovation Solution
A scalable, standardized IT deployment environment that automates deployment across clouds, includes an autoscaling mechanism for resource management, a cost calculation system, and proactive testing for productivity and efficiency, reducing human intervention and improving resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual deployment processes are used to customize IT environments for each user, then adaptability to user needs is improved, but device complexity and time consumption increase significantly
Solution Approach 1:
The deployment process is segmented into standardized templates that can be individually configured and combined. Each template represents a modular unit (e.g., desktop environment, application suite, security policy) that can be selected and customized independently, reducing overall complexity while maintaining adaptability.
Solution Approach 2:
Common IT environment configurations are pre-configured into reusable templates before deployment. These templates contain pre-defined settings, applications, and policies that can be automatically applied to multiple users, eliminating the need for manual customization while preserving user-specific adaptability through template selection and parameter adjustment.
2Reliability
If resources are allocated for peak usage periods, then service reliability during high demand is improved, but resource utilization efficiency deteriorates due to idle capacity during low usage
Solution Approach 1:
The system implements dynamic resource allocation that automatically adjusts computing resources based on real-time usage patterns. During peak periods, resources are scaled up to maintain service reliability; during off-peak periods, resources are scaled down to eliminate waste, while user desktops are automatically suspended and restored as needed.
Solution Approach 2:
User desktop instances are discarded (suspended) during off-peak periods when not in use and recovered (restored) when users need access. This allows the system to reuse the same physical infrastructure for multiple users at different times, improving overall resource utilization while maintaining service availability when needed.
3Productivity
If identical desktop templates are used across users, then resource allocation efficiency is improved, but adaptability to individual user needs deteriorates
Solution Approach 1:
The system applies local quality by allowing global standardization through templates while enabling local customization for individual users. Each user's desktop can be configured with template-based standard components plus user-specific modifications, achieving both efficiency through reuse and adaptability through localized personalization.
Solution Approach 2:
The template system provides universality by creating multi-functional desktop configurations that can serve multiple user needs through selective activation and parameter adjustment. A single template can be adapted to serve different user roles and requirements without requiring completely separate configurations, maintaining both efficiency and adaptability.
4Difficulty of detecting and measuring
If comprehensive documentation and manual maintenance are performed for each deployment, then troubleshooting accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system implements automated feedback mechanisms that track deployment configurations, resource allocation decisions, and performance metrics. This automated documentation and monitoring provides accurate troubleshooting information without manual intervention, reducing maintenance time while preserving diagnostic accuracy through systematic data collection and analysis.
Data Source
AI summary
The present disclosure provides a scalable, standardized IT deployment environment that allows for deployment to any public or private cloud automatically, and that is resizable such that the individual resources can be released (“turned off”) when not needed and powered on when use is expected. Additionally, the present disclosure provides a cost calculation system for better understanding the costs of the IT environment as early as the pre-provisioning stage. The present disclosure also provides a system for proactively testing productivity and efficiency within the IT environment, the results of which can be fed back into the autoscaling mechanism.