Master Image Workload Deployment in Heterogeneous Cloud
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Solution Overview
Problem
In heterogeneous cloud computing environments, deploying workloads across multiple hosts and monitors with different configurations is challenging due to compatibility issues, requiring extensive and costly maintenance of multiple image files to accommodate various permutations of hardware, software, and cloud technologies.
Innovation Solution
A method using a master image with associated subimages, managed by an orchestration engine, which determines the appropriate host and monitor type to deploy workloads, allowing for simultaneous deployment on multiple monitors with different configurations using a single master image, and automatic transfer between incompatible types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple image files are maintained to accommodate various permutations of hardware, software, and cloud technologies, then compatibility with different host and monitor configurations is improved, but maintenance complexity and costs increase
Solution Approach 1:
The patent implements a universal master image that can be deployed across multiple heterogeneous hosts and monitors. The master image contains a workload that can dynamically adapt to different configurations, eliminating the need to maintain separate image files for each hardware/software permutation. This single master image serves multiple functions across diverse environments.
Solution Approach 2:
The system dynamically changes parameters such as host type, monitor type, and workload configuration based on the target environment. The orchestration engine modifies deployment parameters automatically, allowing the same master image to be adapted to different hosts and monitors without requiring multiple specialized image files.
2Adaptability or versatility
If multiple image files are maintained for different configurations, then deployment compatibility is improved, but resource consumption and storage requirements increase
Solution Approach 1:
The patent merges multiple configuration-specific image files into a single master image. Instead of storing separate images for each host-monitor permutation, the system consolidates all necessary configurations into one unified image file, significantly reducing storage requirements while maintaining deployment compatibility across heterogeneous environments.
Solution Approach 2:
The master image is designed to be universal and multi-functional, capable of deploying workloads on any supported host and monitor configuration. This eliminates the need to store multiple specialized image files, as the single master image can adapt to various environments through dynamic parameter adjustment rather than through multiple stored variants.
3Manufacturing precision
If manual selection and configuration of image files for each deployment is performed, then deployment accuracy is improved, but deployment time and operational complexity increase
Solution Approach 1:
The system implements self-service through automated orchestration. The orchestration engine automatically selects the appropriate master image and configures deployment parameters based on the target host and monitor characteristics, eliminating the need for manual image selection and configuration. This automation maintains deployment accuracy while significantly reducing operational time and complexity.
Solution Approach 2:
The orchestration engine uses feedback from environment detection to automatically adjust deployment configurations. By monitoring host and monitor types and comparing them against compatibility criteria, the system automatically selects and configures the appropriate master image without manual intervention, ensuring accurate deployments while minimizing time loss.
Data Source
AI summary
A method for deploying workloads in a heterogenous computing environment having multiple hosts of multiple different types and/or multiple monitors of multiple different types is disclosed. The method includes selecting a master image for deployment of a workload, wherein multiple subimages are associated with the master image, and the subimages correspond to at least some of the different types of hosts and/or the different types of monitors such that the master image is usable to deploy the workload on at least one of the hosts. The method also includes determining a host on which to deploy the workload using the master image; determining a monitor of the host to manage the workload; determining a monitor type of the monitor; determining, by an orchestration engine and based on the monitor type, a subimage that supports the first monitor; and cloning the associated resources to the host to initiate the workload thereon.