Administrative Server Dynamically Builds Compute Node Sets
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Solution Overview
Problem
Users in cloud computing environments lack the knowledge to optimally select and efficiently form cloud groups of compute nodes that meet their workload needs, as they require understanding of the cloud's composition for high availability and performance.
Innovation Solution
A method where an administrative server dynamically builds a set of compute nodes to host user workloads by receiving workload definitions, determining virtual machine demands, and applying demand and placement constraints, along with license enforcement policies, to identify suitable compute nodes without requiring user knowledge of the cloud's composition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually assign compute nodes to form cloud groups, then users can select compute nodes based on their understanding of the cloud environment, but users require specialized knowledge of cloud composition and configuration to achieve optimal results
Solution Approach 1:
The patent introduces an automated intermediary system that mediates between user workload requirements and cloud infrastructure selection. This intermediary automatically analyzes workload definitions, determines virtual machine demands, evaluates compute node characteristics, and applies placement constraints to form optimal cloud groups, eliminating the need for users to possess specialized cloud composition knowledge while ensuring high availability requirements are met
Solution Approach 2:
The system enables self-service by allowing workloads to automatically select and configure their own compute nodes based on predefined constraints and requirements. The automated process evaluates compute node characteristics, determines optimal placements for high availability, and forms cloud groups without requiring manual user intervention or specialized knowledge of cloud infrastructure composition
2Reliability
If users manually configure cloud groups for high availability, then optimal compute node selection can be achieved, but the process becomes time-consuming and complex
Solution Approach 1:
The patent implements preliminary action by pre-defining placement constraints and compute node characteristics before workload deployment. The system pre-processes compute node information, evaluates characteristics such as geographic distribution and failure independence, and has automated rules ready to enforce high availability requirements, enabling rapid cloud group formation without time-consuming manual configuration
Solution Approach 2:
The automated system performs self-service by automatically evaluating compute node characteristics, determining optimal placements for high availability, and forming cloud groups based on workload requirements. This eliminates the time-consuming manual process of selecting and configuring compute nodes while ensuring high availability requirements are met through automated enforcement of placement constraints
3Ease of operation
If automated systems form cloud groups, then user knowledge requirements are reduced, but the system must complexly evaluate workload definitions, virtual machine demands, and placement constraints
Solution Approach 1:
The patent applies segmentation by dividing the automated cloud group formation process into distinct modular components: workload definition processing, virtual machine demand determination, compute node characteristic evaluation, placement constraint application, and cloud group formation. Each module handles a specific aspect of the process independently, managing system complexity through functional decomposition while providing ease of operation through automated integration of these segments
Data Source
AI summary
A method, system and computer program product for dynamically building a set of compute nodes to host a user's workload. An administrative server receives workload definitions that include the types of workloads that are to be run in a cloud group as well as a number of instances of each workload the cloud group should support. These workload definitions are used to determine the virtual machine demands that the cloud group will place on the cloud environment. The administrative server further receives the demand constraints, placement constraints and license enforcement policies. The administrative server identifies a set of compute nodes to host the user's workload based on the virtual machines demands, the demand constraints, the placement constraints and the license enforcement policies. In this manner, a set of compute nodes is dynamically built for consideration in forming a cloud group without the user requiring knowledge of the cloud's composition.