Integrating Capacity Planning and Workload Management
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Solution Overview
Problem
Current computer systems lack integration between capacity planning and workload management systems, leading to inefficiencies and inaccurate resource allocation due to the absence of real-time workload management data in capacity planning processes.
Innovation Solution
An integration architecture that couples workload management and capacity planning functions, enabling the capacity planning system to receive and factor in projected resource demands from the workload management system, using simulation and modeling modules to determine optimal resource allocations and present them for user review.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If capacity planning and workload management systems operate independently, then each system can function with simpler architecture, but resource allocation accuracy and system efficiency deteriorate due to lack of integration
Solution Approach 1:
The patent merges capacity planning and workload management systems into a unified integrated system. The capacity planning module and workload management module communicate through defined interfaces, sharing resource data and allocation decisions. This integration enables the system to achieve accurate resource allocation by combining capacity planning insights with real-time workload management, while the modular architecture manages complexity through standardized communication protocols and shared data structures.
2Productivity
If capacity planning uses historical data only, then the planning process is simpler and faster, but resource allocation becomes inefficient and outdated due to lack of real-time workload information
Solution Approach 1:
The integrated system implements feedback loops where the workload management module continuously monitors actual resource usage and performance metrics, then feeds this real-time data back to the capacity planning module. This feedback mechanism ensures capacity planning is based on both historical trends and current workload conditions, improving resource utilization efficiency while maintaining timely synchronization through continuous data exchange rather than periodic updates.
3Reliability
If the system integrates real-time data exchange between capacity planning and workload management, then resource allocation accuracy improves, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent segments the integrated system into distinct functional modules: a capacity planning module, a workload management module, and communication interfaces between them. Each module maintains its own data structures and processing logic, reducing overall system complexity. The segmentation allows real-time data exchange through well-defined interfaces while preserving the reliability of allocation decisions, as each module can be developed, tested, and maintained independently.
4Loss of energy
If unused hardware resources are fully utilized through integration, then resource efficiency improves, but the risk of resource contention and performance degradation increases
Solution Approach 1:
The integrated system dynamically adjusts resource allocation based on real-time workload conditions and capacity planning recommendations. Rather than statically assigning unused resources, the system continuously monitors resource utilization and performance metrics, dynamically reassigning resources as needed. This dynamic approach reduces resource waste by utilizing previously idle hardware while maintaining system performance stability through adaptive load balancing and priority-based allocation that prevents resource contention.
Data Source
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AI summary
A system for integrating resource capacity planning and workload management, implemented as programming on a suitable computing device, includes a simulation module that receives data related to execution of the workloads, resource types, numbers, and capacities, and generates one or more possible resource configuration options; a modeling module that receives the resource configuration options and determines, based on one or more specified criteria, one or more projected resource allocations among the workloads; and a communications module that receives the projected resource allocations and presents the projected resource allocations for review by a user.