Dynamic Cloud Resource Provisioning for Workload Balancing
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Solution Overview
Problem
Current Cloud computing environments lack efficient solutions for dynamically provisioning resources to balance real-time workloads, manage performance, and optimize costs, as existing technologies fail to address the need for flexible resource allocation and movement between Cloud and non-Cloud environments.
Innovation Solution
The solution involves a method and system for dynamically provisioning Cloud resources by identifying resource needs, evaluating the current state of Cloud providers, determining necessary actions, and dynamically allocating resources within and across Cloud environments based on rules, Service Level Agreements, and other criteria, enabling efficient workload balancing, cost optimization, and resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If static resource provisioning is used in Cloud computing environments, then resource allocation is simple and stable, but workload balancing is inefficient and over-provisioning occurs
Solution Approach 1:
The patent implements dynamic resource provisioning that automatically adjusts resource allocation based on real-time workload conditions. The system monitors workload metrics and dynamically provisions or de-provisions resources across multiple Cloud environments, transforming the static resource allocation model into a dynamic one that adapts to changing demands, thereby improving workload balancing efficiency while preventing over-provisioning.
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor workload conditions and resource utilization metrics. Based on this feedback, the resource provisioning system automatically adjusts resource allocation decisions, creating a closed-loop control system that optimizes resource utilization and prevents both over-provisioning and under-provisioning by responding to actual workload conditions.
2Adaptability or versatility
If resources are fixed within a single Cloud environment, then resource management is simple, but flexibility and cost-effectiveness are reduced
Solution Approach 1:
The patent creates a universal resource provisioning system that can allocate resources across multiple Cloud environments (different Cloud providers, public and private clouds) through a single unified platform. This multi-functional system handles diverse resource types and Cloud environments uniformly, increasing allocation flexibility while managing complexity through standardization and abstraction layers.
Solution Approach 2:
The system introduces an intermediary resource provisioning layer that sits between workload demands and physical Cloud resources. This intermediary abstracts the complexity of multi-Cloud management, providing a simplified interface for resource allocation while handling the complex coordination, monitoring, and provisioning operations across diverse Cloud environments in the background.
3Productivity
If manual resource provisioning is used, then control and monitoring are straightforward, but real-time workload balancing and performance optimization are insufficient
Solution Approach 1:
The patent implements a self-service resource provisioning system that automatically monitors workload conditions and provisions resources without manual intervention. The system autonomously detects workload demands, evaluates resource availability across multiple Cloud environments, and executes provisioning decisions based on predefined policies and real-time conditions, enabling real-time workload balancing while minimizing manual operational overhead.
Solution Approach 2:
The system performs preliminary actions by pre-configuring resource provisioning policies, thresholds, and parameters before workload demands arise. This advance preparation enables the automated system to quickly respond to real-time workload changes without requiring complex decision-making during peak loads, balancing automation capability with manageable control configurations.
Data Source
AI summary
The present invention provides a solution (e.g., rules, techniques, etc.) for enabling the dynamic provisioning (e.g., movement) of Cloud-based jobs and resources. Such provisioning may be within a Cloud infrastructure, from Cloud to Cloud, from non-Cloud to Cloud, and from Cloud to non-Cloud. Each movement scenario is assigned a specific technique based on rules, profiles, SLA and/or other such criteria and agreements. Such dynamic adjustments may be especially advantageous in order to balance real-time workload to avoid over-provisioning, to manage Cloud performance, to attain a more efficient or cost-effective execution environment, to off-load a Cloud or specific Cloud resources for maintenance/service, and the like.