Hybrid Cloud Resource Scheduling via Scoring and Deployment

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Solution Overview

Problem

Managing workload deployment between enterprise datacenter resources and cloud resources in a hybrid cloud environment is challenging due to complex pricing, sunk costs, and restrictions on workload deployment, making it difficult for administrators to optimize resource scheduling.

Innovation Solution

A method for hybrid cloud resource scheduling that compares constraints and budget against datacenter metrics and admission prices to generate a candidate set of datacenters, scores them, and deploys virtual computing instances to a target datacenter that satisfies a threshold score, using a resource scheduler to optimize placement across enterprise and cloud resources.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If cloud resources are purchased to extend enterprise datacenter capacity, then resource availability increases, but cost complexity increases due to complex pricing models

Engineering Contradiction:

Improveresource availabilityVSAvoidcost complexity

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The patent introduces a resource scheduler as an intermediary component that manages the complexity of cloud resource pricing and workload deployment. This scheduler evaluates multiple factors including pricing models, workload constraints, and resource availability to automatically make deployment decisions, thereby shielding administrators from the complexity of cloud pricing while optimizing resource utilization across hybrid cloud environments.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If enterprise datacenter resources are used to accommodate peak demand, then workload deployment flexibility is maintained, but capital expenses increase

Engineering Contradiction:

Improveworkload deployment flexibilityVSAvoidcapital expenses

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The patent implements dynamic resource scheduling that adapts to changing workload demands and pricing conditions in real-time. The system can dynamically shift workloads between enterprise datacenter resources and cloud resources based on current conditions, allowing the infrastructure to be flexible and responsive without requiring over-provisioning of expensive enterprise resources for peak demand scenarios.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes operational parameters such as resource allocation, pricing thresholds, and deployment criteria based on real-time conditions. By adjusting these parameters dynamically, the system optimizes the balance between using enterprise resources and cloud resources, reducing capital expenses while maintaining deployment flexibility when needed.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If workload deployment restrictions are enforced for security or compliance reasons, then security compliance is ensured, but resource scheduling complexity increases

Engineering Contradiction:

Improvesecurity complianceVSAvoidresource scheduling complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent applies preliminary actions by pre-configuring deployment constraints and security policies within the resource scheduler. These constraints are established in advance based on security and compliance requirements, allowing the scheduler to automatically filter and evaluate candidate resources against these pre-set criteria without requiring complex real-time decision-making or manual intervention during deployment.

Inventive Principle:

Principle #10Preliminary action

4Ease of operation

If administrators manually manage workload deployment between enterprise and cloud resources, then control over resource placement is maintained, but management time and effort increase

Engineering Contradiction:

Improvecontrol over resource placementVSAvoidmanagement time

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The patent implements self-service automation where the resource scheduler autonomously performs workload deployment decisions based on predefined policies, constraints, and real-time conditions. The system evaluates candidate resources, scores them according to multiple criteria including cost and compliance, and automatically selects optimal targets without requiring continuous manual administrator intervention, thereby reducing management time while maintaining control through policy-based management.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS10498664B2Hybrid cloud resource scheduling

Publication Date: 2019.12.03 VMWARE INC

AI summary

In an example, a method of placing a virtual computing instance among a plurality of datacenters includes comparing constraints specified for the virtual computing instance against resource metrics obtained from the plurality of datacenters, and a budget specified for the virtual computing instance against admission prices for a plurality of tiers of the plurality of datacenters, to generate a candidate set of datacenters. The method further includes scoring the candidate set of datacenters. The method further includes deploying the virtual computing instance to a target datacenter selected from the candidate set of datacenters that satisfies a threshold score.