Automatic Resource Provisioning for Cloud Workloads

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Solution Overview

Problem

In virtualized computer environments, enterprises face challenges in efficiently managing and allocating resources to meet fluctuating application demands, leading to increased costs, extended development cycles, and friction between IT and development teams due to static IT roles and complex access controls.

Innovation Solution

A system solution for an application lifecycle platform that provides dynamic resource allocation and automatic elasticity, allowing developers to scale resources based on real-time demand, using a computing block infrastructure platform and virtualized cloud application platform to manage virtual and physical resources proactively and reactively.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual resource allocation is used, then resource allocation flexibility is improved, but operational complexity and time consumption increase

Engineering Contradiction:

Improveresource allocation flexibilityVSAvoidoperational time consumption

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system enables self-service resource allocation where the resource allocation system automatically provisions, scales, and manages computing resources based on predefined policies and real-time demands, eliminating the need for manual administrator intervention and reducing operational time consumption while maintaining flexibility

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system pre-configures resource allocation policies, templates, and configurations before actual resource needs arise, allowing automatic resource provisioning and scaling actions to be executed instantly when triggers are activated, thereby reducing operational time while maintaining adaptability

Inventive Principle:

Principle #10Preliminary action

2Stability of the object's composition

If static IT roles are used, then organizational structure stability is improved, but adaptability to cloud computing changes deteriorates

Engineering Contradiction:

Improveorganizational structure stabilityVSAvoidadaptability to cloud computing changes

Core Design Contradiction:

Stability of the object's compositionVSAdaptability or versatility

Solution Approach 1:

The system introduces dynamic role assignments and access controls that automatically adjust based on user needs, project requirements, and cloud resource usage patterns, allowing the organizational structure to adapt to cloud computing changes while maintaining stability through automated policy enforcement

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system creates universal access control mechanisms that serve multiple functions including authentication, authorization, resource allocation, and compliance monitoring, allowing a single stable framework to handle diverse cloud computing scenarios and reduce the need for specialized static roles

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Reliability

If resources are allocated to meet peak demand, then service performance reliability is improved, but operational costs increase

Engineering Contradiction:

Improveservice performance reliabilityVSAvoidoperational costs

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system dynamically adjusts resource allocation based on real-time demand patterns, automatically scaling up resources during peak periods to maintain service performance reliability and scaling down during off-peak periods to reduce operational costs, eliminating the need for static over-provisioning

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system implements continuous monitoring and feedback mechanisms that track resource usage, service performance metrics, and cost data, using this information to automatically optimize resource allocation decisions and balance between reliability and cost efficiency through closed-loop control

Inventive Principle:

Principle #23Feedback

4Productivity

If comprehensive monitoring and automatic provisioning is implemented, then resource optimization is improved, but system complexity increases

Engineering Contradiction:

Improveresource optimization efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system segments the comprehensive monitoring and provisioning function into separate modular components including monitoring agents, policy evaluation engines, resource allocation managers, and provisioning executors, allowing each component to be independently developed, maintained, and optimized while reducing overall system complexity through clear separation of concerns

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS9251033B2Automatic monitoring and just-in-time resource provisioning system

Publication Date: 2016.02.02 EMC IP HLDG CO LLC

AI summary

A method and apparatus for automatic provisioning steps using a physical computing block-based infrastructure platform and a virtualized environment is discussed to provide automatic elasticity. Running applications may be monitoring for increased workload, which may trigger a proactive and/or reactive response. The triggered proactive or reactive response includes executing a remediation action upon workloads exceeding set thresholds, as set by a pre-determined monitoring policy. The remediation actions may include the provisioning of additional virtual or physical computing resources to reduce the workload below the set threshold.