Compliance-Aware Application Scheduling in Hybrid Cloud
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Solution Overview
Problem
In hybrid cloud environments, ensuring ongoing compliance with security and regulatory requirements is challenging due to changing vulnerabilities and configuration issues, especially with the increasing adoption of DevOps and Agile methodologies, which demands a dynamic compliance-aware application scheduler.
Innovation Solution
A method for scheduling services that identifies a resource pool and compliance requirements, filters resources based on compliance status, scores resources by risk, and selects the most suitable resources for scheduling to maintain compliance and minimize application risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional scheduling methods are used in hybrid cloud environments, then resource allocation is simple and fast, but compliance with security and regulatory requirements cannot be ensured
Solution Approach 1:
The patent introduces a compliance intermediary layer between the scheduling system and cloud resources. This intermediary evaluates compliance status of resources and mediates scheduling decisions, ensuring compliance requirements are met without fundamentally changing the core scheduling mechanism. The compliance layer acts as a mediator that filters and validates resource selections based on security and regulatory requirements.
Solution Approach 2:
The scheduling system is segmented into distinct functional modules: resource evaluation module, compliance evaluation module, risk scoring module, and scheduling decision module. This segmentation allows each component to specialize in specific tasks, making the overall system more manageable and maintainable while achieving comprehensive compliance checking.
2Reliability
If compliance checking is performed on all resources, then compliance assurance is improved, but scheduling time and computational resources increase
Solution Approach 1:
The system performs preliminary compliance evaluation and risk scoring on resources before the actual scheduling decision. Compliance status and risk scores are pre-calculated and cached, allowing the scheduling process to quickly reference pre-evaluated information rather than performing full compliance checks at scheduling time. This reduces scheduling latency while maintaining thorough compliance verification.
Solution Approach 2:
The compliance evaluation focuses on critical compliance factors and high-risk resources first, rather than uniformly evaluating all aspects of all resources. The risk scoring mechanism prioritizes resources with higher compliance risks for more thorough evaluation, while low-risk resources receive streamlined checking, reducing overall evaluation time while maintaining compliance assurance.
3Reliability
If risk-based resource selection is implemented, then compliance and security are improved, but resource selection complexity increases
Solution Approach 1:
The patent transforms the resource selection process from a multi-dimensional complex decision into a parameter-driven selection based on risk scores. Resources are evaluated and assigned numerical risk scores based on compliance status, security posture, and other factors. The scheduling system then selects resources based on these quantified parameters, simplifying the selection logic while maintaining comprehensive security and compliance considerations.
Data Source
AI summary
A method for scheduling services in a computing environment includes receiving a service scheduling request corresponding to the computing environment and identifying a resource pool and a set of compliance requirements corresponding to the computing environment. The method continues by identifying target resources within the resource pool, wherein target resources are resources which meet the set of compliance requirements, and subsequently identifying a set of available target resources, wherein available target resources are target resources with scheduling availability. The method further includes analyzing the set of available target resources to determine a risk score for each available target resource and selecting one or more of the set of available target resources according to the determined risk scores. The method continues by scheduling a service corresponding to the service scheduling request on the selected one or more available target resources.