Remote Policy Validation for Distributed Systems
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Solution Overview
Problem
Resource management systems face inefficiencies in managing large-scale distributed systems with growing numbers of components, as they struggle to define and apply appropriate actions and behaviors efficiently without pre-defined policy sets, leading to unmanageable policy validation and adaptation to changing conditions.
Innovation Solution
Implementing remote policy validation, where a resource manager uses remote validation agents to validate policies syntactically and semantically, allowing users to craft custom policies and apply them to distributed system resources, enabling efficient management and validation of policies without pre-defined sets, and allowing policies to be applied hierarchically across resource data objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If resource management systems use pre-defined policy sets to manage system components, then policy application is standardized and efficient, but the systems lack adaptability to changing conditions and custom management requirements
Solution Approach 1:
The patent segments policy management into distinct functional components: policy definition, policy validation, and policy application. Remote validation agents are deployed as independent segments distributed across the system architecture, allowing policies to be validated locally before enforcement. This segmentation enables custom policies to be managed efficiently without requiring centralized validation of every policy change, thus improving adaptability while controlling complexity.
Solution Approach 2:
The system performs preliminary validation of custom policies through remote validation agents before the policies are applied to system components. This preliminary action ensures that custom policies meet syntactic and semantic requirements upfront, preventing invalid policies from causing system errors. The advance validation mechanism enables greater policy flexibility while maintaining system integrity without adding operational complexity.
2Adaptability or versatility
If resource management systems allow custom policies without pre-defined sets, then flexibility and adaptability improve, but validation becomes unmanageable and error-prone
Solution Approach 1:
Remote validation agents act as intermediaries between policy creators and the resource management system. These agents validate custom policies for syntactic correctness and semantic appropriateness before policies are enforced. The intermediary validation layer filters out erroneous policies while allowing flexible custom policies to pass through, thus maintaining both policy flexibility and validation reliability without requiring manual review of every custom policy.
3Manufacturing precision
If resource management systems manually reconfigure system components to implement behavior changes, then precise control is achieved, but the cost and time for modifications increase significantly
Solution Approach 1:
The patent uses policy definitions as abstract copies or templates that describe desired system component behaviors. Instead of manually reconfiguring individual system components, administrators define policies that copy and enforce behavioral patterns across multiple components. The resource management system applies these policy copies automatically, achieving precise behavioral control without the time-consuming process of manual component-by-component reconfiguration.
4Quantity of substance
If resource management systems increase the number of system components to handle growing user bases, then system capacity improves, but the complexity of defining and applying appropriate actions and behaviors increases
Solution Approach 1:
The patent implements universal policy templates that can be applied across diverse system components regardless of their specific functions. A single policy definition can enforce consistent behavioral rules across multiple components (e.g., access control policies applied to storage, compute, and network resources). This universality allows the system to scale to handle growing user bases with increased component quantities while maintaining manageable policy complexity through reusable, multi-functional policy templates.
Data Source
AI summary
Distributed system resources may be managed by applying user created policies to the resources. To ensure that valid policies are applied, remote validation for the policies may be implemented. A validation event for a policy may be detected. A remote validation agent may be identified for the policy and a validation request sent to the remote validation agent that includes information for validating the policy. The remote validation agent may return a validation result for the policy. If valid, a policy action that triggered the remote validation event for the policy may be allowed. If invalid, the policy action that triggered the remote validation event for the policy may be denied.