Automated Data Conformance Engine for Storage Policy Enforcement
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Solution Overview
Problem
Storage administrators face challenges in managing networked data storage systems, including determining and enforcing data management policies across numerous storage objects, which can lead to errors and inefficiencies due to the complexity of manual processes and lack of automated compliance auditing.
Innovation Solution
An apparatus and method featuring a conformance checker and conformance engine that automatically compare data sets to data management policies and enforce policy compliance, reducing administrative burden and error risk by ensuring data sets conform to defined policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If administrators manually manage and enforce data management policies across storage objects, then policy compliance can be monitored, but the complexity and error rate increase significantly as the number of storage objects grows
Solution Approach 1:
The system enables self-service through automated policy enforcement mechanisms. The conformance engine automatically detects policy violations and executes remediation actions without human intervention, while the self-service portal allows administrators to autonomously manage policy compliance. This eliminates manual monitoring and enforcement tasks, reducing management complexity while maintaining reliable policy compliance across growing numbers of storage objects.
2Adaptability or versatility
If administrators manually reconfigure storage objects when policies change, then policy updates can be implemented, but the process becomes increasingly error-prone and time-consuming
Solution Approach 1:
The system implements preliminary action through the conformance engine, which proactively evaluates storage objects against updated policies before violations occur. When policies change, the engine automatically identifies affected objects and executes remediation actions in advance, preventing compliance breaches. This eliminates the need for manual reconfiguration after policy changes, reducing both time loss and error rates while maintaining full policy flexibility.
3Measurement precision
If comprehensive manual auditing of storage objects is performed to ensure policy compliance, then compliance accuracy can be verified, but the time and resources required increase significantly
Solution Approach 1:
The system implements continuous automated auditing through the conformance engine, which continuously monitors storage objects against policy requirements without interruption. This continuous monitoring maintains high compliance accuracy by immediately detecting violations, while eliminating the need for periodic manual audits. The automated nature of the monitoring eliminates time loss associated with scheduling and executing manual audit cycles, providing both precision and efficiency simultaneously.
4Loss of information
If detailed tracking of storage objects and their relationships is maintained manually, then policy applicability can be determined, but the administrative burden and potential for errors increase
Solution Approach 1:
The system introduces an intermediary layer in the form of the conformance engine and self-service portal, which automatically track and manage storage objects and their relationships. This intermediary automatically determines policy applicability by evaluating objects against policy rules, eliminating the need for administrators to manually track objects and relationships. This maintains accurate policy tracking information while dramatically improving administrative ease by removing the manual burden of tracking.
Data Source
AI summary
An apparatus and a method to make data sets conform to data management policies are presented. In one embodiment, the apparatus includes a conformance checker and a conformance engine. The conformance checker may be operable to compare a state of a data set against a data management policy associated with the data set to determine if the data set currently conforms to the data management policy. The conformance engine may then make the data set conform to the data management policy if the conformance checker determines that the data set currently violates the data management policy.