Run-Time Adaptable Policy Engine for Heterogeneous Managed Entities
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Solution Overview
Problem
Modern IT environments with diverse and rapidly changing managed entities face challenges in unified management and governance, particularly in cloud-based systems, where existing technologies lack extensibility and adaptability to handle heterogeneous data types and high velocity changes.
Innovation Solution
A run-time adaptable policy engine that normalizes and correlates data from various sources, allowing dynamic introduction of new data types and sources, and enabling expressive policy evaluation across heterogeneous managed entities, thereby simplifying operations and enforcing governance policies efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional governance tools are used to manage diverse managed entities, then the system can maintain stability and control, but the system lacks extensibility and adaptability to handle new data types and high-velocity changes
Solution Approach 1:
The patent implements a dynamic metadata-driven architecture where the policy engine can adapt its behavior at runtime based on metadata about data sources and policies. This allows the system to handle new data types and sources without structural changes, resolving the contradiction between adaptability and complexity by making the system dynamically configurable rather than statically complex
Solution Approach 2:
The system changes parameters by using metadata to define and modify data structures, collection methods, and policy conditions dynamically. This allows the policy engine to accommodate new managed entities and data types by simply adding metadata definitions rather than changing system architecture, thereby improving adaptability without proportionally increasing complexity
2Productivity
If automated reactive systems are deployed to manage high-rate changes, then the system can respond efficiently to changes, but the system becomes difficult to govern and control
Solution Approach 1:
The patent introduces metadata as an intermediary layer between the automated reactive systems and governance policies. This metadata layer provides a structured interface that enables efficient automated responses while maintaining governability through declarative policy definitions, thus resolving the contradiction between response speed and ease of governance
Solution Approach 2:
The policy engine is designed with universal capabilities to handle multiple data types and sources through a unified metadata-driven approach. This allows the same governance framework to manage diverse managed entities efficiently, improving both productivity and ease of operation by avoiding specialized complex systems for each entity type
3Adaptability or versatility
If the policy engine supports multiple data types and sources, then the system achieves extensibility, but the complexity of managing and correlating heterogeneous data increases
Solution Approach 1:
The patent applies homogeneity by normalizing heterogeneous data from multiple sources into a unified structure defined by metadata. This allows the policy engine to work with diverse data types through a common interface, achieving extensibility while reducing data correlation complexity by eliminating the need for source-specific processing logic
4Reliability
If the system collects and processes data from multiple sources, then comprehensive governance is achieved, but the amount of data to be considered exceeds human capacity and requires complex automated processing
Solution Approach 1:
The patent segments the complex data processing task into distinct components: data collection, normalization, policy evaluation, and action execution. Each component handles a specific aspect of governance, allowing comprehensive processing of multi-source data while reducing overall system complexity through functional decomposition and specialized processing pipelines
Data Source
AI summary
A computer-implemented method of executing a policy-based operation on a shared computer infrastructure includes storing in a computer memory a dynamically extensible metadata system that is in communication with a processor that executes policy-based operations, where the dynamically extensible metadata system includes a data structure, a collection method, a policy processing method, and a policy condition. The collection method is then executed to collect data from a first computer resource in the shared computer infrastructure using a first data structure and from a second computer resource in the shared computer infrastructure using a second data structure, where the first data structure and the second data structure are different data structures. The collected data is then processed with the policy processing method to determine if the collected data meets the policy condition.