Intelligent Configuration Discovery for Distributed Systems
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Solution Overview
Problem
The complexity of large-scale computing environments, where applications span various resources and are distributed across multiple data centers, makes it difficult to understand relationships and dependencies among application components, hindering business decisions such as migrating applications from customer-owned premises to provider networks.
Innovation Solution
An intelligent configuration discovery service that automates the detection of configuration items, assigns unique identifiers, tracks interactions and dependencies, and provides performance monitoring, along with a visualization service and migration marketplace to assist in migrating applications by organizing and curating configuration information from diverse data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If applications are distributed across multiple data centers with diverse resources, then application execution capability and flexibility are improved, but understanding relationships and dependencies among application components becomes difficult
Solution Approach 1:
The patent introduces an intermediary service that acts as a mediator between diverse configuration data sources and the user. This service collects, normalizes, and correlates configuration information from multiple data centers, virtualization layers, and infrastructure components, transforming complex distributed system data into comprehensible dependency models that reveal relationships among application components across different locations.
Solution Approach 2:
The patent segments the complex distributed application environment into manageable configuration units organized by logical layers (application layer, virtualization layer, infrastructure layer). By dividing the system into discrete, identifiable configuration items with standardized attributes, the service enables systematic analysis of dependencies across data centers without being overwhelmed by the overall system complexity.
2Loss of information
If configuration information is collected from diverse data sources, then completeness of application understanding is improved, but complexity of managing and organizing configuration data increases
Solution Approach 1:
The patent implements a universal configuration data model that can represent diverse infrastructure elements (physical servers, virtual machines, containers, storage devices, network components) using a common schema. This multi-functional framework allows the same data structure to handle different data sources and types, enabling comprehensive application understanding while maintaining consistent organization and reducing management complexity through standardization.
3Measurement precision
If manual analysis of application dependencies is performed, then accuracy of dependency understanding is improved, but time and resources required increase significantly
Solution Approach 1:
The patent enables the system to automatically discover and document its own configuration relationships through self-service mechanisms. Configuration agents deployed across infrastructure components automatically report their state and relationships to the central service, which then constructs dependency models without requiring manual intervention. This self-documenting approach maintains high accuracy while eliminating the time and resource costs of manual analysis.
Data Source
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AI summary
At a configuration discovery service, a unique service-side identifier is generated for a configuration item based on analysis of a data set obtained from a first data source. A determination is made that a second data set, which does not contain the service-side identifier and is obtained from a different data source, also includes information pertaining to the same configuration item. A coalesced configuration record for the configuration item is prepared. The coalesced configuration record is stored at a repository and used to respond to a programmatic query.