Topology Discovery for Distributed Computing Environments

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Solution Overview

Problem

In distributed computing environments, there is a challenge in seamlessly transitioning software applications from development to deployment due to lack of readily available information about existing resources in the deployment environment, leading to configuration issues and incompatibilities.

Innovation Solution

An extensible method is provided to discover and model the current topology of a data center, creating linkages between existing and new resources using customizable matching rules, with environment-specific handlers and filters to automate resource discovery and linkage creation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual introspection and documentation methods are used to discover existing resources, then information accuracy may be maintained, but deployment time and complexity increase significantly

Engineering Contradiction:

Improveinformation accuracyVSAvoiddeployment time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The deployment environment performs self-introspection to automatically discover existing resources, their states, and linkages. The system queries itself to obtain configuration information without requiring manual documentation, thereby maintaining accuracy while reducing deployment time.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual introspection and documentation processes are replaced with automated computer-based discovery mechanisms. The system uses programmatic queries and automated handlers to replace manual information gathering, eliminating the time-consuming nature of manual processes while maintaining data accuracy.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of information

If comprehensive resource discovery is performed across all environment types, then completeness of resource information improves, but system complexity and processing overhead increase

Engineering Contradiction:

Improvecompleteness of resource informationVSAvoidsystem complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The resource discovery process is divided into environment-specific handlers, each responsible for a particular type of deployment environment. This segmentation allows the system to manage complexity by organizing discovery logic into modular, specialized components while maintaining comprehensive coverage across different environments.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically selects and executes appropriate handlers based on the specific deployment environment being discovered. This dynamic adaptation allows comprehensive resource discovery tailored to each environment type without requiring a single complex monolithic system, thereby managing overall system complexity.

Inventive Principle:

Principle #15Dynamics

3Productivity

If automated handlers are used to discover resources and create linkages, then deployment efficiency improves, but the initial setup and configuration complexity increases

Engineering Contradiction:

Improvedeployment efficiencyVSAvoidconfiguration complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The handler architecture provides a universal framework that can discover and manage multiple types of resources across different deployment environments. This multi-functionality allows a single automated system to handle diverse resource types and environments, improving deployment efficiency while managing configuration complexity through standardized interfaces.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS8849987B2Automated discovery of a topology of a distributed computing environment

Publication Date: 2014.09.30 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

This invention provides an extensible means of defining the mechanism to find one or more type(s) or instance(s) of existing resources (files, databases, repositories, etc.) and automating their linkages to the artifacts to be created, based on the customizable matching rules.