Automatic Tag-Based Architecture Diagrams for Distributed Systems
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Solution Overview
Problem
Modern distributed and virtualized computer systems experience challenges in maintaining accurate architecture diagrams due to frequent changes in resource allocation and system topology, making it difficult for designers and analysts to identify potential flaws and anticipate failures, leading to reduced performance and increased outages.
Innovation Solution
The implementation of an automatic tag-based system that generates and updates architecture diagrams by utilizing tags associated with computer system resources and inferred relationships, allowing for the creation of accurate and current graphical representations of system structure and relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual architecture diagrams are used to represent computer systems, then initial system design can be documented, but the diagrams rapidly diverge from the actual deployed system due to frequent changes in resource allocation and system topology
Solution Approach 1:
The system automatically generates and updates architecture diagrams by querying cloud resources through APIs and rendering them based on current system state, eliminating the need for manual updates. The diagrams self-update whenever the underlying system changes, ensuring continuous accuracy without human intervention.
Solution Approach 2:
The system continuously queries the actual cloud resource state through APIs and compares it with the represented architecture diagram, automatically detecting and rendering changes. This feedback loop ensures the diagram always reflects the current system topology and resource allocation.
2Reliability
If architecture diagrams are manually maintained in volatile distributed systems, then initial documentation is possible, but system complexity increases and accuracy decreases due to frequent alterations in resource needs and business goals
Solution Approach 1:
The patent replaces manual mechanical processes of drawing and updating diagrams with an automated computational system that queries cloud APIs, processes resource data, and generates diagrams programmatically. This substitution eliminates human effort and ensures consistency.
Solution Approach 2:
The system serves multiple functions: it discovers cloud resources, infers relationships between them, generates architecture diagrams, and automatically updates them. This multi-functional approach consolidates what would otherwise require separate manual processes into a single automated system.
3Ease of operation
If static architecture diagrams are used for volatile systems, then initial design documentation is achieved, but the ability to locate system flaws and anticipate failures is reduced
Solution Approach 1:
The architecture diagrams transition from static representations to dynamic, continuously updating visualizations that reflect real-time or near-real-time system state. The system automatically detects changes in resource allocation, topology, and configuration, and updates the diagrams accordingly, enabling operators to always view the current system state.
Data Source
AI summary
Techniques for generating a graphical representation that depicts topological relationships among computer system resources are described herein. After receiving system information specifying a set of computer system resources, a dependency between a pair of the set of resources, the set of resources can be filtered by a tag comprising a key and a value to create a subset of resources. A graphical representation depicts the subset of resources and topological relationships among computer system resources.