Graph Comparison for Distributed System Availability Risk Assessment
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Solution Overview
Problem
Current data storage and computing services lack effective methods to assess and mitigate resource availability risks in distributed systems, leading to potential service disruptions and data loss due to inadequate redundancy and failure insulation across different locations.
Innovation Solution
A service provider system generates and compares best practice graphs with customer graphs to identify resource availability risks, recommending deployment of resources across multiple zones and regions to enhance redundancy and minimize service disruptions, using virtual machine instances and data volume management for low latency and durability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If resources are deployed in a single location or region, then device complexity is reduced, but reliability deteriorates due to lack of redundancy and failure insulation
Solution Approach 1:
The patent segments the computing resource deployment into multiple independent zones and regions, creating graph representations that model dependencies within each segment. By analyzing these segmented graphs, the system identifies how failures in one segment can be isolated and prevented from propagating to other segments, thereby improving reliability through failure insulation while maintaining manageable complexity through structured organization.
Solution Approach 2:
The patent introduces a new dimensional perspective by creating graph models that represent computing resources across multiple spatial dimensions (zones and regions). This dimensional transformation allows the system to visualize and analyze resource relationships in a multi-layered structure, enabling identification of deployment patterns that enhance availability without proportionally increasing operational complexity.
2Reliability
If resources are distributed across multiple zones and regions, then reliability is improved through redundancy, but device complexity increases due to additional deployment configurations
Solution Approach 1:
The patent implements feedback mechanisms through graph comparison analysis, where the system continuously evaluates the current resource deployment graph against ideal configurations. This feedback loop identifies specific deviations from optimal availability patterns and provides targeted recommendations for remediation, allowing operators to maintain high reliability through distributed deployment while reducing configuration complexity by following data-driven guidance rather than manual best practices.
Solution Approach 2:
The patent transforms the complex multi-dimensional deployment configuration problem into a graph parameter comparison task. By representing resources as nodes and dependencies as edges in the graph, the system changes the parameter space from numerous individual configuration settings to structural graph properties (connectivity, redundancy paths, zone distribution). This parameter transformation simplifies the management of distributed resources while maintaining the reliability benefits of multi-region deployment.
3Reliability
If comprehensive risk assessment is performed using graph comparison, then reliability is improved through proactive identification of vulnerabilities, but device complexity increases due to analysis overhead
Solution Approach 1:
The patent extracts the essential structural properties of resource deployments by representing them as graphs with specific nodes and edges. This extraction process separates the critical availability-determining characteristics from the full complexity of the underlying infrastructure details. By focusing analysis on the extracted graph representation rather than the complete system state, the patent enables comprehensive risk assessment while reducing assessment complexity through targeted structural analysis.
Data Source
AI summary
Embodiments of the present disclosure are directed to, among other things, determining whether some or all portions of an application stack implemented on a distributed system are vulnerable to availability issues. In some examples, a web service may utilize or otherwise control a client instance to control, access, or otherwise manage resources of a distributed system. Based at least in part on comparing one or more customer graphs with one or more model, curated, or best practice graphs of a distributed system, availability risks and/or deployment recommendations may be provided. Additionally, in some examples, one or more remediation and/or migration operations may be performed automatically or provided as recommendations.