Policy-Based Automatic Flow Collection Discovery
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Solution Overview
Problem
Conventional systems require manual expertise and are cumbersome for administrators to create and manage flow collections in large deployments, making it impractical to analyze and configure hundreds or thousands of communications flows effectively.
Innovation Solution
The implementation of a policy-based automatic flow collection discovery system that uses intuitive interfaces and automated tools to simplify the grouping of flows, allowing administrators to select policies such as Application Centric, LUN Centric, Server Centric, and Zone Centric collections, which automatically identify and maintain flow groups without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual flow collection creation is used, then administrators can create flow groups with precise control, but the process becomes complex and time-consuming requiring in-depth knowledge of device addresses and flow definitions
Solution Approach 1:
The system performs automatic flow collection discovery by self-configuring flow groups based on monitored network traffic patterns and device interactions. The management device automatically identifies flows, groups them by device or application, and maintains the groupings without requiring manual administrator intervention, thereby eliminating the complexity of manual configuration while preserving accurate flow grouping through automated analysis of actual network behavior
Solution Approach 2:
The system performs preliminary monitoring and analysis of network flows to automatically discover and establish appropriate flow groupings before administrators need to query or manage them. By continuously monitoring traffic patterns and pre-configuring logical groupings based on observed device communications and application behavior, the system prepares flow collections in advance, making them immediately available for reporting and management without requiring manual setup
2Manufacturing precision
If manual flow analysis is performed in large deployments, then detailed control over each flow can be achieved, but it becomes infeasible to analyze and configure hundreds or thousands of flows
Solution Approach 1:
The management device automatically performs flow discovery and grouping by monitoring network traffic and analyzing flow patterns without requiring administrator intervention. The system self-configures hundreds or thousands of flow groupings based on observed device communications, application behavior, and network patterns, maintaining precise flow configuration through automated rules and policies while achieving high productivity by eliminating manual configuration of each individual flow
Solution Approach 2:
The system implements universal flow grouping mechanisms that automatically apply to all flows in the network regardless of scale. By using application-layer analysis, device identification, and pattern recognition that work across diverse network configurations and scales, the system can uniformly manage thousands of flows through a single automated process rather than requiring individual manual configuration for each flow type or scale
3Ease of operation
If automated flow discovery is implemented, then administrative time and complexity are reduced, but the system requires continuous monitoring and policy management
Solution Approach 1:
The system implements continuous monitoring of network flows to dynamically discover and update flow groupings as network conditions change. By continuously analyzing traffic patterns, device communications, and application behavior, the system maintains accurate and current flow groupings automatically, reducing administrative effort while managing resource consumption through efficient continuous analysis rather than periodic manual updates or intensive batch processing
Data Source
AI summary
In some aspects, the disclosure is directed to methods and systems for automatically identifying a set of communications flows in a network environment, and grouping the identified set into a flow collection for management and monitoring. The system may dynamically maintaining the group membership, without requiring manual analysis and grouping. As a result, manual grouping of flows may be avoided, avoiding this complex, tedious, and error prone task, and allowing easier and more efficient administration and management.