Microburst Visibility System Flow Engine
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Solution Overview
Problem
Conventional methods for providing microburst visibility in information handling systems are burdensome in terms of network bandwidth and storage, and they do not effectively analyze which flows contribute to or are affected by microbursts, lacking essential information for detailed analysis.
Innovation Solution
An Information Handling System (IHS) with a flow database and processing system that captures and analyzes queue flow information for each flow, providing a flow engine to identify queues, modify data packet counters, detect microbursts, and capture relevant information for analysis, allowing for detailed microburst visibility with reduced processing overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods (INT, IOAM, DPP) are enabled on all flows to provide microburst visibility, then measurement precision is improved, but network bandwidth consumption increases and device complexity increases
Solution Approach 1:
The patent extracts only the essential queue depth information from the full packet data, copying only the queue depth value to memory when a microburst is detected, rather than copying all packet data. This selective extraction reduces storage and processing requirements while maintaining microburst visibility.
Solution Approach 2:
The system performs preliminary actions by setting up trigger mechanisms that automatically capture queue depth information when microburst conditions are met, eliminating the need for continuous offline processing of all packet data and reducing real-time bandwidth consumption.
2Measurement precision
If all packets in a queue are copied to memory when microburst is detected, then measurement precision is improved, but storage requirements and processing intensity increase significantly
Solution Approach 1:
The patent extracts only the essential queue depth information from the full packet data, copying only the queue depth value to memory when a microburst is detected, rather than copying all packet data. This selective extraction reduces storage and processing requirements while maintaining microburst visibility.
Solution Approach 2:
Instead of storing all packet data permanently, the system uses temporary memory structures to hold only the critical queue depth information needed for microburst analysis, discarding the rest of the packet data after extraction. This approach reduces storage requirements while maintaining analysis capability.
3Difficulty of detecting and measuring
If conventional methods are used to detect microbursts, then detection capability is improved, but the ability to analyze contributing and affected flows is insufficient
Solution Approach 1:
The system performs preliminary actions by setting up trigger mechanisms that automatically capture queue depth information when microburst conditions are met, eliminating the need for continuous offline processing of all packet data and reducing real-time bandwidth consumption.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors queue depth and provides real-time information about which flows are contributing to and affected by microbursts, enabling detailed flow analysis without requiring offline processing of all packet data.
Data Source
AI summary
A microburst visibility system includes a switch device coupled to each sender device(s) and receiver device(s). The switch device receives flows transmitted by the sender device(s) to the receiver device(s). For each flow that include data packets that are stored in a first queue, the switch device provides a first queue identifier for the first queue in a flow record associated with that flow and modifies, for each data packet that is transmitted as part of that flow, flow information in data packet counter(s) that are associated with the first queue identifier in the flow record associated with that flow. When the switch device detects a microburst in the first queue, it captures the flow information in each data packet counter that is associated with the first queue identifier in each of the flow records included in the switch device, and provides it for analysis.