Logical Network Diagnostic Tool for State Mismatch Detection
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Solution Overview
Problem
In distributed virtual networks, diagnosing network issues is challenging due to the logical nature of network functions and services, which span multiple physical nodes, making it difficult to identify the source of issues using traditional physical network diagnostics.
Innovation Solution
A diagnostic method and tool that identifies logical paths between data compute nodes, receives and compares different states of logical forwarding elements from managed forwarding elements and a master controller, reporting problematic elements when inconsistencies are found, thereby diagnosing network issues in a logical network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional physical network diagnosis tools are used, then the diagnostic process is simple and straightforward, but the tools cannot effectively diagnose issues in distributed virtual networks where logical functions span multiple physical nodes
Solution Approach 1:
The patent introduces logical forwarding elements (LFEs) as intermediary components that abstract the complex distributed virtual network topology into manageable logical units. Each LFE spans multiple managed forwarding elements (MFEs) across different physical nodes, allowing diagnosis tools to interact with virtual network functions through a standardized logical interface rather than directly with numerous physical components. This intermediary layer enables traditional diagnostic approaches to be adapted for virtual networks while managing the underlying complexity.
Solution Approach 2:
The diagnostic system segments the distributed virtual network into discrete logical forwarding elements, each representing a specific virtual network function (routing, switching, firewalling) that can be independently diagnosed. By dividing the complex distributed system into manageable LFE segments, the tool can focus on specific logical functions rather than attempting to diagnose the entire distributed infrastructure at once, improving adaptability while managing complexity.
2Measurement precision
If the diagnostic tool examines all logical paths and forwarding elements, then diagnostic accuracy improves, but the time required to identify the source of network issues increases
Solution Approach 1:
The diagnostic tool performs preliminary actions by pre-establishing the logical network topology and identifying all logical paths between affected nodes before the actual diagnosis begins. The system pre-maps which LFEs and MFEs belong to which logical paths, so when a network issue is detected, the tool can quickly reference this pre-computed topology information rather than discovering it during the diagnostic process. This preliminary preparation maintains high diagnostic accuracy while significantly reducing the time needed to pinpoint the issue source.
Solution Approach 2:
The system applies partial action by focusing the diagnostic examination only on the specific logical paths and LFEs that are relevant to the reported network issue, rather than examining the entire logical network. When a connectivity problem is detected between two nodes, the tool identifies and examines only the logical paths connecting those nodes, leaving unrelated portions of the network unexamined. This selective approach maintains precision for the affected area while reducing overall diagnostic time.
3Reliability
If the system compares discovered state from MFEs with translated state from master controller, then diagnostic reliability improves, but the complexity of state management and comparison increases
Solution Approach 1:
The system creates a translated state that is a simplified copy or representation of the actual discovered state from MFEs. Instead of directly comparing complex raw data from multiple MFEs, the master controller translates and normalizes this data into a standardized format that mirrors the logical network model. This copied translated state can be directly compared with the desired logical configuration, improving diagnostic reliability by eliminating data format inconsistencies while managing complexity through standardization.
Solution Approach 2:
The system changes the parameters and representation of network state data during translation. Raw discovered state from MFEs contains detailed implementation-specific parameters that vary between different physical nodes. The master controller translates this into a normalized parameter set that represents the logical network state, changing the data representation to enable reliable comparison with the desired logical configuration. This parameter transformation maintains diagnostic reliability by preserving essential state information while eliminating variability that would complicate comparisons.
Data Source
AI summary
Some embodiments provide a method for diagnosing a logical network that includes several logical forwarding elements (LFEs) that logically connects a number of data compute nodes (DCNs) to each other. The method identifies a set of LFEs that logically connects a first DCN of the several DCNs to a second DCN. The method also identifies a transport node that couples to the first DCN and implements the set of LFEs. The method then, for each LFE in the set of LFEs (i) receives a first state of the LFE from the transport node, (ii) compares the first state of the LFE with a second state of the LFE that is received from a controller of the LFE, and (iii) reports the LFE as a problematic LFE along with the transport node and the controller of the LFE when the first and second states of the LFE do not match.