Adaptive Network Tracing Protocol Selection for Cloud Systems
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Solution Overview
Problem
Existing network monitoring tools struggle to accurately trace network paths and measure performance through encrypted tunnels and cloud-based systems, often resulting in incomplete data due to protocol restrictions and firewall blocks, which limits visibility into network hops and latency.
Innovation Solution
A system and method that adaptively determine the best protocol for tracing network paths by performing multiple traces using different protocols, evaluating reachability, latency, and packet loss, and selecting the optimal protocol to bypass firewall issues and opaque tunnels, enabling comprehensive network performance monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional traceroute tools are used to trace network paths, then basic network visibility is achieved, but complete and accurate network performance data cannot be obtained through encrypted tunnels and cloud-based systems
Solution Approach 1:
The system changes the protocol parameter by attempting multiple different protocols (ICMP, UDP, TCP) to trace the network path. By varying the protocol type, the system can adapt to different network configurations including encrypted tunnels and cloud-based systems that may block or restrict certain protocols, thereby achieving both measurement accuracy and compatibility.
Solution Approach 2:
The system dynamically selects and switches between different protocols based on which ones successfully traverse the network path. Rather than using a static single protocol, the system adapts its approach in real-time by evaluating which protocols work and using those for measurement, enabling it to handle dynamic network environments with firewalls and encrypted connections.
2Loss of information
If manual traceroute operations are performed using multiple protocols, then comprehensive network path data can be collected, but the operation becomes complex and time-consuming
Solution Approach 1:
The system performs self-service by automatically attempting multiple protocols and selecting the working ones without requiring manual intervention. The automated system evaluates which protocols successfully traverse the network path and uses those for measurement, eliminating the need for operators to manually test each protocol while ensuring complete network path data is collected.
Solution Approach 2:
The system performs preliminary actions by automatically attempting multiple protocols before the actual network performance measurement. By pre-testing which protocols work in the given network environment, the system prepares the optimal protocol selection in advance, reducing operational complexity during the actual measurement phase while ensuring complete data collection.
3Reliability
If administrators block certain protocols or ports for security purposes, then network security is improved, but traceroute tools cannot obtain complete network path information
Solution Approach 1:
The system changes the protocol parameter by attempting multiple different protocols (ICMP, UDP, TCP) to trace the network path. By varying the protocol type, the system can adapt to different network configurations including encrypted tunnels and cloud-based systems that may block or restrict certain protocols, thereby achieving both measurement accuracy and compatibility.
4Loss of information
If multiple protocols are attempted for traceroute, then complete network path data can be obtained, but the time and resources required increase
Solution Approach 1:
The system performs preliminary actions by automatically attempting multiple protocols before the actual network performance measurement. By pre-testing which protocols work in the given network environment, the system prepares the optimal protocol selection in advance, reducing operational complexity during the actual measurement phase while ensuring complete data collection.
Data Source
AI summary
Techniques for using trace with tunnels and cloud-based systems for determining measures of network performance are presented. In an embodiment, a method includes determining a client application is being executed; determining an endpoint associated with the client application, based on any of monitoring application logs associated with the client application and network flows associated with the client application; and causing one or more probes to the determined endpoint and deriving metrics based on the one or more probes for determining performance of the client application.


