Protected Endpoint Monitoring via Producer-Consumer Health Checks
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Solution Overview
Problem
Existing endpoint monitoring systems for cluster infrastructure, particularly in autonomous vehicle fleets, face challenges such as inability to access protected endpoints, resource intensiveness, and reliance on third-party vendors that may compromise security and scalability.
Innovation Solution
Implementing an endpoint monitoring system based on a producer-consumer model within the cluster infrastructure, where test operators generate messages and workers in a worker pool execute and evaluate tests, using a message queue to manage test execution, thereby ensuring scalability, resilience, and adherence to security protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If third-party vendor solutions are used for endpoint monitoring, then monitoring capability is provided, but security is compromised and scalability is limited
Solution Approach 1:
The patent introduces an intermediary authentication system that acts as a mediator between the endpoint monitoring system and protected endpoints. The authentication system provides tokens that enable monitoring without exposing secrets to third parties, thus maintaining security while enabling monitoring functionality.
Solution Approach 2:
The endpoint monitoring system performs self-authentication by obtaining tokens through the authentication system using service account credentials. This eliminates dependency on third-party vendors for authentication management and enables the system to securely access protected endpoints independently.
2Reliability
If traditional endpoint monitoring systems are implemented, then monitoring is performed, but resource consumption increases and scalability decreases
Solution Approach 1:
The patent segments the monitoring system into distinct components: test operators that generate test cases, an authentication system that manages security, and endpoint monitors that execute tests. This segmentation allows each component to be optimized independently and enables scalable deployment where only necessary components are activated.
Solution Approach 2:
The system dynamically adjusts its operation by having test operators generate test cases based on current system state and priorities. The endpoint monitors dynamically obtain tokens and execute tests as needed rather than continuously, reducing resource consumption while maintaining monitoring capability.
3Reliability
If comprehensive health checks are performed on all endpoints, then monitoring coverage is improved, but system performance degrades due to resource overload
Solution Approach 1:
The patent implements partial monitoring by having test operators generate test cases selectively based on system priorities and current state. Not all endpoints are monitored with the same intensity - the system performs sufficient monitoring to detect issues while avoiding excessive checks that would overload the system.
Solution Approach 2:
The endpoint monitoring system performs health checks periodically rather than continuously. Test operators generate test cases at intervals, and endpoint monitors execute tests based on schedules and system conditions, reducing the frequency of checks to levels that maintain coverage while preserving system performance.
Data Source
AI summary
Applications supporting operations of an autonomous vehicle fleet can be implemented on and supported by cluster infrastructure. These applications have endpoints where data traffic runs in and out of these applications. Monitoring the health of these endpoints can be performed by a third-party vendor solution. Third-party vendor solutions cannot access protected endpoints in the cluster infrastructure easily. Also, some solutions are resource intensive. To address some of these shortcomings, an endpoint monitoring system can be developed by cluster operators and implemented directly on the cluster infrastructure based on a producer-consumer model. The consumers of the model can perform health checks on the protected endpoints in the cluster using the same authorized path as other users of the cluster infrastructure.