Distributed Host Validation Engine for SDN Goal-State Consistency
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Solution Overview
Problem
Ensuring comprehensive coverage of all corner cases in user configurations and workflows in a software defined network (SDN) is challenging due to difficulties in verifying every condition, leading to potential service interruptions.
Innovation Solution
A validation engine that runs on each host or remotely, querying control plane components to verify user goal states by comparing actual configurations against goal set data, enabling a massively distributed test engine to perform millions of tests across thousands or millions of nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a series of unit tests are written to test different configurations, then test coverage is improved, but it is difficult to verify every condition and avoid gaps in test coverage
Solution Approach 1:
The system employs automated validation engines that self-execute tests against configured network nodes without requiring manual verification of every condition. The validation engine automatically compares actual configuration states against expected goal states, eliminating the need for human operators to manually verify each test case while maintaining comprehensive coverage.
Solution Approach 2:
The patent replaces manual mechanical testing processes with automated software-based validation engines. Instead of manually checking each configuration condition, the system uses programmable validation logic that automatically executes tests, collects results, and generates reports, substituting human verification with automated computational processes.
2Reliability
If a validation engine runs on each host to verify configurations, then reliability is improved, but computing resources such as processor cycles, memory, network bandwidth, and power are consumed
Solution Approach 1:
The validation engine implements selective verification by identifying and validating only the critical configuration parameters and corner cases rather than attempting to verify every possible condition exhaustively. This partial action approach maintains sufficient reliability for production environments while significantly reducing the computational burden on individual hosts.
Solution Approach 2:
The system introduces a centralized validation coordinator that acts as an intermediary between configuration management and individual host validations. The coordinator distributes validation tasks intelligently, batches requests, and manages validation workflows to minimize the impact on host resources while ensuring comprehensive verification coverage.
3Productivity
If a massively distributed test engine performs millions of tests across thousands or millions of nodes, then productivity is improved, but device complexity increases
Solution Approach 1:
The validation system is divided into independent modular components including validation engines running on individual hosts, a centralized coordination service, and standardized communication interfaces. This segmentation allows the system to scale horizontally by adding more independent validation nodes without increasing the complexity of individual components, enabling parallel execution of millions of tests across thousands of nodes.
Solution Approach 2:
The validation engine implements a universal validation framework that can test multiple configuration scenarios, network protocols, and device types through a single unified platform. The system uses parameterizable test templates and goal state definitions that can be applied across different network configurations, eliminating the need for separate specialized testing systems for each scenario.
Data Source
AI summary
Techniques are described for a validation engine configured to verify user goal states in a virtualized computing environment comprising a plurality of hosts executing a plurality of virtual machines or containers. A representation of a user goal state encoding an updated state is received and queries are sent to control plane components to obtain current states of hosts in the network. The current states and local configurations are verified to be consistent with the user goal state.