Data Center Environment Architecture for Continuous Test Orchestration
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Solution Overview
Problem
Existing data center management systems face challenges with static test execution plans that require constant revision due to changing dependencies, leading to delays and increased costs in test automation orchestration.
Innovation Solution
A data-driven autonomous data center test automation orchestration system that generates continuous test plans using historical data, weighted statistical models, and real-time resource management to optimize execution plans and adapt to changing constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static test execution plans are used, then test automation orchestration is simpler to manage, but the plans require constant revision due to changing dependencies, leading to delays and increased costs
Solution Approach 1:
The patent implements dynamic test execution plans that automatically adapt to changing dependencies and constraints. The system continuously monitors test environments, resource availability, and defect severity, then dynamically adjusts test schedules and execution orders without requiring manual plan revisions. This resolves the contradiction by making the test automation orchestration both easy to manage (automatic adjustments) and time-efficient (no delays from manual revisions).
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor test execution status, resource availability, and dependency changes. This feedback loop enables automatic plan adjustments by comparing actual execution conditions against planned parameters and triggering re-scheduling when deviations are detected. The feedback-driven approach eliminates the need for constant manual plan revision while maintaining optimal test execution timing.
2Ease of manufacture
If static test execution plans are used, then initial setup is simpler, but constant revision is required due to changing dependencies, increasing costs
Solution Approach 1:
The system performs preliminary actions by pre-configuring dynamic adaptation capabilities and dependency monitoring mechanisms during initial test plan setup. Rather than creating static plans that require revision, the system is pre-equipped with automated scheduling algorithms and dependency tracking that proactively handle changes. This preliminary configuration reduces both initial setup complexity and long-term maintenance costs.
Solution Approach 2:
The test automation system implements self-service capabilities where the scheduling component automatically detects dependency changes, re-evaluates test priorities, and re-schedules test executions without human intervention. This self-adjusting mechanism eliminates the need for manual plan revisions and associated costs, while maintaining simple initial setup procedures.
3Productivity
If continuous test plan orchestration is implemented, then test execution efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal orchestration framework that handles multiple test types, dependencies, and resource constraints through a single integrated system. The continuous scheduler component serves multiple functions: monitoring dependencies, managing resources, prioritizing tests based on defect severity, and generating execution schedules. This multi-functional approach improves test execution efficiency while avoiding the complexity of multiple separate systems.
Solution Approach 2:
The system introduces an intermediary continuous scheduler component that mediates between test definitions, resource availability, and execution requirements. This intermediary layer abstracts the complexity of continuous orchestration, presenting a simplified interface to users while handling complex scheduling decisions internally. The mediator pattern resolves the contradiction by isolating complexity within the scheduling component while maintaining simple interfaces for test management.
Data Source
AI summary
A system, method, and computer-readable medium for performing a data center management and monitoring operation. The data center management and monitoring operation includes: receiving a plurality of system under test (SUT) test plans, each SUT test plan comprising a plurality of SUT test cases; providing an analysis component, the analysis component analyzing the plurality of SUT test cases; providing a continuous scheduler component, the continuous scheduler component generating a continuous schedule for the SUT test plan; and, providing a continuous execution plan component, the continuous execution plan component continuously orchestrating the SUT test plan based upon the continuous schedule for the SUT test plan.