Virtual Appliance Performance Lag Prediction via Benchmark Scores
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Solution Overview
Problem
Determining accurate performance metrics for virtual network appliances is challenging due to varying hardware configurations and software implementations, making it difficult to provision and scale network services effectively and prevent performance lag.
Innovation Solution
A method involving determining benchmark scores for virtual appliances on specific hardware configurations, using these scores and configuration values as inputs for a trained predictive model to forecast performance, and taking actions such as resource allocation adjustments or migration to prevent performance lag.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If virtual network appliances are deployed on varied hardware configurations, then adaptability and versatility are improved, but measurement precision of performance metrics deteriorates
Solution Approach 1:
The patent applies parameter changes by using a predictive model that takes hardware configuration parameters (CPU speed, memory amount, processor type) and software configuration parameters as inputs to estimate performance metrics. This allows the system to adapt performance predictions to different hardware configurations without requiring physical measurement on each specific platform, thus maintaining measurement precision while achieving adaptability across varied hardware.
Solution Approach 2:
The patent introduces a predictive model as an intermediary between hardware configuration and performance metric determination. Instead of directly measuring performance on each hardware platform, the model acts as a mediator that translates hardware specifications into estimated performance values, resolving the contradiction between adapting to diverse hardware and maintaining precise performance measurements.
2Ease of operation
If performance metrics are published for virtual appliances, then ease of operation is improved, but reliability of performance prediction deteriorates
Solution Approach 1:
The patent applies preliminary action by calculating and providing performance estimates before the virtual appliance is actually deployed or before performance lag occurs. The predictive model pre-assesses performance based on hardware and software configurations, allowing operators to make informed decisions about resource allocation and appliance placement before actual performance issues arise, thus maintaining both ease of operation and reliability.
Solution Approach 2:
The system implements feedback by continuously monitoring actual performance and comparing it with predicted values, then using this information to refine the predictive model. This feedback mechanism ensures that the published performance metrics remain reliable while maintaining ease of operation for users who rely on these metrics for decision-making.
3Productivity
If resource allocation is increased for virtual appliances, then productivity is improved, but loss of energy worsens
Solution Approach 1:
The patent applies partial action by allocating resources based on predicted performance requirements rather than providing maximum resources to all virtual appliances. The predictive model identifies the optimal level of resource allocation needed to achieve desired performance levels, avoiding excessive resource allocation and the associated energy waste while still improving productivity through targeted resource distribution.
Data Source
AI summary
Embodiments of the present disclosure relate to predicting and preventing performance lag of virtual network appliances. Embodiments include determining a benchmark score for a virtual appliance running on a computing device. Embodiments include providing the benchmark score and one or more virtual appliance settings of the virtual appliance as inputs to a trained predictive model and receiving a predicted performance value as an output from the trained predictive model. Embodiments include using the predicted performance value to perform one or more actions.