Tenant Element Deployment Using Harvested Performance Metrics
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Solution Overview
Problem
Current public cloud service providers' performance metrics are simplistic and inadequate for determining the appropriate resource elements for deploying virtual network functions, leading to challenges in dimensioning deployments, adhering to service-level agreements, and managing scalability.
Innovation Solution
A method is introduced that evaluates multiple candidate resource elements by deploying instances of each candidate in the public cloud, collecting performance metrics, and generating reports to select the optimal resource element and determine the number of instances needed, ensuring compliance with service-level agreements and efficient scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If simplified performance metrics published by CSPs are used, then deployment process is simple and quick, but deployment accuracy and ability to meet performance needs is insufficient
Solution Approach 1:
The system performs preliminary performance testing by deploying test instances of candidate resource elements before actual deployment. Agents are installed on these test instances to collect performance metrics in advance, allowing the system to evaluate and compare candidate resource elements before making deployment decisions, thus resolving the contradiction between simple deployment process and accurate performance evaluation
Solution Approach 2:
The patent introduces agents as intermediary components that are deployed on candidate resource elements to collect detailed performance metrics. These agents act as mediators between the resource elements and the evaluation system, gathering comprehensive performance data that is then aggregated and analyzed to determine the most suitable resource elements for deployment, thereby improving measurement precision without complicating the overall deployment process
2Measurement precision
If detailed performance testing is conducted on multiple candidate resource elements, then deployment accuracy and SLA compliance improve, but deployment time and computational resources increase
Solution Approach 1:
The system performs performance testing on multiple candidate resource elements beyond what is strictly necessary for a single deployment decision. By evaluating a broader set of candidates with comprehensive metrics, the system ensures more accurate and reliable selection, accepting the additional time and resource investment as worthwhile for achieving superior deployment accuracy and SLA compliance
Solution Approach 2:
Performance metrics are collected and aggregated in advance during a preliminary evaluation phase. This preliminary action allows the system to have performance data ready before actual deployment decisions are made, reducing the time required during the critical deployment phase while maintaining comprehensive evaluation accuracy
Data Source
AI summary
Some embodiments of the invention provide a method of deploying first and second tenant deployable elements to a set of one or more public clouds, the first and second tenant deployable elements being different types of elements. The method identifies first and second sets of performance metrics respectively for first and second sets of candidate resource elements to use to deploy the first and second tenant deployable elements, the two sets of performance metrics being different sets of metrics because the first and second tenant deployable elements being different types of elements, the first set of performance metrics having at least one metric that is not included in the second set of performance metrics. The method uses the different sets of metrics evaluate the first and second sets of candidate resource elements, in order to select one of the first set of candidate resource elements for the first tenant deployable element and to select one of the second set of candidate resource elements for the second tenant deployable element. The method deploys the first and second tenant deployable elements in the set of PCDs by using the selected candidate resource elements.