Virtual Application Delivery Controller Dynamic Scaling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing application delivery fabrics face challenges in efficiently managing resource demand, leading to either overload or underutilization of application delivery controllers, resulting in performance issues and inefficient resource allocation.
Innovation Solution
The deployment of virtual application delivery controllers, which can be dynamically scaled up or down based on performance metrics, allowing for real-time adjustment to meet changing demand by a centralized command center, enabling efficient resource allocation and utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If additional application delivery controllers are purchased to meet demand, then the system capacity and reliability are improved, but the cost and device complexity increase
Solution Approach 1:
The patent implements dynamic scaling of application delivery controllers based on real-time demand monitoring. The system automatically provisions additional controllers when demand thresholds are exceeded and de-provisions them when demand decreases, transforming the static infrastructure into a dynamic system that adapts to changing workload conditions.
Solution Approach 2:
The system employs self-service automation through demand monitoring and automatic provisioning mechanisms. The application delivery fabric autonomously detects demand changes, triggers controller deployment or removal without manual intervention, and manages the entire lifecycle of controllers based on real-time performance metrics.
2Productivity
If more application delivery controllers are deployed to handle peak demand, then the system can service higher loads, but resources are wasted when demand drops and controllers remain idle
Solution Approach 1:
The system dynamically adjusts the number of active controllers based on real-time demand monitoring. When demand exceeds predefined thresholds, additional controllers are automatically provisioned to handle the load. When demand decreases below thresholds, controllers are automatically de-provisioned, ensuring optimal resource utilization at all times.
Solution Approach 2:
The system implements continuous feedback loops by monitoring demand metrics and using this information to automatically trigger provisioning or de-provisioning actions. The demand monitoring component continuously feeds information back to the provisioning system, enabling closed-loop control that optimizes resource allocation based on actual usage patterns.
3Reliability
If the number of application delivery controllers is increased to prevent overload, then performance degradation is prevented, but the system becomes less efficient when demand is low
Solution Approach 1:
The system transforms the static controller infrastructure into a dynamic system that automatically adapts its capacity based on real-time demand conditions. The automatic provisioning and de-provisioning mechanisms enable the system to maintain performance stability during peak demand while optimizing resource allocation during low-demand periods.
Solution Approach 2:
The system employs self-service automation to monitor performance metrics, detect demand changes, and automatically adjust controller allocation. This autonomous operation enables the system to maintain performance stability without manual intervention while simultaneously optimizing resource efficiency through automatic scaling decisions.
Data Source
AI summary
The present disclosure is directed to systems and method for providing a virtual appliance. One or more application delivery controller appliances intermediary to a plurality of clients and a plurality of servers perform a plurality of application delivery control functions on network traffic communicated between the plurality of clients and the plurality of servers. A virtual application delivery controller is deployed on a device intermediary to the plurality of clients and the plurality of servers. The virtual application delivery controller executing on the device performs one or more of the plurality of application delivery control functions on network traffic communicated between the plurality of clients and the plurality of servers.