Cloud Micro-Service Controller for Cross-Site Load Balancing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current infrastructure management systems are limited in managing resources across multiple sites via a single controller, as on-premise infrastructure controllers can only control resources within the same data center, lacking the ability to balance load and allocate resources effectively across different locations.
Innovation Solution
Implementing a cloud micro-service controller that provides load balancing and automatic resource allocation across multiple infrastructure controllers, using Blueprints to manage resources and a solver engine to translate these descriptions into actionable steps for resource instantiation and workload balancing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single on-premise infrastructure controller manages resources within one data center, then local resource control is simple and direct, but the controller cannot balance load or allocate resources effectively across multiple locations
Solution Approach 1:
The system segments the infrastructure controller into multiple distributed controllers, each managing resources at different sites. This allows each controller to maintain simple local control while collectively providing cross-site resource management capability through the cloud manager that coordinates between distributed controllers.
Solution Approach 2:
A cloud manager acts as an intermediary between multiple on-premise infrastructure controllers, enabling resource allocation and load balancing across sites without requiring direct complex interconnections between each controller pair. The cloud manager mediates communication and coordination.
2Productivity
If infrastructure controllers operate independently within their own data centers, then each controller maintains simple local operation, but the system lacks centralized coordination for load balancing and resource allocation
Solution Approach 1:
The cloud manager provides universal coordination functionality across all distributed controllers, handling load balancing, resource allocation, and workload migration decisions. This multi-functional coordinator improves system productivity without requiring each individual controller to implement complex coordination logic.
Solution Approach 2:
The system implements feedback mechanisms where the cloud manager monitors resource utilization across all sites and adjusts workload distribution accordingly. Controllers report their load states to the cloud manager, which then makes informed decisions about resource allocation and migration to optimize overall system productivity.
3Extent of automation
If workloads are manually transferred between controllers, then resource balancing can be achieved, but the process is time-consuming and labor-intensive
Solution Approach 1:
The system enables self-service automation where the cloud manager automatically detects workload imbalances and initiates transfers without manual intervention. Controllers autonomously report their states and execute workload migrations based on decisions made by the cloud manager, reducing time loss while achieving effective resource balancing.
Solution Approach 2:
The cloud manager proactively monitors resource utilization patterns and pre-positions workloads on optimal controllers before peak load conditions occur. This preliminary action allows the system to respond more quickly to changing conditions, reducing overall workload migration time when adjustments are needed.
Data Source
AI summary
A system to facilitate infrastructure management is described. The system includes one or more processors and a non-transitory machine-readable medium storing instructions that, when executed, cause the one or more processors to execute an infrastructure management controller to automatically balance utilization of infrastructure resources between a plurality of on-premise infrastructure controllers.