Load Balancer Policy Sharing with Object Storage Lock Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current load balancing techniques do not consider the characteristics of an underlying object store, leading to unnecessarily large loads on the system and reduced performance.
Innovation Solution
A method that analyzes data management factors within an object-based storage system to determine a data management policy, including the location of locks, and shares this policy with a load balancer to optimize request routing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If current load balancing techniques are used without considering object store characteristics, then the load balancer operates with simple routing logic, but the system experiences unnecessarily large loads and reduced performance
Solution Approach 1:
The patent introduces a location and cache manager as an intermediary component that sits between the load balancer and the object store. This manager handles the complex tasks of tracking data locations, lock locations, and cache status, while providing simplified information to the load balancer. The load balancer remains relatively simple but benefits from the intelligent routing decisions enabled by the intermediary manager, thus resolving the contradiction between performance improvement and complexity increase.
2Productivity
If load balancer routes requests without knowledge of data location and lock ownership, then routing decisions are made quickly and simply, but request routing is inefficient and creates contention
Solution Approach 1:
The location and cache manager performs preliminary actions by pre-tracking and maintaining up-to-date information about data locations, lock ownership, and cache status before requests arrive. This advance preparation allows the load balancer to make informed routing decisions without incurring additional lookup delays during request processing, thus improving routing efficiency without increasing processing time.
Solution Approach 2:
The system implements feedback mechanisms where the location and cache manager continuously monitors and updates information about the state of the object store (lock locations, data positions, cache status). This feedback loop enables the load balancer to adapt its routing decisions based on current system state, optimizing request routing efficiency while maintaining timely response through the use of current information.
3Productivity
If lock tracking information is shared with load balancer, then request routing can avoid contention and improve performance, but the system requires additional mechanisms to track and communicate lock locations
Solution Approach 1:
The location and cache manager serves multiple functions simultaneously: it tracks data locations, monitors lock ownership, manages cache status, and provides routing information to the load balancer. By consolidating these diverse functions into a single multi-functional component, the system achieves improved throughput through better-informed routing while minimizing the increase in overall system architecture complexity.
Data Source
AI summary
In one general embodiment, a computer-implemented method includes analyzing a plurality of data management factors within an object-based storage system, including tracking which of a plurality of proxy servers within the object-based storage system currently holds a lock; determining a data management policy for predetermined data within the object-based storage system, based on the analyzing, including identifying a current location of the lock within one of the plurality of proxy servers within the object-based storage system; and sharing the data management policy for the predetermined data, including the current location of the lock within the object-based storage system, with a load balancer associated with the object-based storage system.