Gateway Appliance Load Balancing via Dynamic Rebalancing

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Solution Overview

Problem

Existing data replication systems in cloud computing environments face inefficiencies and data loss due to uneven workload distribution and appliance overload, particularly when multiple appliances are used, as they lack dynamic load balancing and resiliency mechanisms to handle changes in load and appliance failures.

Innovation Solution

Implement a method for intelligent and automatic load balancing and resiliency by evaluating replication loads across multiple gateway appliances, rebalancing workloads based on relative differences in load scores, and dynamically reallocating workloads to prevent overload and ensure data integrity in case of appliance failures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If multiple gateway appliances are used for data replication, then replication capacity and availability are improved, but workload distribution becomes uneven and appliances become overloaded

Engineering Contradiction:

Improvereplication capacityVSAvoidworkload distribution

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system dynamically evaluates replication loads on gateway appliances and automatically rebalances workloads based on real-time load scores. The load balancing mechanism continuously monitors evaluation factors (such as number of replication streams, data volume, replication rate) and redistributes workloads to prevent overload, ensuring optimal resource utilization across multiple appliances.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system implements a feedback mechanism where gateway appliances report their replication load metrics to a controller, which calculates load scores and triggers workload rebalancing when thresholds are exceeded. This closed-loop feedback ensures that workload distribution is continuously optimized based on actual appliance performance and capacity.

Inventive Principle:

Principle #23Feedback

2Reliability

If manual workload monitoring and balancing is implemented, then workload distribution control is improved, but system complexity and operational overhead increase

Engineering Contradiction:

Improveworkload distribution controlVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The gateway appliances perform self-evaluation of their replication loads by monitoring their own performance metrics. The system automatically calculates load scores and executes workload rebalancing without requiring manual intervention. This self-service approach reduces operational overhead while maintaining reliable workload distribution control.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces manual mechanical workload management with automated software-based load balancing. Instead of human operators manually monitoring and adjusting workloads, the system uses algorithmic evaluation of replication parameters to automatically distribute workloads, reducing complexity and operational burden.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Device complexity

If replication workloads are not dynamically balanced, then system simplicity is maintained, but data loss and downtime increase during appliance failures

Engineering Contradiction:

Improvesystem simplicityVSAvoiddata integrity

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The system proactively evaluates replication loads and identifies potential overload conditions before they lead to data loss. By continuously monitoring evaluation factors and calculating load scores, the system can preemptively rebalance workloads or trigger failover procedures to protect data integrity, preventing failures rather than reacting to them.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements redundancy and load distribution mechanisms that provide a buffer against appliance failures. By distributing workloads across multiple gateway appliances and maintaining real-time monitoring, the system creates a safety margin that prevents single appliance failures from causing data loss, cushioning the system against catastrophic failures.

Inventive Principle:

Principle #11Beforehand cushioning (Prior cushioning)

Data Source

PatentUS11704164B1Intelligent and automatic load balancing of workloads on replication appliances based on appliance load scores

Publication Date: 2023.07.18 COHESITY INC

AI summary

Various systems and methods are provided in which a replication process is initiated between a primary site and a recovery site, each having plurality of gateway appliances. Replication loads are evaluated for each given gateway appliance of the plurality of gateway appliances. If a determination is made that at least one gateway appliance of the plurality of gateway appliances is not overloaded, the plurality of gateway appliances are sorted based on replication loads respectively associated with each gateway appliance, and a determination is made as to whether a relative difference in replication loads between a gateway appliance having a highest replication load and a gateway appliance having a lowest replication load exceeds a difference threshold to determine whether the replication workloads between the gateway appliances should be rebalanced.