Cluster Health-Based Load Sharing and Backup Across Clusters
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Solution Overview
Problem
Existing load balancing technologies cannot perform inter-cluster load balancing, traffic sharing, and backup among multiple clusters, leading to inefficiencies and reduced reliability and data security.
Innovation Solution
A method and apparatus for inter-cluster load balancing and backup that periodically monitor cluster health, divide clusters into healthy and unhealthy groups based on node survival, and perform load sharing and backup according to cluster weights and priorities, using modes like multi-master, multi-standby, and master modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If load balancing is performed only within the same cluster, then intra-cluster load balancing is achieved, but inter-cluster load balancing cannot be implemented
Solution Approach 1:
The system divides clusters into primary clusters and backup clusters, with each cluster maintaining independent load balancing capabilities. This segmentation allows inter-cluster load balancing to be implemented by selectively routing traffic between primary and backup clusters based on health status, without requiring complete architectural redesign of existing intra-cluster load balancing mechanisms.
Solution Approach 2:
A health monitoring module acts as an intermediary between load balancers and clusters. This mediator monitors cluster health status and provides real-time feedback to load balancers, enabling dynamic traffic routing decisions across clusters while maintaining the existing load balancing architecture and avoiding direct complex inter-cluster coupling.
2Productivity
If traffic sharing mode is used among clusters, then resource utilization is improved, but system reliability decreases when primary clusters fail
Solution Approach 1:
The system dynamically switches between traffic sharing mode and cluster backup mode based on real-time health monitoring. When primary clusters are healthy, traffic sharing maximizes resource utilization. When primary clusters fail, the system automatically transitions to cluster backup mode, routing traffic to backup clusters to maintain system availability. This dynamic adaptation resolves the contradiction between resource utilization and reliability.
Solution Approach 2:
The system changes the operational parameter of cluster mode (from traffic sharing to backup mode) based on health status. By monitoring cluster health parameters and dynamically adjusting the traffic routing strategy, the system optimizes resource utilization during normal operation while ensuring reliability during failures, effectively resolving the contradiction between these two objectives.
3Reliability
If cluster backup mode is implemented, then system reliability is improved, but load balancing efficiency decreases due to additional monitoring and switching overhead
Solution Approach 1:
Backup clusters are pre-configured and ready to accept traffic before failures occur. The health monitoring module continuously monitors cluster status in advance, and pre-established routing rules enable rapid failover without complex real-time decision-making during failures. This preliminary preparation maintains high reliability while minimizing the overhead impact on load balancing efficiency.
Solution Approach 2:
The health monitoring module provides continuous feedback on cluster status to the load balancing system. This feedback mechanism enables automatic, rule-based routing decisions without requiring complex real-time optimization algorithms, thus maintaining high reliability through automated failover while avoiding excessive computational overhead that would reduce load balancing efficiency.
4Adaptability or versatility
If multiple clusters are monitored and managed centrally, then inter-cluster load balancing is achieved, but system complexity and management difficulty increase
Solution Approach 1:
The system segments inter-cluster management into independent modular components: health monitoring module, load balancing module, and traffic routing module. Each module performs a specific function and can be independently configured and managed. This segmentation achieves comprehensive inter-cluster management capability while reducing overall system complexity through modular design, as each module can be developed, deployed, and maintained separately.
Data Source
AI summary
A cluster-based load sharing and backup method and apparatus is provided. The method includes: periodically monitoring clusters, and determining a healthy cluster group and an unhealthy cluster group according to the health conditions of the clusters; according to the weights and the priorities of the clusters, carrying out load sharing and backup on the traffic of the unhealthy cluster group to the healthy cluster group; receiving and analyzing a client request to obtain an execution task, and determining a target cluster from the healthy cluster group, and a target server node; and sending the execution task to the target server node in the target cluster for execution, and returning an execution result, wherein load sharing and backup comprise performing inter-cluster load sharing and backup, and intra-cluster load sharing and backup according to the health states of the clusters and server nodes in the clusters.