High Availability Cloud Resource Borrowing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional high availability (HA) systems based on passive redundancy face performance degradation due to primary node failures caused by resource shortages, leading to bottlenecks and decreased system performance when backup nodes take over.
Innovation Solution
A method for a high availability cloud architecture system (HACAS) dynamically allocates resources by designating a primary node and backup nodes, borrowing resources from other nodes and redistributing workloads to prevent primary node overload and failure, utilizing an HA coordinator to manage resource usage and workload distribution based on node readiness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If passive redundancy is used with backup nodes, then system reliability is improved, but system performance deteriorates due to bottlenecks during takeover
Solution Approach 1:
The system performs preliminary actions by proactively detecting resource constraints on the primary node before failure occurs. The HA coordinator monitors resource usage and initiates resource borrowing from backup nodes in advance, preventing primary node failure and avoiding the performance bottleneck that would occur during a reactive takeover process.
Solution Approach 2:
The system implements dynamic resource allocation where backup nodes can temporarily lend resources to the primary node based on real-time resource availability and demand. This dynamic approach allows the system to adapt resource distribution flexibly, maintaining high performance while preserving the reliability benefits of passive redundancy.
2Reliability
If resources are allocated to backup nodes, then system reliability is improved, but resource availability for primary node deteriorates
Solution Approach 1:
The system implements dynamic resource allocation where backup nodes can temporarily lend resources to the primary node based on real-time resource availability and demand. This dynamic approach allows the system to adapt resource distribution flexibly, maintaining high performance while preserving the reliability benefits of passive redundancy.
Solution Approach 2:
The system changes the resource allocation parameters dynamically based on system state. When the primary node experiences resource constraints, the HA coordinator adjusts resource allocation by allowing backup nodes to lend resources, effectively changing the resource availability parameter without compromising the underlying passive redundancy architecture.
3Productivity
If primary node handles more computational tasks, then productivity is improved, but reliability deteriorates due to lack of resources
Solution Approach 1:
The HA coordinator implements continuous monitoring of primary node resource usage and provides feedback to detect resource constraints. This feedback mechanism allows the system to identify when the primary node is approaching resource limits and trigger resource borrowing from backup nodes, preventing failure while maintaining high computational throughput.
Solution Approach 2:
The system performs preliminary actions by proactively detecting resource constraints on the primary node before failure occurs. The HA coordinator monitors resource usage and initiates resource borrowing from backup nodes in advance, preventing primary node failure and avoiding the performance bottleneck that would occur during a reactive takeover process.
Data Source
AI summary
Methods, computer program products, and systems are presented. The methods include, for instance: designating virtual machines including resources as respective node to service computational tasks directed to a high availability cloud architecture system; a primary node suffering from a lack of resources gets more resources as borrowed from other nodes that are present as a fail-safe of the primary node; and a resource usage log is kept to determine whether or not the primary node needs resources from other nodes later.