Performance-Aware Backup Controller Selection in HA Containers
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Solution Overview
Problem
In virtualized computing environments, existing high availability mechanisms for containerized systems often fail to select the most performance-aware backup container when a master controller becomes unavailable, leading to sub-optimal performance and potential system downtime.
Innovation Solution
A performance-aware controller selection procedure is implemented, where backup containers are ranked based on performance metrics, and the highest-ranked backup container is elected to take over as the master, ensuring minimal latency and optimal performance by prioritizing on-premises containers for seamless operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing high availability mechanisms are used for containerized systems, then system availability is maintained through backup containers, but the selection of backup container does not consider performance metrics, leading to sub-optimal performance
Solution Approach 1:
The patent changes the selection parameter from simple availability to performance-aware selection by introducing performance metrics (latency, throughput, resource utilization) as key criteria. The system evaluates backup containers based on multiple performance parameters and selects the optimal backup, thereby resolving the contradiction between maintaining availability and ensuring optimal performance.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring performance metrics of backup containers and using this information to make informed selection decisions. The performance evaluation feedback loop ensures that the selected backup container not only maintains availability but also delivers optimal system performance.
2Reliability
If any backup container is selected to take over master controller operations, then system availability is maintained, but selection without performance awareness leads to potential system downtime and sub-optimal operation
Solution Approach 1:
The system performs preliminary performance evaluation and ranking of backup containers before failure occurs. By pre-assessing performance metrics and establishing a ranked list of backup containers, the system can quickly select the optimal backup without time-consuming evaluation during failure events, thus maintaining high availability while minimizing downtime.
Solution Approach 2:
The patent introduces performance metrics as selection parameters and changes the selection criterion from arbitrary or round-robin selection to performance-based selection. This parameter change enables the system to minimize downtime by selecting the best-performing backup container that can immediately take over operations.
3Ease of operation
If backup containers are selected without performance metrics, then selection process is simple, but system efficiency and performance are compromised
Solution Approach 1:
The system implements self-service by having backup containers autonomously report their performance metrics and by automatically evaluating and ranking them based on predefined criteria. This self-service mechanism maintains ease of operation while improving system efficiency, as the selection process remains automated and does not require complex manual intervention.
Solution Approach 2:
The patent changes the selection parameters to include performance metrics while maintaining automated evaluation processes. By introducing measurable performance parameters and automated scoring mechanisms, the system balances simplicity of operation with improved system efficiency, avoiding the need for complex manual assessment procedures.
Data Source
AI summary
Embodiments described herein provide for an election procedure, in a high availability (“HA”) environment, for a backup controller to assume operations performed by a master controller in the event that the master controller becomes unreachable. The master controller may be associated with (e.g., provisioned on) the same set of hardware as one or more worker nodes, and may control operation of the one or more worker nodes. The election procedure may be performed based on performance metrics, location, or efficiency metrics associated with candidate backup controllers (e.g., cloud-based backup controllers), including performance of communications between particular backup controllers and the one or more worker nodes.