Storage Node Reliability Scoring for Automatic Master Promotion
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Solution Overview
Problem
In storage systems with a cluster configuration, selecting an optimal worker node for master promotion is challenging due to the lack of automated tools for evaluating node reliability based on failure history and operation status.
Innovation Solution
The storage system includes a score calculation unit in worker nodes and a promotion node selection unit in master nodes, which calculate and compare scores for each worker node based on their failure history and operation status to automatically select the most reliable node for master promotion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual maintenance operation is used to replace a failed master node, then the system can maintain master node redundancy, but the process requires user intervention and time to select and replace the node
Solution Approach 1:
The system pre-calculates and stores promotion scores for all worker nodes based on their failure histories and operation statuses before a failure occurs. When a master node fails, the system can immediately query the pre-computed scores to identify the optimal promotion candidate, eliminating the need for real-time manual evaluation and reducing maintenance time.
Solution Approach 2:
The system automatically selects the worker node with the highest promotion score to replace the failed master node without requiring user intervention. The automatic master promotion function queries the promotion scores, determines the optimal candidate, and executes the promotion process autonomously, reducing both time loss and operational complexity.
2Productivity
If worker nodes with past failures are selected for master promotion, then the system can maintain continuous operation, but the risk of repeated failures increases
Solution Approach 1:
The system continuously monitors failure histories and operation statuses of all worker nodes, using this feedback to dynamically calculate and update promotion scores. When a master node fails, the system queries the updated scores that reflect current node reliability states, ensuring that nodes with repeated failures are excluded from promotion while favoring nodes with clean operational histories.
3Extent of automation
If automated score-based selection is implemented for master promotion, then the optimal worker node can be automatically selected, but the system complexity increases
Solution Approach 1:
The score calculation function is executed in advance during normal system operation, pre-computing promotion scores for all worker nodes and storing them in the promotion score storage unit. This preliminary computation eliminates the need for complex real-time calculations during failure events, reducing the computational burden and system complexity during critical promotion moments.
4Measurement precision
If promotion scores are calculated based on failure history and operation status, then node reliability can be objectively evaluated, but the measurement and evaluation process becomes more complex
Solution Approach 1:
The system pre-establishes the scoring criteria and calculation methods during normal operation, continuously accumulating failure history and operation status data. When promotion is needed, the system simply queries the pre-computed scores rather than performing complex real-time evaluation, significantly simplifying the measurement and evaluation process while maintaining objective reliability assessment.
Data Source
AI summary
A worker node included in a storage system 1 includes a score calculation unit 31 that calculates a score of the worker node based on a failure history and an operation status of the worker node, and a master node (P) includes a promotion node selection unit 52 that compares scores for each worker node when a failure occurs in one of master nodes and selects, based on the scores, a worker node to be promoted to a master node instead of the master node in which the failure has occurred.