Cluster Pool Refresh Using Configuration Hashes
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Solution Overview
Problem
Resource pools face challenges in maintaining optimal configuration consistency after a change, leading to the provision of stale resource units to users due to the lag between configuration updates and actual resource unit changes, resulting in suboptimal service and potential starvation.
Innovation Solution
Implement a method and system where resource pool managers generate and store configuration hashes for new and existing clusters, periodically comparing these hashes to identify and delete stale clusters, and create new clusters with the updated configuration, ensuring real-time availability of up-to-date resource units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the resource pool maintains a predetermined number of resource units ready for use, then the service availability is improved, but the configuration consistency deteriorates when updates are applied
Solution Approach 1:
The system performs preliminary actions by creating new resource units with the updated configuration before the old configuration is fully deployed. The resource pool manager proactively generates new units with the latest configuration settings, ensuring that when units are claimed, they reflect the current configuration state, thus maintaining configuration consistency while preserving service availability.
Solution Approach 2:
The system discards old configuration data and creates new resource units with updated configurations. When the configuration changes, the resource pool manager identifies and removes old units with stale configurations and replaces them with new units that have the current configuration, thereby maintaining consistency without disrupting service continuity.
2Stability of the object's composition
If new resource units are created immediately when configuration changes, then the configuration consistency is improved, but the resource pool size decreases temporarily
Solution Approach 1:
The resource pool manager proactively creates new resource units with updated configurations before the old units are removed. This preliminary creation ensures that new units are ready to be claimed immediately, maintaining the resource pool size while ensuring configuration consistency. The manager balances the timing of unit creation and removal to prevent temporary size reductions.
3Ease of operation
If the resource pool manager waits for configuration changes to propagate, then the operational simplicity is improved, but the user experience deteriorates due to stale units
Solution Approach 1:
The resource pool manager implements a feedback mechanism that continuously monitors the configuration state and automatically adjusts the resource unit creation and removal processes. When configuration changes are detected, the manager receives feedback about the new configuration state and responds by creating new units with the updated configuration and removing old units, ensuring users always receive up-to-date resources without manual intervention.
Solution Approach 2:
The system performs self-service by automatically detecting configuration changes and managing the lifecycle of resource units without external intervention. The resource pool manager autonomously creates new units with updated configurations, removes old units, and maintains the overall health of the resource pool, eliminating the need for manual operations while ensuring users receive current configurations.
4Measurement precision
If manual cluster deletion is used to update configurations, then the control precision is improved, but the productivity deteriorates due to manual intervention
Solution Approach 1:
The resource pool manager implements self-service automation where the system automatically detects configuration changes, identifies old units with stale configurations, creates new units with updated configurations, and removes old units without manual intervention. This automated self-service process maintains precise control over configuration updates while dramatically improving productivity by eliminating manual operations.
Solution Approach 2:
The system employs feedback mechanisms that automatically monitor configuration states and trigger appropriate actions. When configuration changes are detected, the manager receives feedback and automatically executes the sequence of creating new units and removing old units, maintaining precise control over which units are updated and when, while eliminating the time-consuming manual intervention required in traditional approaches.
Data Source
AI summary
Systems and methods are disclosed for replacing stale clusters in a cluster pool. An example method includes changing a configuration status of a resource pool managed by a resource pool manager from a first configuration to a second configuration. The resource pool may comprise a plurality of clusters. A portion of the plurality of clusters may be configured according to the first configuration and may store a first hash encoding configuration fields for the first configuration. The resource pool manager device may procure, at predetermined periods until a discontinuation cue, new clusters to include as part of the resource pool. Each new cluster procured at each predetermined period can be configured according to the second configuration. A second hash encoding configuration fields for the second configuration may be stored in each new cluster. Clusters that are not storing the second hash may be deleted from the resource pool.