Self-Recoverable Distributed Cluster Node Recovery Mechanism
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Solution Overview
Problem
Existing methods for recovering distributed clustered systems after a host machine failure are cumbersome and require manual intervention, especially in large-scale environments where thousands of host machines may need to be recovered simultaneously, leading to disruptions and inefficiencies.
Innovation Solution
An automatic cluster recovery mechanism that identifies affected nodes, prepares them with necessary components and configurations, initiates heartbeats to register with the cluster network, and reestablishes connections, allowing nodes to restart services without external intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual intervention methods are used for recovering distributed clustered systems, then recovery can be performed with simple system architecture, but recovery time and operational complexity increase significantly
Solution Approach 1:
The system implements self-service through automated recovery mechanisms where the cluster management system automatically detects node failures, identifies affected distributed clustered systems, and orchestrates recovery processes without requiring manual intervention. The system monitors itself and performs self-healing operations including restarting services and reestablishing connections.
Solution Approach 2:
The system applies preliminary action by pre-configuring recovery procedures and maintaining system state information before failures occur. When a node fails, the system has already prepared recovery scripts and configuration data, enabling immediate automated recovery rather than requiring manual setup after failure.
2Productivity
If automated recovery mechanisms are implemented, then recovery speed and efficiency improve, but system complexity and implementation difficulty increase
Solution Approach 1:
The system implements universality by creating a multi-functional cluster management system that combines failure detection, node identification, service management, and recovery orchestration into a single automated platform. This universal system handles multiple types of failures and recovery scenarios through unified mechanisms, improving productivity while managing complexity through consolidation.
Solution Approach 2:
The system applies feedback through continuous monitoring of node health status and automatic adjustment of recovery processes. The cluster management system receives feedback from heartbeat signals and node status reports, then automatically initiates appropriate recovery actions based on the detected failure conditions, enabling efficient automated recovery.
3Reliability
If comprehensive node preparation and connection reestablishment procedures are implemented, then system reliability improves, but operational complexity increases
Solution Approach 1:
The system implements self-service by automatically performing comprehensive node preparation and connection reestablishment procedures without requiring operational intervention. The cluster management system autonomously executes recovery scripts, configures nodes, and reestablishes connections, maintaining high reliability while preserving operational simplicity.
Solution Approach 2:
The system applies segmentation by dividing the complex recovery process into distinct automated stages: failure detection, node identification, service component preparation, connection reestablishment, and verification. Each segment is handled automatically by the cluster management system, ensuring reliability while keeping operations simple through structured automation.
Data Source
AI summary
A mechanism is provided for automatically recovering one or more distributed cluster nodes on a host system. Responsive to the host system recovering, restoring, or restarting, a set of distributed clustered systems affected due to the reboot of the host system and details associated with each of the set of distributed clustered systems are identified. Using the details, a set of nodes that operate on the host system are identified. For each node: respective components and configurations are prepared; a heartbeat is initiated thereby causing the node to register with a cluster network and identify peers within their associated distributed clustered system; a determination is made as to whether the node has reestablished connection with its associated distributed clustered system; and, responsive to the node reestablishing connection with its associated distributed clustered system, service components are started on the node.