OpenClaw 分布式Agent协调

一个Agent干活太慢？那就一百个一起干。但怎么让它们不互相打架，是个技术活。

📌 功能介绍

分布式Agent协调是OpenClaw面向大规模任务的集群编排能力。当单个Agent处理不过来时（比如需要同时监控1000个网站、处理10000个文档），你可以部署多个Agent节点，通过OpenClaw的协调机制实现任务分发、负载均衡和故障转移。就像一支交响乐队——每个乐手独立演奏，但所有人在指挥下形成完美的和声。

🛠️ 使用方法

1. 集群部署

# cluster-config.yaml
cluster:
  name: "miaoquai-prod"
  region: "asia-east-1"
  
  nodes:
    - id: "node-01"
      host: "10.0.1.1"
      role: "coordinator"  # 主节点
      capacity: 20
    - id: "node-02"
      host: "10.0.1.2"
      role: "worker"
      capacity: 10
    - id: "node-03"
      host: "10.0.1.3"
      role: "worker"
      capacity: 10
  
  consensus:
    protocol: "raft"  # raft | paxos | custom
    electionTimeout: "5s"
    heartbeatInterval: "1s"
    
  discovery:
    method: "static"  # static | dns | k8s
    nodes: ["node-01:8080", "node-02:8080", "node-03:8080"]

2. 任务分发策略

# task-distribution-config.yaml
distribution:
  strategy: "adaptive"  # round-robin | hash | least-loaded | adaptive
  
  adaptive:
    rebalanceInterval: "30s"
    threshold: 0.8  # 负载超过80%时重新分配
  
  taskQueue:
    type: "priority"
    maxPending: 10000
    retryPolicy:
      maxAttempts: 3
      backoff: "exponential"
      maxBackoff: "5m"
  
  routing:
    affinity: true  # 同类型任务倾向分配到同一节点
    antiAffinity: false
    locality: "zone"  # same-zone | cross-zone | any

3. 故障转移

# fault-tolerance-config.yaml
faultTolerance:
  healthCheck:
    interval: "10s"
    timeout: "5s"
    unhealthyThreshold: 3
    healthyThreshold: 2
  
  failover:
    strategy: "active-passive"  # active-active | active-passive
    failoverTime: "30s"
    
    taskMigration:
      enabled: true
      migrateInProgress: true  # 迁移进行中的任务
      checkpointInterval: "1m"
  
  circuitBreaker:
    enabled: true
    failureThreshold: 5
    recoveryTimeout: "60s"
    halfOpenRequests: 3

🏆 最佳实践

集群规模建议

任务规模	节点数	推荐架构
轻量（<100任务/天）	1-2节点	单节点 + 冷备
中等（100-1000/天）	3-5节点	Raft集群
大规模（>1000/天）	5-20节点	多区域 + 分片

💻 代码示例

分布式任务编排

const { OpenClawCluster, TaskRouter } = require('@openclaw/cluster');

async function distributeTask(task) {
  const cluster = new OpenClawCluster({
    configPath: './cluster-config.yaml',
    autoDiscovery: true
  });
  
  // 1. 获取集群状态
  const status = await cluster.getStatus();
  console.log(`集群节点: ${status.activeNodes}/${status.totalNodes}`);
  console.log(`活跃任务: ${status.activeTasks}`);
  
  // 2. 智能路由
  const router = new TaskRouter(cluster);
  const targetNode = await router.route(task, {
    strategy: 'least-loaded',
    constraints: {
      requireGPU: task.needsGPU,
      preferSameZone: true,
      maxLatency: '100ms'
    }
  });
  
  // 3. 分发任务
  const job = await cluster.submitTask(targetNode, {
    type: task.type,
    payload: task.payload,
    priority: task.priority || 'normal',
    timeout: task.timeout || '10m',
    checkpoint: true,
    onProgress: (progress) => {
      console.log(`进度: ${progress.percent}% (${progress.message})`);
    }
  });
  
  // 4. 等待结果（支持故障转移）
  const result = await job.wait({
    failover: true,
    timeout: task.timeout || '10m'
  });
  
  return result;
}

MapReduce模式

async function mapReduce(cluster, documents, mapFn, reduceFn) {
  // Map阶段：分发到各节点并行处理
  const mapTasks = documents.map((doc, i) => ({
    id: `map-${i}`,
    type: 'map',
    payload: { document: doc, mapFunction: mapFn },
    priority: 'normal'
  }));
  
  // 并行提交所有map任务
  const mapResults = await Promise.allSettled(
    mapTasks.map(task => cluster.submitTask(task))
  );
  
  // 收集成功的map结果
  const successfulMaps = mapResults
    .filter(r => r.status === 'fulfilled')
    .map(r => r.value.data);
  
  console.log(`Map完成: ${successfulMaps.length}/${mapTasks.length}`);
  
  // Reduce阶段：合并结果
  const reduceTask = await cluster.submitTask({
    id: 'reduce-0',
    type: 'reduce',
    payload: {
      inputs: successfulMaps,
      reduceFunction: reduceFn
    },
    priority: 'high',
    requireNode: 'coordinator'  // 在主节点执行reduce
  });
  
  const finalResult = await reduceTask.wait();
  return finalResult.data;
}

🔗 相关链接

📅 更新时间：2026-05-11 | 📖 更多OpenClaw教程请访问 工具教程索引