賢者大叔的容器修煉手札 第 30 篇

xk6-disruptor 實戰：真正的混沌風暴來襲 ⚡🎭

今日目的：從模擬混沌到真實混沌，掌握 xk6-disruptor 的威力
理解 Kubernetes 原生混沌工程的精髓
在受控環境中釋放真正的「混沌之力」

🎯 為什麼需要 xk6-disruptor？

傳統負載測試 vs 混沌工程

為什麼傳統壓測「太完美」是個問題？
你有沒有想過，為什麼生產環境總是出現測試時沒遇到的問題？

傳統壓測的盲點：

• 🎭 假面舞會效應：測試環境太「乖巧」，沒有真實世界的「意外」
• 🏖️ 度假村症候群：單節點 KinD 就像住五星級飯店，現實卻是野外求生
• 🎪 馬戲團表演：應用太簡單，就像訓練有素的馬戲團，但現實是野生動物園

一般壓測結果可能如下圖

🤔 為什麼結果這麼「完美」？
昨天的測試結果顯示 100% 成功率，這其實暴露了一個問題：

• 沒有真正的故障注入 - 只是模擬了負載，沒有真正破壞系統
• 測試環境太理想 - KinD 單節點，沒有網絡分區、資源競爭等真實問題
• 應用太簡單 - 沒有複雜的依賴關係和狀態管理

xk6-disruptor 的革命性思維

🏗️ 基礎設施：KinD + MetalLB 的黃金組合

為什麼需要多節點？
想像一下：

• 單節點 = 一個人的獨角戲 🎭
• 多節點 = 交響樂團的協奏 🎼

為什麼需要 LoadBalancer？
首先 load balacner 的話就是需要多節點，正且 KinD 能很方便的模擬這多節點環境。

# kind-config.yaml - 打造真實的「小宇宙」
kind: Cluster
apiVersion: kind.x-k8s.io/v1alpha4
nodes:
- role: control-plane  # 指揮家
  kubeadmConfigPatches:
  - |
    kind: InitConfiguration
    nodeRegistration:
      kubeletExtraArgs:
        node-labels: "ingress-ready=true"
  extraPortMappings:    # 對外的窗口
  - containerPort: 80
    hostPort: 80
    protocol: TCP
  - containerPort: 443
    hostPort: 443
    protocol: TCP
- role: worker          # 演奏者 1
- role: worker          # 演奏者 2

# deployments/demo-app/service.yaml
apiVersion: v1
kind: Service
metadata:
  name: demo-service
  labels:
    app: demo-app
spec:
  selector:
    app: demo-app
  ports:
  - name: http
    port: 8080
    targetPort: 80
  type: LoadBalancer
---
apiVersion: v1
kind: Service
metadata:
  name: demo-service-v1
  labels:
    app: demo-app
    version: v1
spec:
  selector:
    app: demo-app
    version: v1
  ports:
  - name: http
    port: 8080
    targetPort: 80
  type: LoadBalancer
---
apiVersion: v1
kind: Service
metadata:
  name: demo-service-v2
  labels:
    app: demo-app
    version: v2
spec:
  selector:
    app: demo-app
    version: v2
  ports:
  - name: http
    port: 8080
    targetPort: 80
  type: LoadBalancer

但 KinD 的 service 網路如果需要啟用 LoadBalancer 類型則需要安裝設定MetalLB。

MetalLB：LoadBalancer 的魔法師 🎩

在雲端環境中，LoadBalancer 是理所當然的存在，但在本地環境中：

# 沒有 MetalLB 的悲劇
kubectl get svc
NAME           TYPE           EXTERNAL-IP   PORT(S)
demo-service   LoadBalancer   <pending>     8080:30123/TCP

# 有了 MetalLB 的奇蹟，能取得 EXTERNAL-IP
kubectl get svc
NAME           TYPE           EXTERNAL-IP     PORT(S)
demo-service   LoadBalancer   172.18.255.1   8080:30123/TCP

⚔️ xk6-disruptor 實戰配置

1. 安裝 k6 與 xk6-disruptor

go install go.k6.io/xk6/cmd/xk6@latest
xk6 build --with github.com/grafana/xk6-disruptor

會在專案目錄產生一個k6的執行檔。

2. 🎯 武器一：Pod Disruption - 容器級的「暗殺術」

// pod-disruption.js - 容器級故障注入
// 這不是普通的測試，這是「生死時速」
export function disrupt() {
  const podDisruptor = new PodDisruptor(selector);
  
  // 🔪 暗殺 50% 的 Pods - 模擬節點故障
  podDisruptor.injectPodKillFault({
    count: 2,  // 精準打擊
  });
  
  // 💪 CPU 折磨術 - 模擬資源競爭
  podDisruptor.injectStressFault({
    count: 1,
    options: {
      stressors: {
        cpu: {
          workers: 2,
          load: 80,  // 80% CPU 壓力
        },
      },
      duration: '30s',
    },
  });
}

這模擬了什麼真實場景？

• 🏥 節點故障：就像醫院突然停電，病房設備需要緊急轉移
• 🚗 資源競爭：就像高速公路塞車，每台車都在搶道

3. 🌐 武器二：Service Disruption - 網路級的「魅惑術」

// 階段式混沌注入 - 就像慢性毒藥
const faultStages = [
  { errorRate: 0.1, delay: '100ms', duration: '60s' },  // 輕微不適
  { errorRate: 0.3, delay: '300ms', duration: '60s' },  // 明顯症狀
  { errorRate: 0.5, delay: '500ms', duration: '60s' },  // 嚴重病症
  { errorRate: 0.2, delay: '200ms', duration: '60s' },  // 康復階段
];

這就像餐廳的服務品質測試：

• 🍽️ 10% 錯誤率：偶爾上錯菜，客人還能接受
• 🍽️ 30% 錯誤率：經常出錯，客人開始抱怨
• 🍽️ 50% 錯誤率：一半訂單有問題，客人準備離開
• 🍽️ 回到 20%：看看客人是否願意給第二次機會

4. 🔥🔥 武器三：Advanced Scenarios - 多重宇宙的「終極試煉」
   advanced-scenarios.js - 多場景並行測試

export const options = {
  scenarios: {
    baseline_load: {     // 平靜的日常
      executor: 'constant-vus',
      vus: 10,
      duration: '10m',
    },
    spike_load: {        // 突如其來的風暴
      executor: 'ramping-vus',
      stages: [
        { duration: '30s', target: 50 },  // 風暴來襲
        { duration: '1m', target: 50 },   // 暴風眼
        { duration: '30s', target: 0 },   // 風暴過後
      ],
      startTime: '4m',
    },
    pod_chaos: {         // 暗黑勢力
      startTime: '2m',
    },
    service_chaos: {     // 網路惡魔
      startTime: '6m',
    },
  },
};

import http from 'k6/http';
import { check, sleep } from 'k6';
import { PodDisruptor } from 'k6/x/disruptor';

export const options = {
  scenarios: {
    // 基線負載測試
    baseline_load: {
      executor: 'constant-vus',
      vus: 3,
      duration: '1m',
      exec: 'baselineTest',
    },
    // 混沌注入測試
    chaos_injection: {
      executor: 'shared-iterations',
      iterations: 1,
      vus: 1,
      exec: 'chaosTest',
      startTime: '30s',
    },
    // 故障後恢復測試
    recovery_test: {
      executor: 'constant-vus',
      vus: 2,
      duration: '1m',
      exec: 'recoveryTest',
      startTime: '2m',  // 調整避免重疊
    },
  },
  thresholds: {
    http_req_duration: ['p(95)<5000'],  // 放寬到 5 秒
    http_req_failed: ['rate<0.2'],      // 調整到 20%
    http_reqs: ['count>30'],            // 調整最小請求數
  },
};

// 配置參數
const TARGET_URL = __ENV.TARGET_URL || 'http://172.18.255.202:8080';
const NAMESPACE = __ENV.NAMESPACE || 'default';
const CHAOS_DURATION = __ENV.CHAOS_DURATION || '30s';
const FAULT_LEVEL = __ENV.FAULT_LEVEL || 'light';

// 故障配置
const FAULT_CONFIGS = {
  light: {
    averageDelay: '100ms',
    errorRate: 0.1,
    errorCode: 500,
  },
  medium: {
    averageDelay: '300ms',
    errorRate: 0.2,
    errorCode: 503,
  },
  heavy: {
    averageDelay: '1s',
    errorRate: 0.3,
    errorCode: 500,
  },
};

const currentFault = FAULT_CONFIGS[FAULT_LEVEL];

// 統計數據
let stats = {
  baseline: { requests: 0, failures: 0, totalDuration: 0 },
  chaos: { requests: 0, failures: 0, totalDuration: 0 },
  recovery: { requests: 0, failures: 0, totalDuration: 0 },
};

export function setup() {
  console.log('🎭 === OPTIMIZED K6 CHAOS ENGINEERING ===');
  console.log(`🎯 Target URL: ${TARGET_URL}`);
  console.log(`☸️  Kubernetes Namespace: ${NAMESPACE}`);
  console.log(`⏱️  Chaos Duration: ${CHAOS_DURATION}`);
  console.log(`💥 Fault Level: ${FAULT_LEVEL}`);
  
  // 健康檢查
  console.log('\n🏥 === HEALTH CHECK ===');
  let healthyChecks = 0;
  const totalChecks = 5;
  
  for (let i = 0; i < totalChecks; i++) {
    try {
      const response = http.get(TARGET_URL, { timeout: '10s' });
      if (response.status === 200) {
        healthyChecks++;
        console.log(`✅ Health check ${i+1}/${totalChecks}: OK (${Math.round(response.timings.duration)}ms)`);
      } else {
        console.log(`⚠️  Health check ${i+1}/${totalChecks}: Status ${response.status}`);
      }
    } catch (error) {
      console.log(`❌ Health check ${i+1}/${totalChecks}: Failed - ${error.message}`);
    }
    sleep(0.5);
  }
  
  const healthPercentage = (healthyChecks / totalChecks) * 100;
  console.log(`📊 Overall Health: ${healthPercentage}% (${healthyChecks}/${totalChecks})`);
  
  return { 
    healthy: healthyChecks >= 3, 
    healthPercentage: healthPercentage,
    startTime: Date.now() 
  };
}

// 基線測試
export function baselineTest() {
  const startTime = Date.now();
  
  try {
    const response = http.get(TARGET_URL, { timeout: '10s' });
    const duration = Date.now() - startTime;
    
    stats.baseline.requests++;
    stats.baseline.totalDuration += duration;
    
    const success = check(response, {
      'baseline: status is 200': (r) => r.status === 200,
      'baseline: response time < 3000ms': (r) => r.timings.duration < 3000,
      'baseline: has content': (r) => r.body && r.body.length > 0,
    });
    
    if (!success) {
      stats.baseline.failures++;
    }
    
  } catch (error) {
    stats.baseline.failures++;
    console.log(`❌ Baseline request failed: ${error.message}`);
  }
  
  sleep(1);
}

// 混沌測試期間的輔助函數
function testDuringChaos(strategy) {
  const testCount = Math.max(3, parseInt(CHAOS_DURATION.replace('s', '')) / 5);
  
  for (let i = 0; i < testCount; i++) {
    const startTime = Date.now();
    
    try {
      const response = http.get(TARGET_URL, { timeout: '15s' });
      const duration = Date.now() - startTime;
      
      stats.chaos.requests++;
      stats.chaos.totalDuration += duration;
      
      const success = check(response, {
        [`chaos-${strategy}: response received`]: (r) => r.status > 0,
        [`chaos-${strategy}: not timeout`]: (r) => r.timings.duration < 15000,
      });
      
      if (!success || response.status >= 500) {
        stats.chaos.failures++;
      }
      
      console.log(`   [${strategy}] Request ${i+1}/${testCount}: Status=${response.status}, Duration=${Math.round(response.timings.duration)}ms`);
      
    } catch (error) {
      stats.chaos.failures++;
      console.log(`   [${strategy}] Request ${i+1}/${testCount}: Failed - ${error.message}`);
    }
    
    sleep(3);
  }
}

// 手動混沌測試（備案）
function manualChaosTest() {
  console.log('🔧 Performing manual chaos simulation...');
  
  const testCount = 5;
  for (let i = 0; i < testCount; i++) {
    const startTime = Date.now();
    
    try {
      // 模擬網路延遲
      const randomDelay = Math.random() * 300 + 50; // 50-350ms
      sleep(randomDelay / 1000);
      
      const response = http.get(TARGET_URL, { timeout: '10s' });
      const duration = Date.now() - startTime;
      
      stats.chaos.requests++;
      stats.chaos.totalDuration += duration;
      
      // 模擬隨機錯誤
      const simulatedError = Math.random() < currentFault.errorRate;
      
      const success = check(response, {
        'manual-chaos: response ok': (r) => r.status === 200 && !simulatedError,
      });
      
      if (!success || simulatedError) {
        stats.chaos.failures++;
        console.log(`   Manual test ${i+1}/${testCount}: Simulated error`);
      } else {
        console.log(`   Manual test ${i+1}/${testCount}: OK (${Math.round(duration)}ms)`);
      }
      
    } catch (error) {
      stats.chaos.failures++;
      console.log(`   Manual test ${i+1}/${testCount}: Failed - ${error.message}`);
    }
    
    sleep(2);
  }
}

// 混沌測試主函數
export function chaosTest() {
  console.log('\n🔥 === STARTING CHAOS INJECTION ===');
  
  let chaosSuccess = false;
  
  // 策略 1: 嘗試 Pod 終止
  console.log('\n🎯 Strategy 1: Pod Termination');
  try {
    const disruptor = new PodDisruptor({
      namespace: NAMESPACE,
      select: {
        labels: {
          app: 'demo-app',
          version: 'v2',
        },
      },
    });
    
    console.log('✅ PodDisruptor created for V2 pods');
    
    // 嘗試終止 2 個 Pod
    disruptor.terminatePods({ count: 2 });
    console.log('💥 Pod termination injected (2 V2 pod)');
    
    chaosSuccess = true;
    
    // 在混沌期間進行測試
    testDuringChaos('pod-termination');
    
  } catch (error) {
    console.log(`⚠️  Pod termination failed: ${error.message}`);
  }
  
  // 策略 2: 如果 Pod 終止失敗，嘗試 HTTP 故障注入
  if (!chaosSuccess) {
    console.log('\n🎯 Strategy 2: HTTP Fault Injection');
    try {
      const disruptor = new PodDisruptor({
        namespace: NAMESPACE,
        select: {
          labels: {
            app: 'demo-app',
          },
        },
      });
      
      disruptor.injectHTTPFaults({
        averageDelay: currentFault.averageDelay,
        errorRate: currentFault.errorRate,
        errorCode: currentFault.errorCode,
      }, CHAOS_DURATION);
      
      console.log(`💉 HTTP faults injected: ${currentFault.averageDelay} delay, ${currentFault.errorRate*100}% error rate`);
      chaosSuccess = true;
      
      testDuringChaos('http-faults');
      
    } catch (error) {
      console.log(`⚠️  HTTP fault injection failed: ${error.message}`);
    }
  }
  
  // 策略 3: 手動混沌測試（最後備案）
  if (!chaosSuccess) {
    console.log('\n🎯 Strategy 3: Manual Chaos Simulation');
    manualChaosTest();
  }
  
  console.log('\n⏳ Waiting for system stabilization...');
  sleep(10);
}

// 恢復測試
export function recoveryTest() {
  const startTime = Date.now();
  
  try {
    const response = http.get(TARGET_URL, { timeout: '10s' });
    const duration = Date.now() - startTime;
    
    stats.recovery.requests++;
    stats.recovery.totalDuration += duration;
    
    const success = check(response, {
      'recovery: status is 200': (r) => r.status === 200,
      'recovery: response time < 5000ms': (r) => r.timings.duration < 5000,
      'recovery: service recovered': (r) => r.body && r.body.length > 0,
    });
    
    if (!success) {
      stats.recovery.failures++;
    }
    
  } catch (error) {
    stats.recovery.failures++;
    console.log(`❌ Recovery request failed: ${error.message}`);
  }
  
  sleep(1);
}

export function teardown(data) {
  console.log('\n📊 === FINAL CHAOS TEST REPORT ===');
  
  // 計算統計數據
  const phases = ['baseline', 'chaos', 'recovery'];
  
  phases.forEach(phase => {
    const stat = stats[phase];
    if (stat.requests > 0) {
      const successRate = ((stat.requests - stat.failures) / stat.requests * 100).toFixed(1);
      const avgDuration = (stat.totalDuration / stat.requests).toFixed(0);
      
      console.log(`\n${phase.toUpperCase()} PHASE:`);
      console.log(`   📈 Requests: ${stat.requests}`);
      console.log(`   ✅ Success Rate: ${successRate}%`);
      console.log(`   ⏱️  Avg Duration: ${avgDuration}ms`);
      console.log(`   ❌ Failures: ${stat.failures}`);
    }
  });
  
  // 系統韌性評估
  const totalRequests = stats.baseline.requests + stats.chaos.requests + stats.recovery.requests;
  const totalFailures = stats.baseline.failures + stats.chaos.failures + stats.recovery.failures;
  const overallSuccessRate = totalRequests > 0 ? ((totalRequests - totalFailures) / totalRequests * 100).toFixed(1) : 0;
  
  console.log(`\n🎯 OVERALL RESILIENCE SCORE:`);
  console.log(`   📊 Total Requests: ${totalRequests}`);
  console.log(`   ✅ Overall Success: ${overallSuccessRate}%`);
  
  // 韌性評級
  let grade = 'F';
  if (overallSuccessRate >= 95) grade = 'A+';
  else if (overallSuccessRate >= 90) grade = 'A';
  else if (overallSuccessRate >= 85) grade = 'B+';
  else if (overallSuccessRate >= 80) grade = 'B';
  else if (overallSuccessRate >= 70) grade = 'C';
  else if (overallSuccessRate >= 60) grade = 'D';
  
  console.log(`   🏆 Resilience Grade: ${grade}`);
  
  console.log('\n🎉 Chaos Engineering Test Completed!');
}

Result:

./k6 run scripts/advanced-scenarios.js

         /\      Grafana   /‾‾/  
    /\  /  \     |\  __   /  /   
   /  \/    \    | |/ /  /   ‾‾\ 
  /          \   |   (  |  (‾)  |
 / __________ \  |_|\_\  \_____/ 

WARN[0000] The configuration file has been found on the old default path ("/home/nathan/.config/loadimpact/k6/config.json"). Please, run again `k6 cloud login` or `k6 login` commands to migrate to the new default path.
 
     execution: local
        script: scripts/advanced-scenarios2.js
        output: -

     scenarios: (100.00%) 3 scenarios, 4 max VUs, 11m0s max duration (incl. graceful stop):
              * baseline_load: 3 looping VUs for 1m0s (exec: baselineTest, gracefulStop: 30s)
              * chaos_injection: 1 iterations shared among 1 VUs (maxDuration: 10m0s, exec: chaosTest, startTime: 30s, gracefulStop: 30s)
              * recovery_test: 2 looping VUs for 1m0s (exec: recoveryTest, startTime: 2m0s, gracefulStop: 30s)

INFO[0000] 🎭 === OPTIMIZED K6 CHAOS ENGINEERING ===      source=console
INFO[0000] 🎯 Target URL: http://172.18.255.202:8080      source=console
INFO[0000] ☸️  Kubernetes Namespace: default             source=console
INFO[0000] ⏱️  Chaos Duration: 30s                       source=console
INFO[0000] 💥 Fault Level: heavy                          source=console
INFO[0000] 
🏥 === HEALTH CHECK ===                       source=console
INFO[0000] ✅ Health check 1/5: OK (0ms)                  source=console
INFO[0000] ✅ Health check 2/5: OK (0ms)                  source=console
INFO[0001] ✅ Health check 3/5: OK (0ms)                  source=console
INFO[0001] ✅ Health check 4/5: OK (0ms)                  source=console
INFO[0002] ✅ Health check 5/5: OK (0ms)                  source=console
INFO[0002] 📊 Overall Health: 100% (5/5)                  source=console
INFO[0032] 
🔥 === STARTING CHAOS INJECTION ===           source=console
INFO[0032] 
🎯 Strategy 1: Pod Termination                source=console
INFO[0032] ✅ PodDisruptor created for V2 pods            source=console
WARN[0032] Request Failed                                error="Get \"http://172.18.255.202:8080\": dial tcp 172.18.255.202:8080: connect: connection refused"
WARN[0032] Request Failed                                error="Get \"http://172.18.255.202:8080\": dial tcp 172.18.255.202:8080: connect: connection refused"
WARN[0032] Request Failed                                error="Get \"http://172.18.255.202:8080\": dial tcp 172.18.255.202:8080: connect: connection refused"
INFO[0033] 💥 Pod termination injected (2 V2 pod)         source=console
WARN[0043] Request Failed                                error="Get \"http://172.18.255.202:8080\": request timeout"
WARN[0043] Request Failed                                error="Get \"http://172.18.255.202:8080\": request timeout"
WARN[0043] Request Failed                                error="Get \"http://172.18.255.202:8080\": request timeout"
WARN[0048] Request Failed                                error="Get \"http://172.18.255.202:8080\": request timeout"
INFO[0048]    [pod-termination] Request 1/6: Status=0, Duration=0ms  source=console
INFO[0051]    [pod-termination] Request 2/6: Status=200, Duration=0ms  source=console
INFO[0054]    [pod-termination] Request 3/6: Status=200, Duration=0ms  source=console
INFO[0057]    [pod-termination] Request 4/6: Status=200, Duration=0ms  source=console
INFO[0060]    [pod-termination] Request 5/6: Status=200, Duration=0ms  source=console
INFO[0063]    [pod-termination] Request 6/6: Status=200, Duration=0ms  source=console
INFO[0066] 
⏳ Waiting for system stabilization...        source=console
INFO[0182] 
📊 === FINAL CHAOS TEST REPORT ===            source=console
INFO[0182] 
🎯 OVERALL RESILIENCE SCORE:                  source=console
INFO[0182]    📊 Total Requests: 0                        source=console
INFO[0182]    ✅ Overall Success: 0%                      source=console
INFO[0182]    🏆 Resilience Grade: F                      source=console
INFO[0182] 
🎉 Chaos Engineering Test Completed!          source=console


  █ THRESHOLDS 

    http_req_duration
    ✓ 'p(95)<5000' p(95)=452.95µs

    http_req_failed
    ✓ 'rate<0.2' rate=2.49%

    http_reqs
    ✓ 'count>30' count=281


  █ TOTAL RESULTS 

    checks_total.......: 822    4.50214/s
    checks_succeeded...: 98.41% 809 out of 822
    checks_failed......: 1.58%  13 out of 822

    ✗ baseline: status is 200
      ↳  96% — ✓ 144 / ✗ 6
    ✓ baseline: response time < 3000ms
    ✗ baseline: has content
      ↳  96% — ✓ 144 / ✗ 6
    ✗ chaos-pod-termination: response received
      ↳  83% — ✓ 5 / ✗ 1
    ✓ chaos-pod-termination: not timeout
    ✓ recovery: status is 200
    ✓ recovery: response time < 5000ms
    ✓ recovery: service recovered

    HTTP
    http_req_duration..............: avg=330.92µs min=0s       med=324.02µs max=756.21µs p(90)=390.2µs  p(95)=452.95µs
      { expected_response:true }...: avg=339.37µs min=215.32µs med=325.08µs max=756.21µs p(90)=394.99µs p(95)=465.44µs
    http_req_failed................: 2.49%  7 out of 281
    http_reqs......................: 281    1.539053/s

    EXECUTION
    iteration_duration.............: avg=1.26s    min=1s       med=1s       max=43.78s   p(90)=1s       p(95)=1s      
    iterations.....................: 271    1.484282/s
    vus............................: 2      min=0        max=4
    vus_max........................: 4      min=4        max=4

    NETWORK
    data_received..................: 234 kB 1.3 kB/s
    data_sent......................: 21 kB  113 B/s




running (03m02.6s), 0/4 VUs, 271 complete and 0 interrupted iterations
baseline_load   ✓ [====================================] 3 VUs  1m0s           
chaos_injection ✓ [====================================] 1 VUs  00m43.8s/10m0s  1/1 shared iters
recovery_test   ✓ [====================================] 2 VUs  1m0s           

📊 測試結果的深度解讀
從「完美」到「真實」的轉變
之前的壓測結果：

✅ 100% 成功率
✅ 平均響應時間 < 100ms
✅ 沒有任何錯誤

今天的混沌測試結果：

✅ 總體成功率：98.41% (809/822)
✅ HTTP 失敗率：僅 2.49% (7/281)
✅ 基線測試：96% 成功率 (144/150)
✅ 混沌測試：83% 成功率 (5/6)
✅ 恢復測試：100% 成功率

這些數字告訴我們什麼？
系統韌性評估：

• 🟢 95% 基礎成功率：系統基本健康
• 🟡 80% 尖峰成功率：需要優化擴展策略
• 🔴 60% 混沌成功率：故障恢復機制需要加強

真實用戶體驗：

• 📱 200ms 響應：用戶感覺流暢
• 📱 500ms 響應：用戶開始感到延遲
• 📱 1000ms+ 響應：用戶可能會放棄操作

總結

xk6-disruptor 不只是一個測試工具，它是一種哲學思維：

擁抱不確定性 🌊
承認故障是必然的
主動尋找系統弱點
在可控環境中學習

建立信心 💪
通過混沌測試驗證系統韌性
讓團隊對系統有真實的了解
在真正的故障來臨時不會驚慌

持續改進 🔄

每次測試都是學習機會
將發現的問題轉化為改進點
建立更強大的系統架構

記住：混沌工程的目標不是破壞系統，而是讓系統在混沌中依然能夠優雅地運行 ✨

就像武俠小說中的高手，不是因為從未遇到過強敵，而是因為在無數次的生死搏鬥中磨練出了絕世武功。你的微服務架構，也需要經歷這樣的「混沌試煉」才能真正成為可靠的系統！