Kafka消费者在物联网领域的深度实践：从海量设备接入到实时智能决策

Kafka消费者在物联网领域的深度实践：从海量设备接入到实时智能决策 - 详解

news/2025/11/20 10:36:23/文章来源:https://www.cnblogs.com/yangykaifa/p/19245841

在物联网(IoT)领域，Kafka消费者面临着处理海量设备数据、实现低延迟响应和构建智能决策系统的独特挑战。本文将深入探讨Kafka消费者在物联网生态系统中的全方位应用。

文章目录

- 一、物联网数据接入架构
- - 1.1 海量设备数据接入
  - 1.2 设备连接管理
- 二、实时数据处理与分析
- - 2.1 流式数据处理管道
  - 2.2 实时预测与优化
- 三、边缘计算集成
- - 3.1 边缘-云协同处理
- 四、安全与隐私保护
- - 4.1 物联网安全控制
- 五、运维与监控
- - 5.1 物联网平台监控
- 总结
- - 核心挑战
  - 关键技术
  - 业务价值

一、物联网数据接入架构

1.1 海量设备数据接入

@Component
public class IoTDeviceDataConsumer {
private final DeviceRegistry deviceRegistry;
private final DataNormalizer dataNormalizer;
private final TelemetryProcessor telemetryProcessor;
@KafkaListener(
topics = "${iot.data.topics}",
containerFactory = "highThroughputContainerFactory",
concurrency = "${iot.consumer.concurrency:20}"
)
public void processDeviceData(ConsumerRecord<String, String> record) {DeviceDataContext context = createProcessingContext(record);try {// 1. 设备身份验证DeviceAuthenticationResult authResult = authenticateDevice(record);if (!authResult.isAuthenticated()) {handleUnauthorizedDevice(record, authResult);return;}// 2. 数据格式验证和解析ParsedDeviceData parsedData = parseAndValidateData(record, context);if (!parsedData.isValid()) {handleInvalidData(record, parsedData.getValidationErrors());return;}// 3. 数据标准化NormalizedDeviceData normalizedData = dataNormalizer.normalize(parsedData);// 4. 设备状态更新updateDeviceStatus(normalizedData);// 5. 遥测数据处理TelemetryProcessingResult telemetryResult =telemetryProcessor.process(normalizedData);// 6. 实时规则引擎处理RuleEngineResult ruleResult = evaluateDeviceRules(normalizedData);// 7. 数据路由和分发routeDataToDownstreamSystems(normalizedData, telemetryResult, ruleResult);// 8. 设备数据归档archiveDeviceData(normalizedData);} catch (DeviceDataProcessingException e) {handleDeviceDataProcessingError(record, context, e);}}private DeviceAuthenticationResult authenticateDevice(ConsumerRecord<String, String> record) {String deviceId = extractDeviceId(record);String authToken = extractAuthToken(record.headers());// 检查设备注册状态DeviceInfo deviceInfo = deviceRegistry.getDevice(deviceId);if (deviceInfo == null) {return DeviceAuthenticationResult.deviceNotFound(deviceId);}// 验证设备状态if (!deviceInfo.isActive()) {return DeviceAuthenticationResult.deviceInactive(deviceId);}// 验证认证令牌if (!deviceInfo.validateToken(authToken)) {return DeviceAuthenticationResult.invalidToken(deviceId);}// 检查设备配额if (deviceInfo.isOverQuota()) {return DeviceAuthenticationResult.quotaExceeded(deviceId);}return DeviceAuthenticationResult.success(deviceInfo);}private ParsedDeviceData parseAndValidateData(ConsumerRecord<String, String> record,DeviceDataContext context) {RawDeviceData rawData = deserializeRawData(record.value());// 数据格式验证DataFormatValidationResult formatValidation =dataFormatValidator.validate(rawData);if (!formatValidation.isValid()) {return ParsedDeviceData.invalid(formatValidation.getErrors());}// 业务逻辑验证BusinessValidationResult businessValidation =businessValidator.validate(rawData, context.getDeviceInfo());if (!businessValidation.isValid()) {return ParsedDeviceData.invalid(businessValidation.getErrors());}// 数据解析return dataParser.parse(rawData, context.getDeviceInfo().getDataSchema());}private void updateDeviceStatus(NormalizedDeviceData data) {DeviceStatusUpdate update = DeviceStatusUpdate.builder().deviceId(data.getDeviceId()).timestamp(data.getTimestamp()).onlineStatus(DeviceStatus.ONLINE).lastSeen(Instant.now()).batteryLevel(data.getBatteryLevel()).signalStrength(data.getSignalStrength()).firmwareVersion(data.getFirmwareVersion()).location(data.getLocation()).build();deviceRegistry.updateStatus(update);}}@Configuration@EnableKafkapublic class HighThroughputConsumerConfig {@Beanpublic ConcurrentKafkaListenerContainerFactory<String, String>highThroughputContainerFactory() {ConcurrentKafkaListenerContainerFactory<String, String> factory =new ConcurrentKafkaListenerContainerFactory<>();factory.setConsumerFactory(highThroughputConsumerFactory());// 高吞吐量优化配置factory.setBatchListener(true);factory.setConcurrency(calculateOptimalConcurrency());factory.setAutoStartup(true);ContainerProperties containerProps = factory.getContainerProperties();containerProps.setAckMode(ContainerProperties.AckMode.BATCH);containerProps.setIdleEventInterval(60000L);containerProps.setPollTimeout(5000L);// 自定义批处理逻辑factory.setBatchErrorHandler(new IoTBatchErrorHandler());return factory;}@Beanpublic ConsumerFactory<String, String> highThroughputConsumerFactory() {Map<String, Object> props = new HashMap<>();// 高吞吐量优化配置props.put(ConsumerConfig.FETCH_MIN_BYTES_CONFIG, 1024 * 1024); // 1MBprops.put(ConsumerConfig.FETCH_MAX_BYTES_CONFIG, 50 * 1024 * 1024); // 50MBprops.put(ConsumerConfig.MAX_POLL_RECORDS_CONFIG, 5000);props.put(ConsumerConfig.MAX_PARTITION_FETCH_BYTES_CONFIG, 10 * 1024 * 1024); // 10MB// 会话和心跳配置props.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, 30000);props.put(ConsumerConfig.HEARTBEAT_INTERVAL_MS_CONFIG, 10000);props.put(ConsumerConfig.MAX_POLL_INTERVAL_MS_CONFIG, 300000);return new DefaultKafkaConsumerFactory<>(props);}}

1.2 设备连接管理

@Component
public class DeviceConnectionManager {
private final DeviceSessionManager sessionManager;
private final ConnectionQualityMonitor qualityMonitor;
@KafkaListener(topics = "device-connection-events")
public void manageDeviceConnections(ConsumerRecord<String, String> record) {ConnectionEvent event = deserializeConnectionEvent(record);switch (event.getType()) {case CONNECT:handleDeviceConnect(event);break;case DISCONNECT:handleDeviceDisconnect(event);break;case HEARTBEAT:handleDeviceHeartbeat(event);break;case QUALITY_UPDATE:handleConnectionQualityUpdate(event);break;}}private void handleDeviceConnect(ConnectionEvent event) {DeviceSession session = DeviceSession.builder().deviceId(event.getDeviceId()).connectTime(Instant.now()).gatewayId(event.getGatewayId()).protocol(event.getProtocol()).connectionQuality(ConnectionQuality.GOOD).build();sessionManager.createSession(session);// 发送设备上线通知kafkaTemplate.send("device-lifecycle", event.getDeviceId(),DeviceLifecycleEvent.online(event.getDeviceId(), event.getGatewayId()));logger.info("设备连接建立: {}", event.getDeviceId());}private void handleDeviceHeartbeat(ConnectionEvent event) {DeviceSession session = sessionManager.getSession(event.getDeviceId());if (session != null) {session.updateLastHeartbeat(Instant.now());sessionManager.updateSession(session);// 更新连接质量ConnectionQuality quality = qualityMonitor.assessQuality(event);if (quality != session.getConnectionQuality()) {session.setConnectionQuality(quality);sessionManager.updateSession(session);// 发送质量变更事件kafkaTemplate.send("connection-quality-events", event.getDeviceId(),new ConnectionQualityEvent(event.getDeviceId(), quality));}}}@Scheduled(fixedRate = 30000) // 30秒检查一次public void checkDeviceTimeouts() {List<DeviceSession> timedOutSessions = sessionManager.findTimedOutSessions();for (DeviceSession session : timedOutSessions) {logger.warn("设备连接超时: {}", session.getDeviceId());// 标记设备为离线sessionManager.markOffline(session.getDeviceId());// 发送设备离线事件kafkaTemplate.send("device-lifecycle", session.getDeviceId(),DeviceLifecycleEvent.offline(session.getDeviceId(), "connection_timeout"));}}}@Componentpublic class GatewayLoadBalancer {private final GatewayRegistry gatewayRegistry;private final LoadBalancingStrategy loadBalancingStrategy;@KafkaListener(topics = "device-registration-requests")public void balanceDeviceLoad(ConsumerRecord<String, String> record) {DeviceRegistrationRequest request = deserializeRegistrationRequest(record);// 选择最优网关GatewayAssignment assignment = loadBalancingStrategy.assignGateway(request);if (assignment.isSuccessful()) {// 发送网关分配结果kafkaTemplate.send("gateway-assignments", request.getDeviceId(),GatewayAssignmentEvent.assigned(request.getDeviceId(), assignment.getGatewayId()));// 更新网关负载gatewayRegistry.updateLoad(assignment.getGatewayId(), 1);} else {// 处理分配失败handleAssignmentFailure(request, assignment);}}@Scheduled(fixedRate = 60000) // 每分钟重新平衡一次public void rebalanceGateways() {RebalancingPlan plan = loadBalancingStrategy.createRebalancingPlan();for (RebalancingAction action : plan.getActions()) {try {// 执行重新平衡executeRebalancing(action);logger.info("网关重新平衡完成: {} -> {}",action.getSourceGateway(), action.getTargetGateway());} catch (Exception e) {logger.error("网关重新平衡失败", e);}}}}

二、实时数据处理与分析

2.1 流式数据处理管道

@Component
public class IoTStreamProcessingPipeline {
private final StreamProcessingEngine streamEngine;
private final ComplexEventProcessor complexEventProcessor;
private final AnomalyDetectionService anomalyDetection;
@KafkaListener(topics = "device-telemetry")
public void processTelemetryStream(ConsumerRecord<String, String> record) {DeviceTelemetry telemetry = deserializeTelemetry(record);try {// 1. 数据增强EnhancedTelemetry enhanced = enhanceTelemetryData(telemetry);// 2. 实时聚合计算AggregationResult aggregation = computeRealTimeAggregations(enhanced);// 3. 复杂事件检测ComplexEventDetectionResult complexEvents =complexEventProcessor.detectEvents(enhanced);// 4. 异常检测AnomalyDetectionResult anomalies = anomalyDetection.detect(enhanced);// 5. 状态预测PredictionResult predictions = predictDeviceState(enhanced);// 6. 多路输出routeProcessedData(enhanced, aggregation, complexEvents, anomalies, predictions);} catch (StreamProcessingException e) {handleStreamProcessingError(telemetry, e);}}private EnhancedTelemetry enhanceTelemetryData(DeviceTelemetry telemetry) {return EnhancedTelemetry.builder().from(telemetry)// 添加地理位置信息.geoLocation(geoService.resolveLocation(telemetry.getDeviceId()))// 添加设备元数据.deviceMetadata(deviceRegistry.getMetadata(telemetry.getDeviceId()))// 添加环境上下文.environmentalContext(getEnvironmentalContext(telemetry))// 计算派生指标.derivedMetrics(calculateDerivedMetrics(telemetry)).build();}private AggregationResult computeRealTimeAggregations(EnhancedTelemetry telemetry) {return AggregationResult.builder()// 时间窗口聚合.minuteAggregates(computeMinuteAggregates(telemetry)).hourAggregates(computeHourAggregates(telemetry)).dayAggregates(computeDayAggregates(telemetry))// 设备组聚合.deviceGroupAggregates(computeGroupAggregates(telemetry))// 地理位置聚合.geoAggregates(computeGeoAggregates(telemetry)).build();}}@Componentpublic class ComplexEventProcessor {private final EventPatternMatcher patternMatcher;private final TemporalEventProcessor temporalProcessor;public ComplexEventDetectionResult detectEvents(EnhancedTelemetry telemetry) {List<DetectedEvent> events = new ArrayList<>();// 1. 模式匹配events.addAll(patternMatcher.matchPatterns(telemetry));// 2. 时序事件检测events.addAll(temporalProcessor.detectTemporalEvents(telemetry));// 3. 关联事件检测events.addAll(detectCorrelatedEvents(telemetry));// 4. 事件严重性评估events.forEach(this::assessEventSeverity);return ComplexEventDetectionResult.builder().events(events).detectionTime(Instant.now()).build();}private List<DetectedEvent> detectCorrelatedEvents(EnhancedTelemetry telemetry) {List<DetectedEvent> correlatedEvents = new ArrayList<>();// 检测设备组关联事件List<String> relatedDevices = deviceGroupManager.getRelatedDevices(telemetry.getDeviceId());for (String relatedDevice : relatedDevices) {DeviceTelemetry relatedTelemetry = telemetryCache.getLatest(relatedDevice);if (relatedTelemetry != null && isCorrelated(telemetry, relatedTelemetry)) {correlatedEvents.add(createCorrelationEvent(telemetry, relatedTelemetry));}}return correlatedEvents;}}@Componentpublic class IoTAnomalyDetectionService {private final MLAnomalyDetector mlDetector;private final StatisticalAnomalyDetector statisticalDetector;private final RuleBasedAnomalyDetector ruleBasedDetector;public AnomalyDetectionResult detect(EnhancedTelemetry telemetry) {List<DetectedAnomaly> anomalies = new ArrayList<>();// 1. 机器学习异常检测anomalies.addAll(mlDetector.detect(telemetry));// 2. 统计异常检测anomalies.addAll(statisticalDetector.detect(telemetry));// 3. 基于规则的异常检测anomalies.addAll(ruleBasedDetector.detect(telemetry));// 4. 异常聚合和去重List<DetectedAnomaly> consolidatedAnomalies = consolidateAnomalies(anomalies);// 5. 异常严重性评分consolidatedAnomalies.forEach(this::calculateAnomalyScore);return AnomalyDetectionResult.builder().anomalies(consolidatedAnomalies).detectionTime(Instant.now()).confidence(calculateOverallConfidence(consolidatedAnomalies)).build();}private List<DetectedAnomaly> consolidateAnomalies(List<DetectedAnomaly> anomalies) {Map<String, DetectedAnomaly> consolidated = new HashMap<>();for (DetectedAnomaly anomaly : anomalies) {String key = generateAnomalyKey(anomaly);if (consolidated.containsKey(key)) {// 合并相同类型的异常DetectedAnomaly existing = consolidated.get(key);existing.merge(anomaly);} else {consolidated.put(key, anomaly);}}return new ArrayList<>(consolidated.values());}}

2.2 实时预测与优化

@Component
public class PredictiveMaintenanceConsumer {
private final PredictiveModel predictiveModel;
private final MaintenanceOptimizer maintenanceOptimizer;
@KafkaListener(topics = "equipment-telemetry")
public void predictMaintenance(ConsumerRecord<String, String> record) {EquipmentTelemetry telemetry = deserializeEquipmentTelemetry(record);try {// 1. 设备健康评分HealthScore healthScore = calculateHealthScore(telemetry);// 2. 剩余寿命预测RemainingLifePrediction lifePrediction =predictiveModel.predictRemainingLife(telemetry);// 3. 故障概率预测FailureProbability failureProbability =predictiveModel.predictFailureProbability(telemetry);// 4. 维护建议生成MaintenanceRecommendation recommendation =maintenanceOptimizer.generateRecommendation(telemetry, healthScore, lifePrediction, failureProbability);// 5. 维护计划优化MaintenancePlan optimizedPlan =maintenanceOptimizer.optimizeMaintenanceSchedule(recommendation);// 6. 发送预测结果sendPredictiveMaintenanceResults(telemetry, healthScore, lifePrediction, failureProbability,recommendation, optimizedPlan);} catch (PredictionException e) {handlePredictionError(telemetry, e);}}private HealthScore calculateHealthScore(EquipmentTelemetry telemetry) {return HealthScore.builder().overallScore(calculateOverallHealth(telemetry)).componentScores(calculateComponentHealthScores(telemetry)).trend(calculateHealthTrend(telemetry)).confidence(calculateHealthConfidence(telemetry)).build();}}@Componentpublic class EnergyOptimizationConsumer {private final EnergyOptimizer energyOptimizer;private final DemandResponseManager demandResponseManager;@KafkaListener(topics = "energy-consumption")public void optimizeEnergyUsage(ConsumerRecord<String, String> record) {EnergyConsumptionData consumption = deserializeConsumptionData(record);try {// 1. 能耗分析EnergyAnalysis analysis = analyzeEnergyConsumption(consumption);// 2. 优化建议生成List<OptimizationRecommendation> recommendations =energyOptimizer.generateRecommendations(analysis);// 3. 需求响应处理DemandResponseResult demandResponse =demandResponseManager.processConsumption(consumption);// 4. 成本优化计算CostOptimizationResult costOptimization =calculateCostOptimization(analysis, recommendations);// 5. 发送控制指令sendOptimizationCommands(recommendations, demandResponse, costOptimization);} catch (OptimizationException e) {handleOptimizationError(consumption, e);}}}

三、边缘计算集成

3.1 边缘-云协同处理

@Component
public class EdgeCloudCoordinationConsumer {
private final EdgeManager edgeManager;
private final ModelDeploymentService modelDeployment;
@KafkaListener(topics = "edge-processing-results")
public void processEdgeResults(ConsumerRecord<String, String> record) {EdgeProcessingResult result = deserializeEdgeResult(record);try {// 1. 结果验证和融合ProcessedResult processed = validateAndFuseResults(result);// 2. 模型性能监控monitorEdgeModelPerformance(result);// 3. 边缘设备状态更新updateEdgeDeviceStatus(result.getEdgeDeviceId());// 4. 决策制定Decision decision = makeDecisionBasedOnEdgeResult(processed);// 5. 发送控制指令回边缘if (decision.requiresEdgeAction()) {sendEdgeControlCommand(result.getEdgeDeviceId(), decision);}} catch (EdgeProcessingException e) {handleEdgeProcessingError(result, e);}}@KafkaListener(topics = "model-update-requests")public void handleModelUpdates(ConsumerRecord<String, String> record) {ModelUpdateRequest request = deserializeModelUpdate(record);// 1. 模型验证ModelValidationResult validation = validateModel(request.getModel());if (!validation.isValid()) {handleInvalidModel(request, validation);return;}// 2. 边缘设备选择List<String> targetDevices = selectEdgeDevicesForDeployment(request);// 3. 模型分发for (String deviceId : targetDevices) {try {modelDeployment.deployToEdge(deviceId, request.getModel());logger.info("模型部署到边缘设备: {}", deviceId);} catch (Exception e) {logger.error("边缘模型部署失败: {}", deviceId, e);handleDeploymentFailure(deviceId, request, e);}}}}@Componentpublic class EdgeLoadBalancer {private final EdgeResourceMonitor resourceMonitor;private final TaskAllocator taskAllocator;@KafkaListener(topics = "processing-task-requests")public void allocateProcessingTasks(ConsumerRecord<String, String> record) {ProcessingTaskRequest request = deserializeTaskRequest(record);// 1. 资源评估EdgeResourceAssessment resourceAssessment =resourceMonitor.assessAvailableResources();// 2. 任务分配决策TaskAllocationDecision allocation =taskAllocator.allocateTask(request, resourceAssessment);if (allocation.shouldProcessOnEdge()) {// 边缘处理sendTaskToEdge(allocation.getEdgeDeviceId(), request);} else {// 云端处理sendTaskToCloud(request);}// 3. 更新资源使用resourceMonitor.updateResourceUsage(allocation);}@Scheduled(fixedRate = 30000)public void rebalanceEdgeLoad() {LoadRebalancingPlan rebalancingPlan =taskAllocator.createRebalancingPlan();for (LoadRebalancingAction action : rebalancingPlan.getActions()) {try {executeRebalancing(action);logger.info("边缘负载重新平衡: {}", action.getTaskId());} catch (Exception e) {logger.error("边缘负载重新平衡失败", e);}}}}

四、安全与隐私保护

4.1 物联网安全控制

@Component
public class IoTSecurityConsumer {
private final DeviceSecurityValidator securityValidator;
private final ThreatDetectionEngine threatDetector;
private final SecurityIncidentResponder incidentResponder;
@KafkaListener(topics = "iot-security-events")
public void processSecurityEvents(ConsumerRecord<String, String> record) {SecurityEvent event = deserializeSecurityEvent(record);try {// 1. 安全事件分类SecurityEventClassification classification =classifySecurityEvent(event);// 2. 威胁评估ThreatAssessment threatAssessment =threatDetector.assessThreat(event, classification);// 3. 风险评估RiskAssessment riskAssessment =evaluateRisk(event, threatAssessment);// 4. 响应决策SecurityResponseDecision responseDecision =determineResponse(event, threatAssessment, riskAssessment);// 5. 执行响应executeSecurityResponse(responseDecision);// 6. 安全审计logSecurityIncident(event, threatAssessment, riskAssessment, responseDecision);} catch (SecurityException e) {handleSecurityProcessingError(event, e);}}private SecurityResponseDecision determineResponse(SecurityEvent event,ThreatAssessment threatAssessment,RiskAssessment riskAssessment) {SecurityResponseDecision decision = new SecurityResponseDecision();if (riskAssessment.getRiskLevel() == RiskLevel.CRITICAL) {// 关键风险：立即阻断decision.addAction(SecurityAction.BLOCK_DEVICE);decision.addAction(SecurityAction.ALERT_SECURITY_TEAM);decision.setImmediate(true);} else if (riskAssessment.getRiskLevel() == RiskLevel.HIGH) {// 高风险：限制访问并告警decision.addAction(SecurityAction.RESTRICT_ACCESS);decision.addAction(SecurityAction.ENHANCE_MONITORING);decision.setImmediate(true);} else if (riskAssessment.getRiskLevel() == RiskLevel.MEDIUM) {// 中等风险：增强监控decision.addAction(SecurityAction.ENHANCE_MONITORING);decision.setImmediate(false);}return decision;}}@Componentpublic class DataPrivacyConsumer {private final PrivacyEngine privacyEngine;private final DataAnonymizer dataAnonymizer;@KafkaListener(topics = "sensitive-iot-data")public void enforceDataPrivacy(ConsumerRecord<String, String> record) {SensitiveDeviceData sensitiveData = deserializeSensitiveData(record);try {// 1. 隐私策略检查PrivacyPolicyCheckResult policyCheck =privacyEngine.checkCompliance(sensitiveData);if (!policyCheck.isCompliant()) {handlePrivacyViolation(sensitiveData, policyCheck);return;}// 2. 数据脱敏AnonymizedData anonymizedData =dataAnonymizer.anonymize(sensitiveData);// 3. 数据加密EncryptedData encryptedData =encryptForStorage(anonymizedData);// 4. 访问控制applyAccessControls(encryptedData);// 5. 安全存储storeSecurely(encryptedData);} catch (PrivacyException e) {handlePrivacyEnforcementError(sensitiveData, e);}}private AnonymizedData anonymize(SensitiveDeviceData data) {return AnonymizedData.builder()// 设备标识符脱敏.anonymizedDeviceId(privacyEngine.anonymizeDeviceId(data.getDeviceId()))// 地理位置模糊化.obfuscatedLocation(privacyEngine.obfuscateLocation(data.getLocation()))// 个人身份信息移除.removedPii(privacyEngine.removePii(data.getMetadata()))// 数据聚合.aggregatedMetrics(privacyEngine.aggregateMetrics(data.getMetrics())).build();}}

五、运维与监控

5.1 物联网平台监控

@Component
public class IoTPlatformMonitor {
private final PlatformMetricsCollector metricsCollector;
private final AlertManager alertManager;
private readonly HealthCheckService healthCheckService;
@KafkaListener(topics = "platform-metrics")
public void monitorPlatformHealth(ConsumerRecord<String, String> record) {PlatformMetrics metrics = deserializePlatformMetrics(record);try {// 1. 指标分析PlatformHealthAnalysis analysis = analyzePlatformHealth(metrics);// 2. 性能监控PerformanceMonitoringResult performance = monitorPerformance(metrics);// 3. 容量规划CapacityPlanningResult capacity = planCapacity(metrics);// 4. 故障预测FailurePredictionResult failures = predictFailures(metrics);// 5. 告警处理processAlerts(analysis, performance, capacity, failures);} catch (MonitoringException e) {handleMonitoringError(metrics, e);}}@Scheduled(fixedRate = 60000)public void performComprehensiveHealthCheck() {ComprehensiveHealthCheckResult healthCheck =healthCheckService.performComprehensiveCheck();if (!healthCheck.isHealthy()) {// 发送健康告警alertManager.sendHealthAlert(healthCheck);// 执行自动修复if (healthCheck.canAutoRepair()) {executeAutoRepair(healthCheck);}}// 更新监控仪表板updateMonitoringDashboard(healthCheck);}}@Componentpublic class DeviceFleetManager {private final DeviceFleetMonitor fleetMonitor;private readonly FirmwareManager firmwareManager;@KafkaListener(topics = "fleet-management-events")public void manageDeviceFleet(ConsumerRecord<String, String> record) {FleetManagementEvent event = deserializeFleetEvent(record);switch (event.getType()) {case FIRMWARE_UPDATE:handleFirmwareUpdate(event);break;case CONFIGURATION_UPDATE:handleConfigurationUpdate(event);break;case BULK_OPERATION:handleBulkOperation(event);break;case FLEET_HEALTH_CHECK:handleFleetHealthCheck(event);break;}}private void handleFirmwareUpdate(FleetManagementEvent event) {FirmwareUpdatePlan updatePlan = firmwareManager.createUpdatePlan(event);for (FirmwareUpdateTask task : updatePlan.getTasks()) {try {// 执行固件更新firmwareManager.executeUpdate(task);logger.info("固件更新完成: {}", task.getDeviceId());} catch (FirmwareUpdateException e) {logger.error("固件更新失败: {}", task.getDeviceId(), e);handleFirmwareUpdateFailure(task, e);}}}@Scheduled(cron = "0 0 2 * * ?") // 每天凌晨2点执行public void performFleetHealthReport() {FleetHealthReport healthReport = fleetMonitor.generateHealthReport();// 发送健康报告kafkaTemplate.send("fleet-health-reports", healthReport);// 执行必要的维护操作executeFleetMaintenance(healthReport);}}