前言

RDS-Redis自动巡检作为企业级云数据库运维的核心能力之一，直接影响着数据存储的稳定性和缓存性能。通过智能的云数据库监控策略，完善的缓存优化机制，能够及时发现数据库异常，预防数据丢失，保障企业级应用的高可用性。本文从云数据库监控设计到缓存优化，从基础原理到企业级实践，系统梳理RDS-Redis自动巡检的完整解决方案。

一、RDS-Redis自动巡检架构设计

1.1 巡检系统整体架构

1.2 巡检核心组件

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/**
 * RDS-Redis自动巡检核心组件
 */
@Component
public class RDSRedisInspectionEngine {

    @Autowired
    private RDSMonitorService rdsMonitorService;

    @Autowired
    private RedisMonitorService redisMonitorService;

    @Autowired
    private CloudDatabaseManager cloudDatabaseManager;

    @Autowired
    private CacheManager cacheManager;

    @Autowired
    private AlertService alertService;

    @Autowired
    private InspectionResultStorage resultStorage;

    /**
     * 启动RDS-Redis巡检引擎
     */
    public void startInspectionEngine() {
        try {
            // 1. 初始化云数据库连接
            initializeCloudDatabaseConnections();

            // 2. 启动RDS监控
            rdsMonitorService.startMonitoring();

            // 3. 启动Redis监控
            redisMonitorService.startMonitoring();

            // 4. 启动云数据库管理
            cloudDatabaseManager.startManagement();

            // 5. 启动缓存管理
            cacheManager.startManagement();

            log.info("RDS-Redis巡检引擎启动成功");

        } catch (Exception e) {
            log.error("RDS-Redis巡检引擎启动失败", e);
            throw new InspectionEngineException("巡检引擎启动失败", e);
        }
    }

    /**
     * 停止RDS-Redis巡检引擎
     */
    public void stopInspectionEngine() {
        try {
            // 1. 停止缓存管理
            cacheManager.stopManagement();

            // 2. 停止云数据库管理
            cloudDatabaseManager.stopManagement();

            // 3. 停止Redis监控
            redisMonitorService.stopMonitoring();

            // 4. 停止RDS监控
            rdsMonitorService.stopMonitoring();

            log.info("RDS-Redis巡检引擎停止成功");

        } catch (Exception e) {
            log.error("RDS-Redis巡检引擎停止失败", e);
        }
    }

    /**
     * 初始化云数据库连接
     */
    private void initializeCloudDatabaseConnections() {
        try {
            // 初始化RDS连接
            rdsMonitorService.initializeConnections();

            // 初始化Redis连接
            redisMonitorService.initializeConnections();

            log.info("云数据库连接初始化完成");

        } catch (Exception e) {
            log.error("云数据库连接初始化失败", e);
            throw new ConnectionException("云数据库连接初始化失败", e);
        }
    }
}

二、RDS数据库监控

2.1 RDS监控服务

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/**
 * RDS数据库监控服务
 */
@Service
public class RDSMonitorService {

    @Autowired
    private RDSConnectionManager connectionManager;

    @Autowired
    private RDSMetricsCollector metricsCollector;

    @Autowired
    private RDSHealthAnalyzer healthAnalyzer;

    @Autowired
    private RDSOptimizer optimizer;

    private final ScheduledExecutorService monitorScheduler;
    private final Map<String, RDSInstance> monitoredInstances;

    public RDSMonitorService() {
        this.monitorScheduler = Executors.newScheduledThreadPool(10);
        this.monitoredInstances = new ConcurrentHashMap<>();
    }

    /**
     * 启动RDS监控
     */
    public void startMonitoring() {
        // 启动定期监控任务
        monitorScheduler.scheduleAtFixedRate(
            this::monitorRDSInstances,
            0,
            60, // 1分钟
            TimeUnit.SECONDS
        );

        log.info("RDS数据库监控启动成功");
    }

    /**
     * 停止RDS监控
     */
    public void stopMonitoring() {
        try {
            monitorScheduler.shutdown();
            if (!monitorScheduler.awaitTermination(30, TimeUnit.SECONDS)) {
                monitorScheduler.shutdownNow();
            }

            log.info("RDS数据库监控停止成功");

        } catch (Exception e) {
            log.error("RDS数据库监控停止失败", e);
        }
    }

    /**
     * 初始化RDS连接
     */
    public void initializeConnections() {
        try {
            // 获取所有RDS实例
            List<RDSInstance> instances = connectionManager.getAllInstances();

            // 初始化每个实例的连接
            for (RDSInstance instance : instances) {
                initializeInstanceConnection(instance);
                monitoredInstances.put(instance.getInstanceId(), instance);
            }

            log.info("RDS实例连接初始化完成，实例数量: {}", instances.size());

        } catch (Exception e) {
            log.error("RDS连接初始化失败", e);
            throw new ConnectionException("RDS连接初始化失败", e);
        }
    }

    /**
     * 监控RDS实例
     */
    private void monitorRDSInstances() {
        try {
            for (RDSInstance instance : monitoredInstances.values()) {
                monitorSingleInstance(instance);
            }

        } catch (Exception e) {
            log.error("RDS实例监控失败", e);
        }
    }

    /**
     * 监控单个RDS实例
     */
    private void monitorSingleInstance(RDSInstance instance) {
        try {
            // 1. 收集实例指标
            RDSMetrics metrics = metricsCollector.collectMetrics(instance);

            // 2. 分析实例健康状态
            RDSHealthStatus healthStatus = healthAnalyzer.analyzeHealth(instance, metrics);

            // 3. 检查实例状态
            if (!healthStatus.isHealthy()) {
                handleUnhealthyInstance(instance, healthStatus);
            }

            // 4. 尝试性能优化
            if (healthStatus.needsOptimization()) {
                attemptOptimization(instance, healthStatus);
            }

            // 5. 记录监控结果
            recordMonitoringResult(instance, metrics, healthStatus);

        } catch (Exception e) {
            log.error("RDS实例监控失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 处理不健康实例
     */
    private void handleUnhealthyInstance(RDSInstance instance, RDSHealthStatus healthStatus) {
        try {
            // 1. 发送实例告警
            sendInstanceAlert(instance, healthStatus);

            // 2. 记录实例问题
            recordInstanceIssue(instance, healthStatus);

            // 3. 尝试自动修复
            if (healthStatus.isAutoRepairable()) {
                attemptAutoRepair(instance, healthStatus);
            }

        } catch (Exception e) {
            log.error("不健康实例处理失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 发送实例告警
     */
    private void sendInstanceAlert(RDSInstance instance, RDSHealthStatus healthStatus) {
        RDSAlert alert = new RDSAlert();
        alert.setAlertType(AlertType.RDS_UNHEALTHY);
        alert.setSeverity(healthStatus.getSeverity());
        alert.setMessage("RDS实例状态异常: " + instance.getInstanceId());
        alert.setInstance(instance);
        alert.setHealthStatus(healthStatus);
        alert.setTimestamp(System.currentTimeMillis());

        // 发送告警
        alertService.sendAlert(alert);
    }

    /**
     * 尝试自动修复
     */
    private void attemptAutoRepair(RDSInstance instance, RDSHealthStatus healthStatus) {
        try {
            log.info("尝试自动修复RDS实例: {}", instance.getInstanceId());

            // 根据问题类型选择修复策略
            switch (healthStatus.getIssueType()) {
                case CONNECTION_ISSUE:
                    repairConnectionIssue(instance);
                    break;
                case PERFORMANCE_ISSUE:
                    repairPerformanceIssue(instance);
                    break;
                case STORAGE_ISSUE:
                    repairStorageIssue(instance);
                    break;
                case BACKUP_ISSUE:
                    repairBackupIssue(instance);
                    break;
                default:
                    log.warn("无法自动修复的问题类型: {}", healthStatus.getIssueType());
            }

        } catch (Exception e) {
            log.error("RDS实例自动修复失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 尝试性能优化
     */
    private void attemptOptimization(RDSInstance instance, RDSHealthStatus healthStatus) {
        try {
            log.info("尝试RDS实例性能优化: {}", instance.getInstanceId());

            // 根据性能问题选择优化策略
            switch (healthStatus.getPerformanceIssueType()) {
                case HIGH_CPU_USAGE:
                    optimizer.optimizeCPUUsage(instance);
                    break;
                case HIGH_MEMORY_USAGE:
                    optimizer.optimizeMemoryUsage(instance);
                    break;
                case HIGH_DISK_USAGE:
                    optimizer.optimizeDiskUsage(instance);
                    break;
                case SLOW_QUERY:
                    optimizer.optimizeSlowQuery(instance);
                    break;
                default:
                    log.warn("无法自动优化的性能问题类型: {}", healthStatus.getPerformanceIssueType());
            }

        } catch (Exception e) {
            log.error("RDS实例性能优化失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 修复连接问题
     */
    private void repairConnectionIssue(RDSInstance instance) {
        try {
            // 重启实例连接
            connectionManager.restartInstanceConnection(instance);
            log.info("RDS实例连接修复成功: {}", instance.getInstanceId());

        } catch (Exception e) {
            log.error("RDS实例连接修复失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 修复性能问题
     */
    private void repairPerformanceIssue(RDSInstance instance) {
        try {
            // 调整实例参数
            optimizer.adjustInstanceParameters(instance);
            log.info("RDS实例性能修复成功: {}", instance.getInstanceId());

        } catch (Exception e) {
            log.error("RDS实例性能修复失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 修复存储问题
     */
    private void repairStorageIssue(RDSInstance instance) {
        try {
            // 清理临时文件
            optimizer.cleanupTempFiles(instance);
            log.info("RDS实例存储修复成功: {}", instance.getInstanceId());

        } catch (Exception e) {
            log.error("RDS实例存储修复失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 修复备份问题
     */
    private void repairBackupIssue(RDSInstance instance) {
        try {
            // 触发备份
            optimizer.triggerBackup(instance);
            log.info("RDS实例备份修复成功: {}", instance.getInstanceId());

        } catch (Exception e) {
            log.error("RDS实例备份修复失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 记录监控结果
     */
    private void recordMonitoringResult(RDSInstance instance, RDSMetrics metrics, RDSHealthStatus healthStatus) {
        RDSMonitoringResult result = new RDSMonitoringResult();
        result.setInstanceId(instance.getInstanceId());
        result.setTimestamp(System.currentTimeMillis());
        result.setMetrics(metrics);
        result.setHealthStatus(healthStatus);

        // 存储监控结果
        resultStorage.storeRDSResult(result);
    }
}

2.2 RDS指标收集器

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/**
 * RDS指标收集器
 */
@Component
public class RDSMetricsCollector {

    @Autowired
    private RDSConnectionManager connectionManager;

    @Autowired
    private CloudAPIClient cloudAPIClient;

    /**
     * 收集RDS指标
     */
    public RDSMetrics collectMetrics(RDSInstance instance) {
        RDSMetrics metrics = new RDSMetrics();

        try {
            // 1. 收集基础指标
            collectBasicMetrics(instance, metrics);

            // 2. 收集性能指标
            collectPerformanceMetrics(instance, metrics);

            // 3. 收集存储指标
            collectStorageMetrics(instance, metrics);

            // 4. 收集连接指标
            collectConnectionMetrics(instance, metrics);

            // 5. 收集备份指标
            collectBackupMetrics(instance, metrics);

        } catch (Exception e) {
            log.error("RDS指标收集失败: {}", instance.getInstanceId(), e);
        }

        return metrics;
    }

    /**
     * 收集基础指标
     */
    private void collectBasicMetrics(RDSInstance instance, RDSMetrics metrics) {
        try {
            // 实例状态
            String instanceStatus = cloudAPIClient.getInstanceStatus(instance.getInstanceId());
            metrics.setInstanceStatus(instanceStatus);

            // 实例类型
            String instanceType = cloudAPIClient.getInstanceType(instance.getInstanceId());
            metrics.setInstanceType(instanceType);

            // 引擎版本
            String engineVersion = cloudAPIClient.getEngineVersion(instance.getInstanceId());
            metrics.setEngineVersion(engineVersion);

            // 创建时间
            Date createTime = cloudAPIClient.getCreateTime(instance.getInstanceId());
            metrics.setCreateTime(createTime);

        } catch (Exception e) {
            log.error("基础指标收集失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 收集性能指标
     */
    private void collectPerformanceMetrics(RDSInstance instance, RDSMetrics metrics) {
        try {
            // CPU使用率
            double cpuUsage = cloudAPIClient.getCPUUsage(instance.getInstanceId());
            metrics.setCpuUsage(cpuUsage);

            // 内存使用率
            double memoryUsage = cloudAPIClient.getMemoryUsage(instance.getInstanceId());
            metrics.setMemoryUsage(memoryUsage);

            // QPS
            double qps = cloudAPIClient.getQPS(instance.getInstanceId());
            metrics.setQps(qps);

            // 平均延迟
            double avgLatency = cloudAPIClient.getAverageLatency(instance.getInstanceId());
            metrics.setAverageLatency(avgLatency);

            // 慢查询数
            int slowQueryCount = cloudAPIClient.getSlowQueryCount(instance.getInstanceId());
            metrics.setSlowQueryCount(slowQueryCount);

            // 连接数
            int connectionCount = cloudAPIClient.getConnectionCount(instance.getInstanceId());
            metrics.setConnectionCount(connectionCount);

            // 最大连接数
            int maxConnections = cloudAPIClient.getMaxConnections(instance.getInstanceId());
            metrics.setMaxConnections(maxConnections);

        } catch (Exception e) {
            log.error("性能指标收集失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 收集存储指标
     */
    private void collectStorageMetrics(RDSInstance instance, RDSMetrics metrics) {
        try {
            // 磁盘使用率
            double diskUsage = cloudAPIClient.getDiskUsage(instance.getInstanceId());
            metrics.setDiskUsage(diskUsage);

            // 可用空间
            long availableSpace = cloudAPIClient.getAvailableSpace(instance.getInstanceId());
            metrics.setAvailableSpace(availableSpace);

            // 总空间
            long totalSpace = cloudAPIClient.getTotalSpace(instance.getInstanceId());
            metrics.setTotalSpace(totalSpace);

            // IOPS
            int iops = cloudAPIClient.getIOPS(instance.getInstanceId());
            metrics.setIops(iops);

            // 读取IOPS
            int readIops = cloudAPIClient.getReadIOPS(instance.getInstanceId());
            metrics.setReadIops(readIops);

            // 写入IOPS
            int writeIops = cloudAPIClient.getWriteIOPS(instance.getInstanceId());
            metrics.setWriteIops(writeIops);

        } catch (Exception e) {
            log.error("存储指标收集失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 收集连接指标
     */
    private void collectConnectionMetrics(RDSInstance instance, RDSMetrics metrics) {
        try {
            // 活跃连接数
            int activeConnections = cloudAPIClient.getActiveConnections(instance.getInstanceId());
            metrics.setActiveConnections(activeConnections);

            // 空闲连接数
            int idleConnections = cloudAPIClient.getIdleConnections(instance.getInstanceId());
            metrics.setIdleConnections(idleConnections);

            // 连接错误数
            int connectionErrors = cloudAPIClient.getConnectionErrors(instance.getInstanceId());
            metrics.setConnectionErrors(connectionErrors);

            // 连接超时数
            int connectionTimeouts = cloudAPIClient.getConnectionTimeouts(instance.getInstanceId());
            metrics.setConnectionTimeouts(connectionTimeouts);

        } catch (Exception e) {
            log.error("连接指标收集失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 收集备份指标
     */
    private void collectBackupMetrics(RDSInstance instance, RDSMetrics metrics) {
        try {
            // 最后备份时间
            Date lastBackupTime = cloudAPIClient.getLastBackupTime(instance.getInstanceId());
            metrics.setLastBackupTime(lastBackupTime);

            // 备份大小
            long backupSize = cloudAPIClient.getBackupSize(instance.getInstanceId());
            metrics.setBackupSize(backupSize);

            // 备份状态
            String backupStatus = cloudAPIClient.getBackupStatus(instance.getInstanceId());
            metrics.setBackupStatus(backupStatus);

            // 备份保留天数
            int backupRetentionDays = cloudAPIClient.getBackupRetentionDays(instance.getInstanceId());
            metrics.setBackupRetentionDays(backupRetentionDays);

        } catch (Exception e) {
            log.error("备份指标收集失败: {}", instance.getInstanceId(), e);
        }
    }
}

2.3 RDS健康分析器

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/**
 * RDS健康分析器
 */
@Component
public class RDSHealthAnalyzer {

    /**
     * 分析RDS健康状态
     */
    public RDSHealthStatus analyzeHealth(RDSInstance instance, RDSMetrics metrics) {
        RDSHealthStatus status = new RDSHealthStatus();

        try {
            // 1. 分析实例状态
            InstanceStatusAnalysis instanceAnalysis = analyzeInstanceStatus(metrics);
            status.setInstanceAnalysis(instanceAnalysis);

            // 2. 分析性能状态
            PerformanceStatusAnalysis performanceAnalysis = analyzePerformanceStatus(metrics);
            status.setPerformanceAnalysis(performanceAnalysis);

            // 3. 分析存储状态
            StorageStatusAnalysis storageAnalysis = analyzeStorageStatus(metrics);
            status.setStorageAnalysis(storageAnalysis);

            // 4. 分析连接状态
            ConnectionStatusAnalysis connectionAnalysis = analyzeConnectionStatus(metrics);
            status.setConnectionAnalysis(connectionAnalysis);

            // 5. 分析备份状态
            BackupStatusAnalysis backupAnalysis = analyzeBackupStatus(metrics);
            status.setBackupAnalysis(backupAnalysis);

            // 6. 综合评估健康状态
            evaluateHealthStatus(status);

        } catch (Exception e) {
            log.error("RDS健康分析失败: {}", instance.getInstanceId(), e);
            status.setHealthy(false);
            status.setSeverity(Severity.HIGH);
        }

        return status;
    }

    /**
     * 分析实例状态
     */
    private InstanceStatusAnalysis analyzeInstanceStatus(RDSMetrics metrics) {
        InstanceStatusAnalysis analysis = new InstanceStatusAnalysis();

        // 检查实例状态
        String instanceStatus = metrics.getInstanceStatus();
        if ("Running".equals(instanceStatus)) {
            analysis.setInstanceStatus(InstanceStatus.RUNNING);
            analysis.setInstanceStatusLevel(StatusLevel.NORMAL);
        } else if ("Stopped".equals(instanceStatus)) {
            analysis.setInstanceStatus(InstanceStatus.STOPPED);
            analysis.setInstanceStatusLevel(StatusLevel.CRITICAL);
        } else if ("Starting".equals(instanceStatus)) {
            analysis.setInstanceStatus(InstanceStatus.STARTING);
            analysis.setInstanceStatusLevel(StatusLevel.WARNING);
        } else {
            analysis.setInstanceStatus(InstanceStatus.UNKNOWN);
            analysis.setInstanceStatusLevel(StatusLevel.CRITICAL);
        }

        return analysis;
    }

    /**
     * 分析性能状态
     */
    private PerformanceStatusAnalysis analyzePerformanceStatus(RDSMetrics metrics) {
        PerformanceStatusAnalysis analysis = new PerformanceStatusAnalysis();

        // 分析CPU使用率
        double cpuUsage = metrics.getCpuUsage();
        analysis.setCpuUsage(cpuUsage);
        analysis.setCpuUsageLevel(evaluateCPUUsageLevel(cpuUsage));

        // 分析内存使用率
        double memoryUsage = metrics.getMemoryUsage();
        analysis.setMemoryUsage(memoryUsage);
        analysis.setMemoryUsageLevel(evaluateMemoryUsageLevel(memoryUsage));

        // 分析QPS
        double qps = metrics.getQps();
        analysis.setQps(qps);
        analysis.setQpsLevel(evaluateQPSLevel(qps));

        // 分析平均延迟
        double avgLatency = metrics.getAverageLatency();
        analysis.setAverageLatency(avgLatency);
        analysis.setLatencyLevel(evaluateLatencyLevel(avgLatency));

        // 分析慢查询数
        int slowQueryCount = metrics.getSlowQueryCount();
        analysis.setSlowQueryCount(slowQueryCount);
        analysis.setSlowQueryLevel(evaluateSlowQueryLevel(slowQueryCount));

        return analysis;
    }

    /**
     * 分析存储状态
     */
    private StorageStatusAnalysis analyzeStorageStatus(RDSMetrics metrics) {
        StorageStatusAnalysis analysis = new StorageStatusAnalysis();

        // 分析磁盘使用率
        double diskUsage = metrics.getDiskUsage();
        analysis.setDiskUsage(diskUsage);
        analysis.setDiskUsageLevel(evaluateDiskUsageLevel(diskUsage));

        // 分析可用空间
        long availableSpace = metrics.getAvailableSpace();
        analysis.setAvailableSpace(availableSpace);
        analysis.setAvailableSpaceLevel(evaluateAvailableSpaceLevel(availableSpace));

        // 分析IOPS
        int iops = metrics.getIops();
        analysis.setIops(iops);
        analysis.setIopsLevel(evaluateIOPSLevel(iops));

        return analysis;
    }

    /**
     * 分析连接状态
     */
    private ConnectionStatusAnalysis analyzeConnectionStatus(RDSMetrics metrics) {
        ConnectionStatusAnalysis analysis = new ConnectionStatusAnalysis();

        // 分析连接数
        int connectionCount = metrics.getConnectionCount();
        int maxConnections = metrics.getMaxConnections();
        double connectionRatio = (double) connectionCount / maxConnections;

        analysis.setConnectionCount(connectionCount);
        analysis.setMaxConnections(maxConnections);
        analysis.setConnectionRatio(connectionRatio);
        analysis.setConnectionLevel(evaluateConnectionLevel(connectionRatio));

        // 分析连接错误
        int connectionErrors = metrics.getConnectionErrors();
        analysis.setConnectionErrors(connectionErrors);
        analysis.setConnectionErrorLevel(evaluateConnectionErrorLevel(connectionErrors));

        // 分析连接超时
        int connectionTimeouts = metrics.getConnectionTimeouts();
        analysis.setConnectionTimeouts(connectionTimeouts);
        analysis.setConnectionTimeoutLevel(evaluateConnectionTimeoutLevel(connectionTimeouts));

        return analysis;
    }

    /**
     * 分析备份状态
     */
    private BackupStatusAnalysis analyzeBackupStatus(RDSMetrics metrics) {
        BackupStatusAnalysis analysis = new BackupStatusAnalysis();

        // 分析备份状态
        String backupStatus = metrics.getBackupStatus();
        analysis.setBackupStatus(backupStatus);
        analysis.setBackupStatusLevel(evaluateBackupStatusLevel(backupStatus));

        // 分析最后备份时间
        Date lastBackupTime = metrics.getLastBackupTime();
        analysis.setLastBackupTime(lastBackupTime);
        analysis.setBackupTimeLevel(evaluateBackupTimeLevel(lastBackupTime));

        // 分析备份大小
        long backupSize = metrics.getBackupSize();
        analysis.setBackupSize(backupSize);
        analysis.setBackupSizeLevel(evaluateBackupSizeLevel(backupSize));

        return analysis;
    }

    /**
     * 评估健康状态
     */
    private void evaluateHealthStatus(RDSHealthStatus status) {
        boolean isHealthy = true;
        Severity maxSeverity = Severity.LOW;

        // 评估实例状态
        if (status.getInstanceAnalysis().getInstanceStatusLevel() == StatusLevel.CRITICAL) {
            isHealthy = false;
            maxSeverity = Severity.CRITICAL;
        }

        // 评估性能状态
        if (status.getPerformanceAnalysis().hasCriticalIssues()) {
            isHealthy = false;
            maxSeverity = Severity.max(maxSeverity, Severity.HIGH);
        }

        // 评估存储状态
        if (status.getStorageAnalysis().hasCriticalIssues()) {
            isHealthy = false;
            maxSeverity = Severity.max(maxSeverity, Severity.HIGH);
        }

        // 评估连接状态
        if (status.getConnectionAnalysis().hasCriticalIssues()) {
            isHealthy = false;
            maxSeverity = Severity.max(maxSeverity, Severity.MEDIUM);
        }

        // 评估备份状态
        if (status.getBackupAnalysis().hasCriticalIssues()) {
            isHealthy = false;
            maxSeverity = Severity.max(maxSeverity, Severity.MEDIUM);
        }

        status.setHealthy(isHealthy);
        status.setSeverity(maxSeverity);
    }

    /**
     * 评估CPU使用率级别
     */
    private StatusLevel evaluateCPUUsageLevel(double cpuUsage) {
        if (cpuUsage > 0.9) { // 90%
            return StatusLevel.CRITICAL;
        } else if (cpuUsage > 0.8) { // 80%
            return StatusLevel.WARNING;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估内存使用率级别
     */
    private StatusLevel evaluateMemoryUsageLevel(double memoryUsage) {
        if (memoryUsage > 0.9) { // 90%
            return StatusLevel.CRITICAL;
        } else if (memoryUsage > 0.8) { // 80%
            return StatusLevel.WARNING;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估QPS级别
     */
    private StatusLevel evaluateQPSLevel(double qps) {
        if (qps < 100) { // 100 QPS
            return StatusLevel.WARNING;
        } else if (qps < 50) { // 50 QPS
            return StatusLevel.CRITICAL;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估延迟级别
     */
    private StatusLevel evaluateLatencyLevel(double latency) {
        if (latency > 1000) { // 1000ms
            return StatusLevel.CRITICAL;
        } else if (latency > 500) { // 500ms
            return StatusLevel.WARNING;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估慢查询级别
     */
    private StatusLevel evaluateSlowQueryLevel(int slowQueryCount) {
        if (slowQueryCount > 100) { // 100个
            return StatusLevel.CRITICAL;
        } else if (slowQueryCount > 50) { // 50个
            return StatusLevel.WARNING;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估磁盘使用率级别
     */
    private StatusLevel evaluateDiskUsageLevel(double diskUsage) {
        if (diskUsage > 0.9) { // 90%
            return StatusLevel.CRITICAL;
        } else if (diskUsage > 0.8) { // 80%
            return StatusLevel.WARNING;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估可用空间级别
     */
    private StatusLevel evaluateAvailableSpaceLevel(long availableSpace) {
        if (availableSpace < 1024 * 1024 * 1024) { // 1GB
            return StatusLevel.CRITICAL;
        } else if (availableSpace < 5 * 1024 * 1024 * 1024) { // 5GB
            return StatusLevel.WARNING;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估IOPS级别
     */
    private StatusLevel evaluateIOPSLevel(int iops) {
        if (iops > 10000) { // 10000 IOPS
            return StatusLevel.WARNING;
        } else if (iops > 15000) { // 15000 IOPS
            return StatusLevel.CRITICAL;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估连接级别
     */
    private StatusLevel evaluateConnectionLevel(double connectionRatio) {
        if (connectionRatio > 0.9) { // 90%
            return StatusLevel.CRITICAL;
        } else if (connectionRatio > 0.8) { // 80%
            return StatusLevel.WARNING;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估连接错误级别
     */
    private StatusLevel evaluateConnectionErrorLevel(int connectionErrors) {
        if (connectionErrors > 100) { // 100个
            return StatusLevel.CRITICAL;
        } else if (connectionErrors > 50) { // 50个
            return StatusLevel.WARNING;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估连接超时级别
     */
    private StatusLevel evaluateConnectionTimeoutLevel(int connectionTimeouts) {
        if (connectionTimeouts > 50) { // 50个
            return StatusLevel.CRITICAL;
        } else if (connectionTimeouts > 20) { // 20个
            return StatusLevel.WARNING;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估备份状态级别
     */
    private StatusLevel evaluateBackupStatusLevel(String backupStatus) {
        if ("Failed".equals(backupStatus)) {
            return StatusLevel.CRITICAL;
        } else if ("InProgress".equals(backupStatus)) {
            return StatusLevel.WARNING;
        } else if ("Completed".equals(backupStatus)) {
            return StatusLevel.NORMAL;
        } else {
            return StatusLevel.WARNING;
        }
    }

    /**
     * 评估备份时间级别
     */
    private StatusLevel evaluateBackupTimeLevel(Date lastBackupTime) {
        if (lastBackupTime == null) {
            return StatusLevel.CRITICAL;
        }

        long timeDiff = System.currentTimeMillis() - lastBackupTime.getTime();
        long daysDiff = timeDiff / (24 * 60 * 60 * 1000);

        if (daysDiff > 7) { // 7天
            return StatusLevel.CRITICAL;
        } else if (daysDiff > 3) { // 3天
            return StatusLevel.WARNING;
        } else {
            return StatusLevel.NORMAL;
        }
    }

    /**
     * 评估备份大小级别
     */
    private StatusLevel evaluateBackupSizeLevel(long backupSize) {
        if (backupSize > 100 * 1024 * 1024 * 1024) { // 100GB
            return StatusLevel.WARNING;
        } else if (backupSize > 500 * 1024 * 1024 * 1024) { // 500GB
            return StatusLevel.CRITICAL;
        } else {
            return StatusLevel.NORMAL;
        }
    }
}

三、Redis缓存监控

3.1 Redis监控服务

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/**
 * Redis缓存监控服务
 */
@Service
public class RedisMonitorService {

    @Autowired
    private RedisConnectionManager redisConnectionManager;

    @Autowired
    private RedisMetricsCollector redisMetricsCollector;

    @Autowired
    private RedisHealthAnalyzer redisHealthAnalyzer;

    @Autowired
    private RedisOptimizer redisOptimizer;

    private final ScheduledExecutorService monitorScheduler;
    private final Map<String, RedisInstance> monitoredInstances;

    public RedisMonitorService() {
        this.monitorScheduler = Executors.newScheduledThreadPool(10);
        this.monitoredInstances = new ConcurrentHashMap<>();
    }

    /**
     * 启动Redis监控
     */
    public void startMonitoring() {
        // 启动定期监控任务
        monitorScheduler.scheduleAtFixedRate(
            this::monitorRedisInstances,
            0,
            30, // 30秒
            TimeUnit.SECONDS
        );

        log.info("Redis缓存监控启动成功");
    }

    /**
     * 停止Redis监控
     */
    public void stopMonitoring() {
        try {
            monitorScheduler.shutdown();
            if (!monitorScheduler.awaitTermination(30, TimeUnit.SECONDS)) {
                monitorScheduler.shutdownNow();
            }

            log.info("Redis缓存监控停止成功");

        } catch (Exception e) {
            log.error("Redis缓存监控停止失败", e);
        }
    }

    /**
     * 初始化Redis连接
     */
    public void initializeConnections() {
        try {
            // 获取所有Redis实例
            List<RedisInstance> instances = redisConnectionManager.getAllInstances();

            // 初始化每个实例的连接
            for (RedisInstance instance : instances) {
                initializeInstanceConnection(instance);
                monitoredInstances.put(instance.getInstanceId(), instance);
            }

            log.info("Redis实例连接初始化完成，实例数量: {}", instances.size());

        } catch (Exception e) {
            log.error("Redis连接初始化失败", e);
            throw new ConnectionException("Redis连接初始化失败", e);
        }
    }

    /**
     * 监控Redis实例
     */
    private void monitorRedisInstances() {
        try {
            for (RedisInstance instance : monitoredInstances.values()) {
                monitorSingleInstance(instance);
            }

        } catch (Exception e) {
            log.error("Redis实例监控失败", e);
        }
    }

    /**
     * 监控单个Redis实例
     */
    private void monitorSingleInstance(RedisInstance instance) {
        try {
            // 1. 收集实例指标
            RedisMetrics metrics = redisMetricsCollector.collectMetrics(instance);

            // 2. 分析实例健康状态
            RedisHealthStatus healthStatus = redisHealthAnalyzer.analyzeHealth(instance, metrics);

            // 3. 检查实例状态
            if (!healthStatus.isHealthy()) {
                handleUnhealthyInstance(instance, healthStatus);
            }

            // 4. 尝试性能优化
            if (healthStatus.needsOptimization()) {
                attemptOptimization(instance, healthStatus);
            }

            // 5. 记录监控结果
            recordMonitoringResult(instance, metrics, healthStatus);

        } catch (Exception e) {
            log.error("Redis实例监控失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 处理不健康实例
     */
    private void handleUnhealthyInstance(RedisInstance instance, RedisHealthStatus healthStatus) {
        try {
            // 1. 发送实例告警
            sendInstanceAlert(instance, healthStatus);

            // 2. 记录实例问题
            recordInstanceIssue(instance, healthStatus);

            // 3. 尝试自动修复
            if (healthStatus.isAutoRepairable()) {
                attemptAutoRepair(instance, healthStatus);
            }

        } catch (Exception e) {
            log.error("不健康Redis实例处理失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 发送实例告警
     */
    private void sendInstanceAlert(RedisInstance instance, RedisHealthStatus healthStatus) {
        RedisAlert alert = new RedisAlert();
        alert.setAlertType(AlertType.REDIS_UNHEALTHY);
        alert.setSeverity(healthStatus.getSeverity());
        alert.setMessage("Redis实例状态异常: " + instance.getInstanceId());
        alert.setInstance(instance);
        alert.setHealthStatus(healthStatus);
        alert.setTimestamp(System.currentTimeMillis());

        // 发送告警
        alertService.sendAlert(alert);
    }

    /**
     * 尝试自动修复
     */
    private void attemptAutoRepair(RedisInstance instance, RedisHealthStatus healthStatus) {
        try {
            log.info("尝试自动修复Redis实例: {}", instance.getInstanceId());

            // 根据问题类型选择修复策略
            switch (healthStatus.getIssueType()) {
                case CONNECTION_ISSUE:
                    repairConnectionIssue(instance);
                    break;
                case MEMORY_ISSUE:
                    repairMemoryIssue(instance);
                    break;
                case PERFORMANCE_ISSUE:
                    repairPerformanceIssue(instance);
                    break;
                case KEY_EXPIRATION_ISSUE:
                    repairKeyExpirationIssue(instance);
                    break;
                default:
                    log.warn("无法自动修复的问题类型: {}", healthStatus.getIssueType());
            }

        } catch (Exception e) {
            log.error("Redis实例自动修复失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 尝试性能优化
     */
    private void attemptOptimization(RedisInstance instance, RedisHealthStatus healthStatus) {
        try {
            log.info("尝试Redis实例性能优化: {}", instance.getInstanceId());

            // 根据性能问题选择优化策略
            switch (healthStatus.getPerformanceIssueType()) {
                case LOW_HIT_RATIO:
                    redisOptimizer.optimizeHitRatio(instance);
                    break;
                case HIGH_MEMORY_USAGE:
                    redisOptimizer.optimizeMemoryUsage(instance);
                    break;
                case SLOW_COMMANDS:
                    redisOptimizer.optimizeSlowCommands(instance);
                    break;
                case HIGH_EVICTION_RATE:
                    redisOptimizer.optimizeEvictionRate(instance);
                    break;
                default:
                    log.warn("无法自动优化的性能问题类型: {}", healthStatus.getPerformanceIssueType());
            }

        } catch (Exception e) {
            log.error("Redis实例性能优化失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 修复连接问题
     */
    private void repairConnectionIssue(RedisInstance instance) {
        try {
            // 重启实例连接
            redisConnectionManager.restartInstanceConnection(instance);
            log.info("Redis实例连接修复成功: {}", instance.getInstanceId());

        } catch (Exception e) {
            log.error("Redis实例连接修复失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 修复内存问题
     */
    private void repairMemoryIssue(RedisInstance instance) {
        try {
            // 清理过期键
            redisOptimizer.cleanupExpiredKeys(instance);
            log.info("Redis实例内存修复成功: {}", instance.getInstanceId());

        } catch (Exception e) {
            log.error("Redis实例内存修复失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 修复性能问题
     */
    private void repairPerformanceIssue(RedisInstance instance) {
        try {
            // 调整实例参数
            redisOptimizer.adjustInstanceParameters(instance);
            log.info("Redis实例性能修复成功: {}", instance.getInstanceId());

        } catch (Exception e) {
            log.error("Redis实例性能修复失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 修复键过期问题
     */
    private void repairKeyExpirationIssue(RedisInstance instance) {
        try {
            // 调整过期策略
            redisOptimizer.adjustExpirationPolicy(instance);
            log.info("Redis实例键过期修复成功: {}", instance.getInstanceId());

        } catch (Exception e) {
            log.error("Redis实例键过期修复失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 记录监控结果
     */
    private void recordMonitoringResult(RedisInstance instance, RedisMetrics metrics, RedisHealthStatus healthStatus) {
        RedisMonitoringResult result = new RedisMonitoringResult();
        result.setInstanceId(instance.getInstanceId());
        result.setTimestamp(System.currentTimeMillis());
        result.setMetrics(metrics);
        result.setHealthStatus(healthStatus);

        // 存储监控结果
        resultStorage.storeRedisResult(result);
    }
}

3.2 Redis指标收集器

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/**
 * Redis指标收集器
 */
@Component
public class RedisMetricsCollector {

    @Autowired
    private RedisConnectionManager connectionManager;

    @Autowired
    private CloudAPIClient cloudAPIClient;

    /**
     * 收集Redis指标
     */
    public RedisMetrics collectMetrics(RedisInstance instance) {
        RedisMetrics metrics = new RedisMetrics();

        try {
            // 1. 收集基础指标
            collectBasicMetrics(instance, metrics);

            // 2. 收集性能指标
            collectPerformanceMetrics(instance, metrics);

            // 3. 收集内存指标
            collectMemoryMetrics(instance, metrics);

            // 4. 收集键值指标
            collectKeyValueMetrics(instance, metrics);

            // 5. 收集复制指标
            collectReplicationMetrics(instance, metrics);

        } catch (Exception e) {
            log.error("Redis指标收集失败: {}", instance.getInstanceId(), e);
        }

        return metrics;
    }

    /**
     * 收集基础指标
     */
    private void collectBasicMetrics(RedisInstance instance, RedisMetrics metrics) {
        try {
            // 实例状态
            String instanceStatus = cloudAPIClient.getRedisInstanceStatus(instance.getInstanceId());
            metrics.setInstanceStatus(instanceStatus);

            // 实例类型
            String instanceType = cloudAPIClient.getRedisInstanceType(instance.getInstanceId());
            metrics.setInstanceType(instanceType);

            // Redis版本
            String redisVersion = cloudAPIClient.getRedisVersion(instance.getInstanceId());
            metrics.setRedisVersion(redisVersion);

            // 运行时间
            long uptime = cloudAPIClient.getRedisUptime(instance.getInstanceId());
            metrics.setUptime(uptime);

        } catch (Exception e) {
            log.error("Redis基础指标收集失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 收集性能指标
     */
    private void collectPerformanceMetrics(RedisInstance instance, RedisMetrics metrics) {
        try {
            // 每秒操作数
            double opsPerSecond = cloudAPIClient.getRedisOpsPerSecond(instance.getInstanceId());
            metrics.setOpsPerSecond(opsPerSecond);

            // 平均响应时间
            double avgResponseTime = cloudAPIClient.getRedisAverageResponseTime(instance.getInstanceId());
            metrics.setAverageResponseTime(avgResponseTime);

            // 最大响应时间
            double maxResponseTime = cloudAPIClient.getRedisMaxResponseTime(instance.getInstanceId());
            metrics.setMaxResponseTime(maxResponseTime);

            // 连接数
            int connectedClients = cloudAPIClient.getRedisConnectedClients(instance.getInstanceId());
            metrics.setConnectedClients(connectedClients);

            // 阻塞客户端数
            int blockedClients = cloudAPIClient.getRedisBlockedClients(instance.getInstanceId());
            metrics.setBlockedClients(blockedClients);

            // 慢查询数
            int slowLogCount = cloudAPIClient.getRedisSlowLogCount(instance.getInstanceId());
            metrics.setSlowLogCount(slowLogCount);

        } catch (Exception e) {
            log.error("Redis性能指标收集失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 收集内存指标
     */
    private void collectMemoryMetrics(RedisInstance instance, RedisMetrics metrics) {
        try {
            // 已使用内存
            long usedMemory = cloudAPIClient.getRedisUsedMemory(instance.getInstanceId());
            metrics.setUsedMemory(usedMemory);

            // 最大内存
            long maxMemory = cloudAPIClient.getRedisMaxMemory(instance.getInstanceId());
            metrics.setMaxMemory(maxMemory);

            // 内存使用率
            double memoryUsage = (double) usedMemory / maxMemory;
            metrics.setMemoryUsage(memoryUsage);

            // 内存碎片率
            double memoryFragmentationRatio = cloudAPIClient.getRedisMemoryFragmentationRatio(instance.getInstanceId());
            metrics.setMemoryFragmentationRatio(memoryFragmentationRatio);

            // 已使用内存峰值
            long usedMemoryPeak = cloudAPIClient.getRedisUsedMemoryPeak(instance.getInstanceId());
            metrics.setUsedMemoryPeak(usedMemoryPeak);

            // 内存使用率峰值
            double memoryUsagePeak = (double) usedMemoryPeak / maxMemory;
            metrics.setMemoryUsagePeak(memoryUsagePeak);

        } catch (Exception e) {
            log.error("Redis内存指标收集失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 收集键值指标
     */
    private void collectKeyValueMetrics(RedisInstance instance, RedisMetrics metrics) {
        try {
            // 键总数
            int totalKeys = cloudAPIClient.getRedisTotalKeys(instance.getInstanceId());
            metrics.setTotalKeys(totalKeys);

            // 过期键数
            int expiredKeys = cloudAPIClient.getRedisExpiredKeys(instance.getInstanceId());
            metrics.setExpiredKeys(expiredKeys);

            // 键空间命中数
            long keyspaceHits = cloudAPIClient.getRedisKeyspaceHits(instance.getInstanceId());
            metrics.setKeyspaceHits(keyspaceHits);

            // 键空间未命中数
            long keyspaceMisses = cloudAPIClient.getRedisKeyspaceMisses(instance.getInstanceId());
            metrics.setKeyspaceMisses(keyspaceMisses);

            // 命中率
            double hitRatio = (double) keyspaceHits / (keyspaceHits + keyspaceMisses);
            metrics.setHitRatio(hitRatio);

            // 驱逐键数
            int evictedKeys = cloudAPIClient.getRedisEvictedKeys(instance.getInstanceId());
            metrics.setEvictedKeys(evictedKeys);

        } catch (Exception e) {
            log.error("Redis键值指标收集失败: {}", instance.getInstanceId(), e);
        }
    }

    /**
     * 收集复制指标
     */
    private void collectReplicationMetrics(RedisInstance instance, RedisMetrics metrics) {
        try {
            // 主从状态
            String replicationRole = cloudAPIClient.getRedisReplicationRole(instance.getInstanceId());
            metrics.setReplicationRole(replicationRole);

            // 从节点数
            int connectedSlaves = cloudAPIClient.getRedisConnectedSlaves(instance.getInstanceId());
            metrics.setConnectedSlaves(connectedSlaves);

            // 复制延迟
            long replicationLag = cloudAPIClient.getRedisReplicationLag(instance.getInstanceId());
            metrics.setReplicationLag(replicationLag);

            // 复制状态
            String replicationStatus = cloudAPIClient.getRedisReplicationStatus(instance.getInstanceId());
            metrics.setReplicationStatus(replicationStatus);

        } catch (Exception e) {
            log.error("Redis复制指标收集失败: {}", instance.getInstanceId(), e);
        }
    }
}

四、企业级RDS-Redis巡检方案

4.1 巡检配置管理

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/**
 * RDS-Redis巡检配置管理服务
 */
@Service
public class RDSRedisInspectionConfigService {

    @Autowired
    private InspectionConfigRepository configRepository;

    /**
     * 获取巡检配置
     */
    public RDSRedisInspectionConfig getConfig(String configId) {
        return configRepository.findById(configId)
            .orElseThrow(() -> new ConfigNotFoundException("RDS-Redis巡检配置不存在: " + configId));
    }

    /**
     * 保存巡检配置
     */
    public void saveConfig(RDSRedisInspectionConfig config) {
        try {
            // 验证配置
            validateConfig(config);

            // 保存配置
            configRepository.save(config);

            log.info("RDS-Redis巡检配置保存成功: {}", config.getConfigId());

        } catch (Exception e) {
            log.error("RDS-Redis巡检配置保存失败", e);
            throw new ConfigSaveException("RDS-Redis巡检配置保存失败", e);
        }
    }

    /**
     * 更新巡检配置
     */
    public void updateConfig(String configId, RDSRedisInspectionConfig config) {
        try {
            // 检查配置是否存在
            if (!configRepository.existsById(configId)) {
                throw new ConfigNotFoundException("RDS-Redis巡检配置不存在: " + configId);
            }

            // 验证配置
            validateConfig(config);

            // 更新配置
            config.setConfigId(configId);
            configRepository.save(config);

            log.info("RDS-Redis巡检配置更新成功: {}", configId);

        } catch (Exception e) {
            log.error("RDS-Redis巡检配置更新失败", e);
            throw new ConfigUpdateException("RDS-Redis巡检配置更新失败", e);
        }
    }

    /**
     * 删除巡检配置
     */
    public void deleteConfig(String configId) {
        try {
            if (!configRepository.existsById(configId)) {
                throw new ConfigNotFoundException("RDS-Redis巡检配置不存在: " + configId);
            }

            configRepository.deleteById(configId);

            log.info("RDS-Redis巡检配置删除成功: {}", configId);

        } catch (Exception e) {
            log.error("RDS-Redis巡检配置删除失败", e);
            throw new ConfigDeleteException("RDS-Redis巡检配置删除失败", e);
        }
    }

    /**
     * 获取所有配置
     */
    public List<RDSRedisInspectionConfig> getAllConfigs() {
        return configRepository.findAll();
    }

    /**
     * 验证配置
     */
    private void validateConfig(RDSRedisInspectionConfig config) {
        if (config.getConfigId() == null || config.getConfigId().isEmpty()) {
            throw new ConfigValidationException("配置ID不能为空");
        }

        if (config.getRdsInstances() == null || config.getRdsInstances().isEmpty()) {
            throw new ConfigValidationException("RDS实例不能为空");
        }

        if (config.getRedisInstances() == null || config.getRedisInstances().isEmpty()) {
            throw new ConfigValidationException("Redis实例不能为空");
        }

        if (config.getInspectionInterval() <= 0) {
            throw new ConfigValidationException("巡检间隔必须大于0");
        }

        if (config.getAlertThresholds() == null || config.getAlertThresholds().isEmpty()) {
            throw new ConfigValidationException("告警阈值不能为空");
        }
    }
}

4.2 巡检报告生成

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/**
 * RDS-Redis巡检报告生成服务
 */
@Service
public class RDSRedisInspectionReportService {

    @Autowired
    private InspectionResultStorageService resultStorageService;

    @Autowired
    private ReportTemplateService templateService;

    /**
     * 生成RDS-Redis巡检报告
     */
    public RDSRedisInspectionReport generateReport(String environment, Date startTime, Date endTime) {
        RDSRedisInspectionReport report = new RDSRedisInspectionReport();

        try {
            // 1. 设置报告基本信息
            report.setReportId(generateReportId());
            report.setEnvironment(environment);
            report.setStartTime(startTime);
            report.setEndTime(endTime);
            report.setGenerateTime(new Date());

            // 2. 获取RDS巡检结果
            List<RDSMonitoringResult> rdsResults = resultStorageService.getRDSResultsByEnvironment(environment, startTime, endTime);

            // 3. 获取Redis巡检结果
            List<RedisMonitoringResult> redisResults = resultStorageService.getRedisResultsByEnvironment(environment, startTime, endTime);

            // 4. 生成RDS统计信息
            RDSStatistics rdsStats = generateRDSStatistics(rdsResults);
            report.setRdsStatistics(rdsStats);

            // 5. 生成Redis统计信息
            RedisStatistics redisStats = generateRedisStatistics(redisResults);
            report.setRedisStatistics(redisStats);

            // 6. 生成性能分析
            PerformanceAnalysis performanceAnalysis = generatePerformanceAnalysis(rdsResults, redisResults);
            report.setPerformanceAnalysis(performanceAnalysis);

            // 7. 生成异常分析
            ExceptionAnalysis exceptionAnalysis = generateExceptionAnalysis(rdsResults, redisResults);
            report.setExceptionAnalysis(exceptionAnalysis);

            // 8. 生成建议
            List<Recommendation> recommendations = generateRecommendations(report);
            report.setRecommendations(recommendations);

            // 9. 生成报告摘要
            String summary = generateSummary(report);
            report.setSummary(summary);

            log.info("RDS-Redis巡检报告生成成功: {}", report.getReportId());

        } catch (Exception e) {
            log.error("RDS-Redis巡检报告生成失败", e);
            throw new ReportGenerationException("RDS-Redis巡检报告生成失败", e);
        }

        return report;
    }

    /**
     * 生成RDS统计信息
     */
    private RDSStatistics generateRDSStatistics(List<RDSMonitoringResult> results) {
        RDSStatistics stats = new RDSStatistics();

        try {
            // 计算基础统计
            stats.setTotalInspections(results.size());
            stats.setHealthyInspections((int) results.stream()
                .filter(result -> result.getHealthStatus().isHealthy())
                .count());
            stats.setUnhealthyInspections((int) results.stream()
                .filter(result -> !result.getHealthStatus().isHealthy())
                .count());

            // 计算健康率
            if (stats.getTotalInspections() > 0) {
                stats.setHealthRate((double) stats.getHealthyInspections() / stats.getTotalInspections());
            }

            // 计算平均CPU使用率
            double avgCpuUsage = results.stream()
                .mapToDouble(result -> result.getMetrics().getCpuUsage())
                .average()
                .orElse(0.0);
            stats.setAverageCpuUsage(avgCpuUsage);

            // 计算平均内存使用率
            double avgMemoryUsage = results.stream()
                .mapToDouble(result -> result.getMetrics().getMemoryUsage())
                .average()
                .orElse(0.0);
            stats.setAverageMemoryUsage(avgMemoryUsage);

            // 计算平均QPS
            double avgQps = results.stream()
                .mapToDouble(result -> result.getMetrics().getQps())
                .average()
                .orElse(0.0);
            stats.setAverageQps(avgQps);

            // 计算平均延迟
            double avgLatency = results.stream()
                .mapToDouble(result -> result.getMetrics().getAverageLatency())
                .average()
                .orElse(0.0);
            stats.setAverageLatency(avgLatency);

            // 计算平均磁盘使用率
            double avgDiskUsage = results.stream()
                .mapToDouble(result -> result.getMetrics().getDiskUsage())
                .average()
                .orElse(0.0);
            stats.setAverageDiskUsage(avgDiskUsage);

        } catch (Exception e) {
            log.error("RDS统计信息生成失败", e);
        }

        return stats;
    }

    /**
     * 生成Redis统计信息
     */
    private RedisStatistics generateRedisStatistics(List<RedisMonitoringResult> results) {
        RedisStatistics stats = new RedisStatistics();

        try {
            // 计算基础统计
            stats.setTotalInspections(results.size());
            stats.setHealthyInspections((int) results.stream()
                .filter(result -> result.getHealthStatus().isHealthy())
                .count());
            stats.setUnhealthyInspections((int) results.stream()
                .filter(result -> !result.getHealthStatus().isHealthy())
                .count());

            // 计算健康率
            if (stats.getTotalInspections() > 0) {
                stats.setHealthRate((double) stats.getHealthyInspections() / stats.getTotalInspections());
            }

            // 计算平均内存使用率
            double avgMemoryUsage = results.stream()
                .mapToDouble(result -> result.getMetrics().getMemoryUsage())
                .average()
                .orElse(0.0);
            stats.setAverageMemoryUsage(avgMemoryUsage);

            // 计算平均命中率
            double avgHitRatio = results.stream()
                .mapToDouble(result -> result.getMetrics().getHitRatio())
                .average()
                .orElse(0.0);
            stats.setAverageHitRatio(avgHitRatio);

            // 计算平均响应时间
            double avgResponseTime = results.stream()
                .mapToDouble(result -> result.getMetrics().getAverageResponseTime())
                .average()
                .orElse(0.0);
            stats.setAverageResponseTime(avgResponseTime);

            // 计算平均每秒操作数
            double avgOpsPerSecond = results.stream()
                .mapToDouble(result -> result.getMetrics().getOpsPerSecond())
                .average()
                .orElse(0.0);
            stats.setAverageOpsPerSecond(avgOpsPerSecond);

            // 计算平均键数量
            double avgTotalKeys = results.stream()
                .mapToDouble(result -> result.getMetrics().getTotalKeys())
                .average()
                .orElse(0.0);
            stats.setAverageTotalKeys(avgTotalKeys);

        } catch (Exception e) {
            log.error("Redis统计信息生成失败", e);
        }

        return stats;
    }

    /**
     * 生成性能分析
     */
    private PerformanceAnalysis generatePerformanceAnalysis(List<RDSMonitoringResult> rdsResults, 
                                                           List<RedisMonitoringResult> redisResults) {
        PerformanceAnalysis analysis = new PerformanceAnalysis();

        try {
            // 分析RDS性能趋势
            List<Double> rdsCpuUsages = rdsResults.stream()
                .map(result -> result.getMetrics().getCpuUsage())
                .collect(Collectors.toList());
            analysis.setRdsCpuUsageTrend(analyzeTrend(rdsCpuUsages));

            List<Double> rdsLatencies = rdsResults.stream()
                .map(result -> result.getMetrics().getAverageLatency())
                .collect(Collectors.toList());
            analysis.setRdsLatencyTrend(analyzeTrend(rdsLatencies));

            // 分析Redis性能趋势
            List<Double> redisHitRatios = redisResults.stream()
                .map(result -> result.getMetrics().getHitRatio())
                .collect(Collectors.toList());
            analysis.setRedisHitRatioTrend(analyzeTrend(redisHitRatios));

            List<Double> redisResponseTimes = redisResults.stream()
                .map(result -> result.getMetrics().getAverageResponseTime())
                .collect(Collectors.toList());
            analysis.setRedisResponseTimeTrend(analyzeTrend(redisResponseTimes));

            // 分析整体性能
            analysis.setOverallPerformanceScore(calculateOverallPerformanceScore(rdsResults, redisResults));

        } catch (Exception e) {
            log.error("性能分析生成失败", e);
        }

        return analysis;
    }

    /**
     * 生成异常分析
     */
    private ExceptionAnalysis generateExceptionAnalysis(List<RDSMonitoringResult> rdsResults, 
                                                      List<RedisMonitoringResult> redisResults) {
        ExceptionAnalysis analysis = new ExceptionAnalysis();

        try {
            // 统计RDS异常类型
            Map<String, Integer> rdsExceptionCount = new HashMap<>();
            for (RDSMonitoringResult result : rdsResults) {
                if (!result.getHealthStatus().isHealthy()) {
                    String issueType = result.getHealthStatus().getIssueType().name();
                    rdsExceptionCount.merge(issueType, 1, Integer::sum);
                }
            }
            analysis.setRdsExceptionCount(rdsExceptionCount);

            // 统计Redis异常类型
            Map<String, Integer> redisExceptionCount = new HashMap<>();
            for (RedisMonitoringResult result : redisResults) {
                if (!result.getHealthStatus().isHealthy()) {
                    String issueType = result.getHealthStatus().getIssueType().name();
                    redisExceptionCount.merge(issueType, 1, Integer::sum);
                }
            }
            analysis.setRedisExceptionCount(redisExceptionCount);

            // 找出最常见的异常
            String mostCommonRdsException = rdsExceptionCount.entrySet().stream()
                .max(Map.Entry.comparingByValue())
                .map(Map.Entry::getKey)
                .orElse("无");
            analysis.setMostCommonRdsException(mostCommonRdsException);

            String mostCommonRedisException = redisExceptionCount.entrySet().stream()
                .max(Map.Entry.comparingByValue())
                .map(Map.Entry::getKey)
                .orElse("无");
            analysis.setMostCommonRedisException(mostCommonRedisException);

        } catch (Exception e) {
            log.error("异常分析生成失败", e);
        }

        return analysis;
    }

    /**
     * 生成建议
     */
    private List<Recommendation> generateRecommendations(RDSRedisInspectionReport report) {
        List<Recommendation> recommendations = new ArrayList<>();

        try {
            // 基于RDS统计生成建议
            RDSStatistics rdsStats = report.getRdsStatistics();
            if (rdsStats.getHealthRate() < 0.8) {
                Recommendation rec = new Recommendation();
                rec.setType(RecommendationType.RDS_STABILITY);
                rec.setPriority(Priority.HIGH);
                rec.setTitle("提升RDS稳定性");
                rec.setDescription("当前RDS健康率为" + String.format("%.2f", rdsStats.getHealthRate() * 100) + "%，建议检查RDS配置和性能");
                recommendations.add(rec);
            }

            if (rdsStats.getAverageCpuUsage() > 0.8) {
                Recommendation rec = new Recommendation();
                rec.setType(RecommendationType.RDS_PERFORMANCE);
                rec.setPriority(Priority.HIGH);
                rec.setTitle("优化RDS性能");
                rec.setDescription("平均CPU使用率为" + String.format("%.2f", rdsStats.getAverageCpuUsage() * 100) + "%，建议优化查询和调整配置");
                recommendations.add(rec);
            }

            // 基于Redis统计生成建议
            RedisStatistics redisStats = report.getRedisStatistics();
            if (redisStats.getHealthRate() < 0.8) {
                Recommendation rec = new Recommendation();
                rec.setType(RecommendationType.REDIS_STABILITY);
                rec.setPriority(Priority.HIGH);
                rec.setTitle("提升Redis稳定性");
                rec.setDescription("当前Redis健康率为" + String.format("%.2f", redisStats.getHealthRate() * 100) + "%，建议检查Redis配置和内存使用");
                recommendations.add(rec);
            }

            if (redisStats.getAverageHitRatio() < 0.8) {
                Recommendation rec = new Recommendation();
                rec.setType(RecommendationType.REDIS_PERFORMANCE);
                rec.setPriority(Priority.MEDIUM);
                rec.setTitle("优化Redis命中率");
                rec.setDescription("平均命中率为" + String.format("%.2f", redisStats.getAverageHitRatio() * 100) + "%，建议优化缓存策略");
                recommendations.add(rec);
            }

            // 基于异常分析生成建议
            ExceptionAnalysis exceptionAnalysis = report.getExceptionAnalysis();
            if (exceptionAnalysis.getMostCommonRdsException() != null && 
                !exceptionAnalysis.getMostCommonRdsException().equals("无")) {
                Recommendation rec = new Recommendation();
                rec.setType(RecommendationType.RDS_EXCEPTION_HANDLING);
                rec.setPriority(Priority.MEDIUM);
                rec.setTitle("处理RDS常见异常");
                rec.setDescription("最常见的RDS异常是：" + exceptionAnalysis.getMostCommonRdsException() + "，建议优先处理");
                recommendations.add(rec);
            }

            if (exceptionAnalysis.getMostCommonRedisException() != null && 
                !exceptionAnalysis.getMostCommonRedisException().equals("无")) {
                Recommendation rec = new Recommendation();
                rec.setType(RecommendationType.REDIS_EXCEPTION_HANDLING);
                rec.setPriority(Priority.MEDIUM);
                rec.setTitle("处理Redis常见异常");
                rec.setDescription("最常见的Redis异常是：" + exceptionAnalysis.getMostCommonRedisException() + "，建议优先处理");
                recommendations.add(rec);
            }

        } catch (Exception e) {
            log.error("建议生成失败", e);
        }

        return recommendations;
    }

    /**
     * 生成报告摘要
     */
    private String generateSummary(RDSRedisInspectionReport report) {
        StringBuilder summary = new StringBuilder();

        summary.append("RDS-Redis巡检报告摘要\n");
        summary.append("环境: ").append(report.getEnvironment()).append("\n");
        summary.append("统计期间: ").append(report.getStartTime()).append(" - ").append(report.getEndTime()).append("\n");
        summary.append("RDS健康率: ").append(String.format("%.2f", report.getRdsStatistics().getHealthRate() * 100)).append("%\n");
        summary.append("Redis健康率: ").append(String.format("%.2f", report.getRedisStatistics().getHealthRate() * 100)).append("%\n");
        summary.append("RDS平均CPU使用率: ").append(String.format("%.2f", report.getRdsStatistics().getAverageCpuUsage() * 100)).append("%\n");
        summary.append("Redis平均命中率: ").append(String.format("%.2f", report.getRedisStatistics().getAverageHitRatio() * 100)).append("%\n");

        if (!report.getRecommendations().isEmpty()) {
            summary.append("主要建议: ").append(report.getRecommendations().get(0).getTitle()).append("\n");
        }

        return summary.toString();
    }

    /**
     * 分析趋势
     */
    private TrendDirection analyzeTrend(List<Double> values) {
        if (values.size() < 2) {
            return TrendDirection.STABLE;
        }

        // 简单趋势分析
        double firstHalf = values.subList(0, values.size() / 2).stream()
            .mapToDouble(Double::doubleValue)
            .average()
            .orElse(0.0);

        double secondHalf = values.subList(values.size() / 2, values.size()).stream()
            .mapToDouble(Double::doubleValue)
            .average()
            .orElse(0.0);

        if (secondHalf > firstHalf * 1.1) {
            return TrendDirection.INCREASING;
        } else if (secondHalf < firstHalf * 0.9) {
            return TrendDirection.DECREASING;
        } else {
            return TrendDirection.STABLE;
        }
    }

    /**
     * 计算整体性能评分
     */
    private double calculateOverallPerformanceScore(List<RDSMonitoringResult> rdsResults, 
                                                   List<RedisMonitoringResult> redisResults) {
        double rdsScore = 0.0;
        double redisScore = 0.0;

        // 计算RDS性能评分
        if (!rdsResults.isEmpty()) {
            double avgCpuUsage = rdsResults.stream()
                .mapToDouble(result -> result.getMetrics().getCpuUsage())
                .average()
                .orElse(0.0);
            double avgLatency = rdsResults.stream()
                .mapToDouble(result -> result.getMetrics().getAverageLatency())
                .average()
                .orElse(0.0);

            rdsScore = (1.0 - avgCpuUsage) * 0.5 + (1.0 - Math.min(avgLatency / 1000.0, 1.0)) * 0.5;
        }

        // 计算Redis性能评分
        if (!redisResults.isEmpty()) {
            double avgHitRatio = redisResults.stream()
                .mapToDouble(result -> result.getMetrics().getHitRatio())
                .average()
                .orElse(0.0);
            double avgResponseTime = redisResults.stream()
                .mapToDouble(result -> result.getMetrics().getAverageResponseTime())
                .average()
                .orElse(0.0);

            redisScore = avgHitRatio * 0.5 + (1.0 - Math.min(avgResponseTime / 100.0, 1.0)) * 0.5;
        }

        return (rdsScore + redisScore) / 2.0;
    }

    /**
     * 生成报告ID
     */
    private String generateReportId() {
        return "rds-redis-report-" + System.currentTimeMillis() + "-" + Thread.currentThread().getId();
    }
}

五、最佳实践与总结

5.1 RDS-Redis自动巡检最佳实践

  1. 云数据库监控策略

    • 建立全面的RDS监控体系
    • 监控实例健康状态
    • 监控性能指标

  2. 缓存监控策略

    • 建立完善的Redis监控
    • 监控缓存命中率
    • 监控内存使用情况

  3. 性能优化策略

    • 优化数据库查询
    • 优化缓存策略
    • 监控资源使用率

  4. 异常处理机制

    • 建立完善的异常分类
    • 实现智能告警
    • 提供自动修复能力

5.2 架构师级云数据库运维技能

  1. 云数据库管理能力

    • 深入理解RDS架构
    • 掌握实例管理
    • 管理备份和恢复

  2. 缓存管理能力

    • 深入理解Redis架构
    • 掌握缓存策略
    • 管理内存和性能

  3. 性能调优能力

    • 优化数据库性能
    • 优化缓存性能
    • 调整配置参数

  4. 监控运维能力

    • 建立监控体系
    • 实现自动化运维
    • 持续优化改进

5.3 持续改进建议

  1. 监控体系完善

    • 完善监控指标
    • 优化告警策略
    • 提升监控精度

  2. 自动化程度提升

    • 实现更多自动修复
    • 优化巡检策略
    • 提升运维效率

  3. 知识积累

    • 建立运维知识库
    • 总结最佳实践
    • 形成标准化流程

总结

RDS-Redis自动巡检是企业级云数据库运维的核心能力，通过智能的云数据库监控策略、完善的缓存优化机制和系统化的性能管理，能够及时发现数据库异常，预防数据丢失，保障企业级应用的高可用性。本文从云数据库监控设计到缓存优化，从基础原理到企业级实践，系统梳理了RDS-Redis自动巡检的完整解决方案。

关键要点：

  1. 云数据库监控策略：全面的RDS监控和实例健康检查
  2. 缓存监控机制：完善的Redis监控和性能优化
  3. 性能优化方案：智能的性能监控和优化
  4. 企业级实践：配置管理、报告生成、持续改进

通过深入理解这些技术要点，架构师能够设计出完善的RDS-Redis自动巡检系统，提升云数据库的稳定性和可靠性，确保企业级应用的高可用性。