## 1. Redis内置监控命令
– INFO cluster：查看集群的详细信息
– CLUSTER INFO：查看集群的状态信息
– CLUSTER NODES：查看集群中的节点信息
– CLUSTER SLOTS：查看集群中的槽位分配情况
– MONITOR：实时监控Redis的命令执行情况
– CLIENT LIST：查看客户端连接情况
– SLOWLOG：查看慢查询日志

## 2. 第三方监控工具
– Prometheus：开源的监控系统，用于收集和存储时间序列数据
– Grafana：开源的可视化平台，用于展示监控数据
– Redis Exporter：用于将Redis的监控指标导出到Prometheus
– Redis Sentinel：Redis的高可用性解决方案，也可以用于监控
– Redis Cluster：Redis的集群解决方案，也可以用于监控

## 3. 云服务监控
– AWS CloudWatch：AWS的监控服务
– Azure Monitor：Azure的监控服务
– Alibaba Cloud Monitor：阿里云的监控服务
– Tencent Cloud Monitor：腾讯云的监控服务

## 1. 故障检测策略
– 节点心跳检测：通过PING命令检测节点是否存活
– 集群状态检测：定期检查集群的状态
– 槽位状态检测：定期检查槽位的状态
– 网络连接检测：检测节点之间的网络连接

## 2. 故障转移策略
– 自动故障转移：当主节点出现故障时，自动将从节点提升为新的主节点
– 手动故障转移：通过命令手动将从节点提升为新的主节点
– 优先级设置：设置从节点的优先级，决定故障转移的顺序
– 故障转移超时：设置故障转移的超时时间

## 3. 数据恢复策略
– 持久化恢复：通过RDB或AOF文件恢复数据
– 复制恢复：通过主从复制恢复数据
– 集群恢复：通过集群的自动修复机制恢复数据
– 手动恢复：通过手动操作恢复数据

## 4. 集群重平衡策略
– 自动重平衡：集群自动平衡槽位分配
– 手动重平衡：通过命令手动平衡槽位分配
– 槽位迁移：将槽位从一个节点迁移到另一个节点
– 节点添加：添加新节点并分配槽位
– 节点移除：移除节点并重新分配槽位

学习交流加群风哥QQ113257174

Part03-生产环境项目实施方案

3.1 集群监控配置

## 1. 部署Redis Exporter
# 下载Redis Exporter
$ wget https://github.com/oliver006/redis_exporter/releases/download/v1.50.0/redis_exporter-v1.50.0.linux-amd64.tar.gz

# 解压Redis Exporter
$ tar -xzf redis_exporter-v1.50.0.linux-amd64.tar.gz
$ mv redis_exporter-v1.50.0.linux-amd64/redis_exporter /usr/local/bin/

# 创建Redis Exporter服务（每个节点）
$ vi /etc/systemd/system/redis_exporter.service

[Unit]
Description=Redis Exporter
After=network.target

[Service]
Type=simple
User=redis
ExecStart=/usr/local/bin/redis_exporter –redis.addr=redis://192.168.1.100:7000 –redis.password=fgedu@2026
Restart=always

[Install]
WantedBy=multi-user.target

# 启动Redis Exporter服务
$ systemctl daemon-reload
$ systemctl start redis_exporter
$ systemctl enable redis_exporter

## 2. 部署Prometheus
# 下载Prometheus
$ wget https://github.com/prometheus/prometheus/releases/download/v2.47.0/prometheus-2.47.0.linux-amd64.tar.gz

# 解压Prometheus
$ tar -xzf prometheus-2.47.0.linux-amd64.tar.gz
$ mv prometheus-2.47.0.linux-amd64 /usr/local/prometheus

# 创建Prometheus配置文件
$ vi /usr/local/prometheus/prometheus.yml

global:
scrape_interval: 15s
evaluation_interval: 15s

rule_files:
– “redis_cluster_rules.yml”

alerting:
alertmanagers:
– static_configs:
– targets:
– localhost:9093

scrape_configs:
– job_name: “prometheus”
static_configs:
– targets: [“localhost:9090”]

– job_name: “redis_cluster”
static_configs:
– targets: [“192.168.1.100:9121”, “192.168.1.101:9121”, “192.168.1.102:9121”]
labels:
cluster: “redis-cluster”

## 3. 部署Grafana
# 下载Grafana
$ wget https://dl.grafana.com/oss/release/grafana-10.0.0.linux-amd64.tar.gz

# 解压Grafana
$ tar -xzf grafana-10.0.0.linux-amd64.tar.gz
$ mv grafana-10.0.0 /usr/local/grafana

# 创建Grafana服务
$ vi /etc/systemd/system/grafana-server.service

[Unit]
Description=Grafana
After=network.target

[Service]
Type=simple
User=grafana
ExecStart=/usr/local/grafana/bin/grafana-server –config=/usr/local/grafana/conf/defaults.ini –homepath=/usr/local/grafana
Restart=always

[Install]
WantedBy=multi-user.target

# 启动Grafana服务
$ systemctl daemon-reload
$ systemctl start grafana-server
$ systemctl enable grafana-server

## 4. 配置Prometheus告警规则
$ vi /usr/local/prometheus/redis_cluster_rules.yml

groups:
– name: redis_cluster_alerts
rules:
– alert: RedisClusterDown
expr: redis_cluster_state != 1
for: 5m
labels:
severity: critical
annotations:
summary: “Redis cluster down”
description: “Redis cluster {{ $labels.cluster }} is down”

– alert: RedisClusterSlotFail
expr: redis_cluster_slots_fail > 0
for: 5m
labels:
severity: critical
annotations:
summary: “Redis cluster slot fail”
description: “Redis cluster {{ $labels.cluster }} has {{ $value }} failed slots”

– alert: RedisClusterNodeDown
expr: redis_up == 0
for: 5m
labels:
severity: critical
annotations:
summary: “Redis node down”
description: “Redis node {{ $labels.instance }} is down”

– alert: RedisMemoryUsageHigh
expr: redis_used_memory / redis_config_maxmemory * 100 > 80
for: 5m
labels:
severity: warning
annotations:
summary: “Redis memory usage high”
description: “Redis node {{ $labels.instance }} memory usage is {{ $value }}%”

– alert: RedisReplicationLag
expr: redis_replication_offset_delay > 10
for: 5m
labels:
severity: warning
annotations:
summary: “Redis replication lag”
description: “Redis node {{ $labels.instance }} replication lag is {{ $value }} seconds”

## 1. 故障检测
– 监控系统检测到节点故障
– 告警系统发送告警通知
– 运维人员收到告警通知

## 2. 故障确认
– 登录故障节点，检查节点状态
– 查看Redis日志，分析故障原因
– 确认故障类型和影响范围

## 3. 故障处理
– 根据故障类型采取相应的处理措施
– 对于主节点故障，等待自动故障转移或手动执行故障转移
– 对于从节点故障，修复从节点或添加新的从节点
– 对于网络故障，检查网络连接并修复

## 4. 故障恢复
– 确认故障已解决
– 验证集群状态是否正常
– 验证数据是否一致
– 记录故障处理过程

## 5. 故障预防
– 分析故障原因，采取预防措施
– 优化集群配置，提高集群的稳定性
– 加强监控，及时发现和处理问题

## 1. 主节点故障恢复
– 自动故障转移：Redis集群会自动将从节点提升为新的主节点
– 手动故障转移：通过CLUSTER FAILOVER命令手动执行故障转移

## 2. 从节点故障恢复
– 修复从节点：修复从节点的故障，重启从节点
– 添加新的从节点：如果从节点无法修复，添加新的从节点

## 3. 网络故障恢复
– 检查网络连接：检查节点之间的网络连接
– 修复网络问题：修复网络故障，确保节点之间的网络连接正常
– 等待集群恢复：网络恢复后，集群会自动修复

## 4. 数据恢复
– 持久化恢复：通过RDB或AOF文件恢复数据
– 复制恢复：通过主从复制恢复数据
– 集群恢复：通过集群的自动修复机制恢复数据

## 5. 集群重平衡
– 自动重平衡：集群自动平衡槽位分配
– 手动重平衡：通过redis-cli –cluster rebalance命令手动平衡槽位分配

风哥提示：Redis接口限流是保护系统的重要机制，合理的限流策略可以防止系统过载，确保系统的稳定性和可用性。在实际应用中，需要根据具体业务场景和数据特点，选择合适的限流算法和策略。

Part04-生产案例与实战讲解

4.1 集群监控实战

## 1. 场景描述
– 生产环境中的Redis集群需要实时监控
– 确保Redis集群的稳定运行
– 及时发现和解决问题

## 2. 解决方案
– 部署Redis Exporter、Prometheus和Grafana
– 配置集群监控指标和告警规则
– 建立监控面板和告警通知

## 3. 实战操作
# 部署Redis Exporter（每个节点）
$ wget https://github.com/oliver006/redis_exporter/releases/download/v1.50.0/redis_exporter-v1.50.0.linux-amd64.tar.gz
$ tar -xzf redis_exporter-v1.50.0.linux-amd64.tar.gz
$ mv redis_exporter-v1.50.0.linux-amd64/redis_exporter /usr/local/bin/
$ vi /etc/systemd/system/redis_exporter.service

[Unit]
Description=Redis Exporter
After=network.target

[Service]
Type=simple
User=redis
ExecStart=/usr/local/bin/redis_exporter –redis.addr=redis://192.168.1.100:7000 –redis.password=fgedu@2026
Restart=always

[Install]
WantedBy=multi-user.target

$ systemctl daemon-reload
$ systemctl start redis_exporter
$ systemctl enable redis_exporter

# 部署Prometheus
$ wget https://github.com/prometheus/prometheus/releases/download/v2.47.0/prometheus-2.47.0.linux-amd64.tar.gz
$ tar -xzf prometheus-2.47.0.linux-amd64.tar.gz
$ mv prometheus-2.47.0.linux-amd64 /usr/local/prometheus
$ vi /usr/local/prometheus/prometheus.yml

global:
scrape_interval: 15s
evaluation_interval: 15s

rule_files:
– “redis_cluster_rules.yml”

alerting:
alertmanagers:
– static_configs:
– targets:
– localhost:9093

scrape_configs:
– job_name: “prometheus”
static_configs:
– targets: [“localhost:9090”]

– job_name: “redis_cluster”
static_configs:
– targets: [“192.168.1.100:9121”, “192.168.1.101:9121”, “192.168.1.102:9121”]
labels:
cluster: “redis-cluster”

# 创建Redis集群告警规则
$ vi /usr/local/prometheus/redis_cluster_rules.yml

groups:
– name: redis_cluster_alerts
rules:
– alert: RedisClusterDown
expr: redis_cluster_state != 1
for: 5m
labels:
severity: critical
annotations:
summary: “Redis cluster down”
description: “Redis cluster {{ $labels.cluster }} is down”

– alert: RedisClusterSlotFail
expr: redis_cluster_slots_fail > 0
for: 5m
labels:
severity: critical
annotations:
summary: “Redis cluster slot fail”
description: “Redis cluster {{ $labels.cluster }} has {{ $value }} failed slots”

– alert: RedisClusterNodeDown
expr: redis_up == 0
for: 5m
labels:
severity: critical
annotations:
summary: “Redis node down”
description: “Redis node {{ $labels.instance }} is down”

– alert: RedisMemoryUsageHigh
expr: redis_used_memory / redis_config_maxmemory * 100 > 80
for: 5m
labels:
severity: warning
annotations:
summary: “Redis memory usage high”
description: “Redis node {{ $labels.instance }} memory usage is {{ $value }}%”

– alert: RedisReplicationLag
expr: redis_replication_offset_delay > 10
for: 5m
labels:
severity: warning
annotations:
summary: “Redis replication lag”
description: “Redis node {{ $labels.instance }} replication lag is {{ $value }} seconds”

# 启动Prometheus服务
$ systemctl daemon-reload
$ systemctl start prometheus
$ systemctl enable prometheus

# 部署Grafana
$ wget https://dl.grafana.com/oss/release/grafana-10.0.0.linux-amd64.tar.gz
$ tar -xzf grafana-10.0.0.linux-amd64.tar.gz
$ mv grafana-10.0.0 /usr/local/grafana
$ vi /etc/systemd/system/grafana-server.service

[Unit]
Description=Grafana
After=network.target

[Service]
Type=simple
User=grafana
ExecStart=/usr/local/grafana/bin/grafana-server –config=/usr/local/grafana/conf/defaults.ini –homepath=/usr/local/grafana
Restart=always

[Install]
WantedBy=multi-user.target

$ systemctl daemon-reload
$ systemctl start grafana-server
$ systemctl enable grafana-server

# 配置Grafana数据源和面板
# 访问Grafana Web界面：http://localhost:3000
# 默认用户名和密码：admin/admin
# 添加Prometheus数据源
# 导入Redis集群监控面板（ID：763）

## 1. 场景描述
– 生产环境中的Redis集群出现主节点故障
– 需要及时处理故障，确保集群的稳定运行
– 验证故障处理的有效性

## 2. 解决方案
– 监控系统检测到主节点故障
– 自动故障转移将从节点提升为新的主节点
– 验证集群状态是否正常

## 3. 实战操作
# 查看集群状态
$ /redis/app/bin/redis-cli -h 192.168.1.100 -p 7000 -a fgedu@2026 cluster info

# 输出示例
cluster_state:ok
cluster_slots_assigned:16384
cluster_slots_ok:16384
cluster_slots_pfail:0
cluster_slots_fail:0
cluster_known_nodes:6
cluster_size:3
cluster_current_epoch:6
cluster_my_epoch:1
cluster_stats_messages_ping_sent:1000
cluster_stats_messages_pong_sent:990
cluster_stats_messages_sent:1990
cluster_stats_messages_ping_received:990
cluster_stats_messages_pong_received:1000
cluster_stats_messages_meet_received:5
cluster_stats_messages_received:1995

# 查看集群节点信息
$ /redis/app/bin/redis-cli -h 192.168.1.100 -p 7000 -a fgedu@2026 cluster nodes

# 输出示例
1a2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z:7000@17000 master – 0 1627824000000 1 connected 0-5460
2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1:7001@17001 slave 1a2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z 0 1627824000000 1 connected
3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a:7000@17000 master – 0 1627824000000 2 connected 5461-10922
4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2:7001@17001 slave 3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a 0 1627824000000 2 connected
5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b:7000@17000 master – 0 1627824000000 3 connected 10923-16383
6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b3:7001@17001 slave 5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b 0 1627824000000 3 connected

# 模拟主节点故障
$ systemctl stop redis-7000

# 查看集群状态
$ /redis/app/bin/redis-cli -h 192.168.1.101 -p 7000 -a fgedu@2026 cluster info

# 输出示例
cluster_state:ok
cluster_slots_assigned:16384
cluster_slots_ok:16384
cluster_slots_pfail:0
cluster_slots_fail:0
cluster_known_nodes:6
cluster_size:3
cluster_current_epoch:7
cluster_my_epoch:2
cluster_stats_messages_ping_sent:1050
cluster_stats_messages_pong_sent:1040
cluster_stats_messages_sent:2090
cluster_stats_messages_ping_received:1040
cluster_stats_messages_pong_received:1050
cluster_stats_messages_meet_received:5
cluster_stats_messages_received:2095

# 查看集群节点信息
$ /redis/app/bin/redis-cli -h 192.168.1.101 -p 7000 -a fgedu@2026 cluster nodes

# 输出示例
1a2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z:7000@17000 master,fail – 1627824000000 1627824060000 1 disconnected
2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1:7001@17001 master – 0 1627824065000 7 connected 0-5460
3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a:7000@17000 master – 0 1627824065000 2 connected 5461-10922
4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2:7001@17001 slave 3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a 0 1627824065000 2 connected
5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b:7000@17000 master – 0 1627824065000 3 connected 10923-16383
6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b3:7001@17001 slave 5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b 0 1627824065000 3 connected

# 验证故障转移是否成功
# 从输出可以看到，原来的从节点2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1:7001已经被提升为新的主节点，负责槽位0-5460

# 修复故障节点
$ systemctl start redis-7000

# 查看集群状态
$ /redis/app/bin/redis-cli -h 192.168.1.100 -p 7000 -a fgedu@2026 cluster info

# 输出示例
cluster_state:ok
cluster_slots_assigned:16384
cluster_slots_ok:16384
cluster_slots_pfail:0
cluster_slots_fail:0
cluster_known_nodes:6
cluster_size:3
cluster_current_epoch:7
cluster_my_epoch:1
cluster_stats_messages_ping_sent:1100
cluster_stats_messages_pong_sent:1090
cluster_stats_messages_sent:2190
cluster_stats_messages_ping_received:1090
cluster_stats_messages_pong_received:1100
cluster_stats_messages_meet_received:5
cluster_stats_messages_received:2195

# 查看集群节点信息
$ /redis/app/bin/redis-cli -h 192.168.1.100 -p 7000 -a fgedu@2026 cluster nodes

# 输出示例
1a2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z:7000@17000 slave 2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1 0 1627824120000 7 connected
2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1:7001@17001 master – 0 1627824125000 7 connected 0-5460
3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a:7000@17000 master – 0 1627824125000 2 connected 5461-10922
4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2:7001@17001 slave 3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a 0 1627824125000 2 connected
5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b:7000@17000 master – 0 1627824125000 3 connected 10923-16383
6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b3:7001@17001 slave 5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b 0 1627824125000 3 connected

# 验证集群是否恢复正常
# 从输出可以看到，原来的主节点1a2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z:7000现在成为了从节点，复制新的主节点2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1:7001

## 1. 场景描述
– 生产环境中的Redis集群出现数据不一致问题
– 需要进行数据恢复，确保数据的一致性和完整性
– 验证数据恢复的有效性

## 2. 解决方案
– 停止故障节点
– 从备份恢复数据
– 重启节点并加入集群
– 验证数据是否一致

## 3. 实战操作
# 查看集群状态
$ /redis/app/bin/redis-cli -h 192.168.1.100 -p 7000 -a fgedu@2026 cluster info

# 输出示例
cluster_state:ok
cluster_slots_assigned:16384
cluster_slots_ok:16384
cluster_slots_pfail:0
cluster_slots_fail:0
cluster_known_nodes:6
cluster_size:3
cluster_current_epoch:7
cluster_my_epoch:1
cluster_stats_messages_ping_sent:1150
cluster_stats_messages_pong_sent:1140
cluster_stats_messages_sent:2290
cluster_stats_messages_ping_received:1140
cluster_stats_messages_pong_received:1150
cluster_stats_messages_meet_received:5
cluster_stats_messages_received:2295

# 查看集群节点信息
$ /redis/app/bin/redis-cli -h 192.168.1.100 -p 7000 -a fgedu@2026 cluster nodes

# 输出示例
1a2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z:7000@17000 slave 2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1 0 1627824180000 7 connected
2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1:7001@17001 master – 0 1627824185000 7 connected 0-5460
3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a:7000@17000 master – 0 1627824185000 2 connected 5461-10922
4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2:7001@17001 slave 3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a 0 1627824185000 2 connected
5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b:7000@17000 master – 0 1627824185000 3 connected 10923-16383
6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b3:7001@17001 slave 5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b 0 1627824185000 3 connected

# 停止故障节点
$ systemctl stop redis-7000

# 从备份恢复数据
$ cp /backup/redis/dump.rdb /redis/fgdata/

# 重启节点
$ systemctl start redis-7000

# 查看集群状态
$ /redis/app/bin/redis-cli -h 192.168.1.100 -p 7000 -a fgedu@2026 cluster info

# 输出示例
cluster_state:ok
cluster_slots_assigned:16384
cluster_slots_ok:16384
cluster_slots_pfail:0
cluster_slots_fail:0
cluster_known_nodes:6
cluster_size:3
cluster_current_epoch:7
cluster_my_epoch:1
cluster_stats_messages_ping_sent:1200
cluster_stats_messages_pong_sent:1190
cluster_stats_messages_sent:2390
cluster_stats_messages_ping_received:1190
cluster_stats_messages_pong_received:1200
cluster_stats_messages_meet_received:5
cluster_stats_messages_received:2395

# 查看集群节点信息
$ /redis/app/bin/redis-cli -h 192.168.1.100 -p 7000 -a fgedu@2026 cluster nodes

# 输出示例
1a2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z:7000@17000 slave 2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1 0 1627824240000 7 connected
2b3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1:7001@17001 master – 0 1627824245000 7 connected 0-5460
3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a:7000@17000 master – 0 1627824245000 2 connected 5461-10922
4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2:7001@17001 slave 3c4d5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a 0 1627824245000 2 connected
5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b:7000@17000 master – 0 1627824245000 3 connected 10923-16383
6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b3:7001@17001 slave 5e6f7g8h9i0j1k2l3m4n5o6p7q8r9s0t1u2v3w4x5y6z1a2b 0 1627824245000 3 connected

# 验证数据是否一致
$ /redis/app/bin/redis-cli -h 192.168.1.100 -p 7000 -a fgedu@2026 get user:1001

# 输出示例
“张三”

$ /redis/app/bin/redis-cli -h 192.168.1.101 -p 7001 -a fgedu@2026 get user:1001

# 输出示例
“张三”

# 验证集群是否正常工作
$ /redis/app/bin/redis-cli -h 192.168.1.100 -p 7000 -a fgedu@2026 set test:key value

# 输出示例
OK

$ /redis/app/bin/redis-cli -h 192.168.1.101 -p 7000 -a fgedu@2026 get test:key

# 输出示例
“value”

更多学习教程公众号风哥教程itpux_com

Part05-风哥经验总结与分享

5.1 最佳实践

Redis集群监控与故障处理实战最佳实践：

• 全面监控：覆盖所有集群节点，包括主节点和从节点，学习交流加群风哥微信: itpux-com
• 关键指标：选择关键指标进行监控，如内存使用、CPU使用率、网络流量、集群状态等
• 合理阈值：设置合理的告警阈值，避免误告警和漏告警
• 多级告警：设置不同级别的告警，根据问题的严重程度采取不同的处理措施
• 及时处理：收到告警后及时处理，避免问题扩大
• 自动故障转移：启用自动故障转移，确保集群的高可用性
• 定期备份：定期备份数据，以便在故障发生后恢复数据
• 定期演练：定期进行故障演练，提高故障处理能力
• 持续优化：根据实际情况，持续优化监控和故障处理策略

5.2 常见问题