## 1. Redis内置监控命令
– INFO：查看Redis的详细信息
– 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
– 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. 告警级别
– 紧急（Critical）：需要立即处理的问题，如Redis服务不可用
– 严重（Major）：需要尽快处理的问题，如内存使用过高
– 警告（Warning）：需要关注的问题，如连接数过多
– 信息（Info）：需要了解的信息，如配置变更

## 2. 告警阈值
– 内存使用：超过最大内存的80%
– CPU使用率：超过80%
– 连接数：超过最大连接数的80%
– 命令执行时间：超过100ms
– 复制延迟：超过10s

## 3. 告警方式
– 邮件：发送邮件通知
– 短信：发送短信通知
– 微信：发送微信通知
– 电话：拨打语音电话通知
– 第三方平台：如PagerDuty、OpsGenie等

## 4. 告警处理流程
– 告警触发：监控系统检测到指标达到阈值
– 告警通知：通过设定的方式通知相关人员
– 问题处理：相关人员收到通知后处理问题
– 告警恢复：问题解决后，告警自动恢复
– 告警记录：记录告警历史，用于分析和优化

学习交流加群风哥QQ113257174

Part03-生产环境项目实施方案

3.1 Redis Exporter配置

## 1. 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

## 2. 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/

## 3. 创建Redis Exporter服务
$ 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://192.168.1.100:6379 –redis.password=fgedu@2026
Restart=always

[Install]
WantedBy=multi-user.target

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

## 5. 验证Redis Exporter
$ curl http://localhost:9121/metrics

# 输出示例
# HELP redis_exporter_build_info A metric with a constant ‘1’ value labeled by version, revision, branch, and goversion from which redis_exporter was built.
# TYPE redis_exporter_build_info gauge
redis_exporter_build_info{branch=”master”,goversion=”go1.20.5″,revision=”abcdef123456″,version=”1.50.0″} 1
# HELP redis_up 1 if Redis is up, 0 if down
# TYPE redis_up gauge
redis_up 1
# HELP redis_uptime_in_seconds Redis server uptime in seconds
# TYPE redis_uptime_in_seconds gauge
redis_uptime_in_seconds 3600
# HELP redis_connected_clients Number of client connections (excluding connections from replicas)
# TYPE redis_connected_clients gauge
redis_connected_clients 10
# HELP redis_used_memory Redis memory usage in bytes
# TYPE redis_used_memory gauge
redis_used_memory 104857600
# HELP redis_used_memory_rss Redis memory usage in bytes (RSS)
# TYPE redis_used_memory_rss gauge
redis_used_memory_rss 157286400
# HELP redis_used_memory_peak Redis memory usage peak in bytes
# TYPE redis_used_memory_peak gauge
redis_used_memory_peak 209715200
# HELP redis_mem_fragmentation_ratio Ratio between used_memory_rss and used_memory
# TYPE redis_mem_fragmentation_ratio gauge
redis_mem_fragmentation_ratio 1.5
# HELP redis_total_connections_received Total number of connections received
# TYPE redis_total_connections_received counter
redis_total_connections_received 1000
# HELP redis_total_commands_processed Total number of commands processed
# TYPE redis_total_commands_processed counter
redis_total_commands_processed 10000
# HELP redis_instantaneous_ops_per_sec Number of commands processed per second
# TYPE redis_instantaneous_ops_per_sec gauge
redis_instantaneous_ops_per_sec 100
# HELP redis_keyspace_hits Number of keys that were looked up and found present
# TYPE redis_keyspace_hits counter
redis_keyspace_hits 5000
# HELP redis_keyspace_misses Number of keys that were looked up and not found
# TYPE redis_keyspace_misses counter
redis_keyspace_misses 1000

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

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

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

global:
scrape_interval: 15s
evaluation_interval: 15s

rule_files:
# – “first_rules.yml”
# – “second_rules.yml”

alerting:
alertmanagers:
– static_configs:
– targets:
# – alertmanager:9093

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

– job_name: “redis”
static_configs:
– targets: [“192.168.1.100:9121”]
labels:
instance: “redis-1″

## 4. 创建Prometheus服务
$ vi /etc/systemd/system/prometheus.service

[Unit]
Description=Prometheus
After=network.target

[Service]
Type=simple
User=prometheus
ExecStart=/usr/local/prometheus/prometheus –config.file=/usr/local/prometheus/prometheus.yml –storage.tsdb.path=/usr/local/prometheus/data
Restart=always

[Install]
WantedBy=multi-user.target

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

## 6. 验证Prometheus
$ curl http://localhost:9090/metrics

# 输出示例
# HELP prometheus_build_info A metric with a constant ‘1’ value labeled by version, revision, branch, and goversion from which Prometheus was built.
# TYPE prometheus_build_info gauge
prometheus_build_info{branch=”HEAD”,goversion=”go1.20.5″,revision=”abcdef123456″,version=”2.47.0″} 1
# HELP prometheus_tsdb_compaction_chunk_range Final time range of chunks compacted in the TSDB.
# TYPE prometheus_tsdb_compaction_chunk_range gauge
prometheus_tsdb_compaction_chunk_range{range=”10m”} 0
# HELP prometheus_tsdb_head_chunk_encoding_stats Number of chunks in each encoding in the head.
# TYPE prometheus_tsdb_head_chunk_encoding_stats gauge
prometheus_tsdb_head_chunk_encoding_stats{encoding=”delta”} 0
prometheus_tsdb_head_chunk_encoding_stats{encoding=”double_delta”} 0
prometheus_tsdb_head_chunk_encoding_stats{encoding=”histogram”} 0
prometheus_tsdb_head_chunk_encoding_stats{encoding=”float”} 0
prometheus_tsdb_head_chunk_encoding_stats{encoding=”gorilla”} 0
# HELP prometheus_tsdb_head_chunks Number of chunks in the head.
# TYPE prometheus_tsdb_head_chunks gauge
prometheus_tsdb_head_chunks 0
# HELP prometheus_tsdb_head_max_time Maximum time stored in the head.
# TYPE prometheus_tsdb_head_max_time gauge
prometheus_tsdb_head_max_time 0
# HELP prometheus_tsdb_head_min_time Minimum time stored in the head.
# TYPE prometheus_tsdb_head_min_time gauge
prometheus_tsdb_head_min_time 0
# HELP prometheus_tsdb_head_samples_appended_total Total number of samples appended to the head.
# TYPE prometheus_tsdb_head_samples_appended_total counter
prometheus_tsdb_head_samples_appended_total 0
# HELP prometheus_tsdb_head_series Total number of series in the head.
# TYPE prometheus_tsdb_head_series gauge
prometheus_tsdb_head_series 0

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

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

## 3. 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

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

## 5. 配置Grafana数据源
# 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：
# 1. 点击”Configuration” -> “Data sources”
# 2. 点击”Add data source”
# 3. 选择”Prometheus”
# 4. 设置URL为”http://localhost:9090″
# 5. 点击”Save & Test”

## 6. 导入Redis监控面板
# 1. 点击”Dashboards” -> “Import”
# 2. 输入面板ID：763
# 3. 选择Prometheus数据源
# 4. 点击”Import”

## 7. 验证Grafana
# 访问Grafana Web界面：http://localhost:3000
# 查看Redis监控面板

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 Redis监控实战

## 1. 场景描述
– 生产环境中的Redis实例需要实时监控
– 确保Redis服务的稳定运行
– 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
$ 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://192.168.1.100:6379 –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_rules.yml”

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

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

– job_name: “redis”
static_configs:
– targets: [“192.168.1.100:9121”]
labels:
instance: “redis-1”

# 创建Redis告警规则
$ vi /usr/local/prometheus/redis_rules.yml

groups:
– name: redis_alerts
rules:
– alert: RedisDown
expr: redis_up == 0
for: 5m
labels:
severity: critical
annotations:
summary: “Redis down”
description: “Redis instance {{ $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 instance {{ $labels.instance }} memory usage is {{ $value }}%”

– alert: RedisCPUUsageHigh
expr: (redis_cpu_sys_seconds_total + redis_cpu_user_seconds_total) / redis_uptime_in_seconds * 100 > 80
for: 5m
labels:
severity: warning
annotations:
summary: “Redis CPU usage high”
description: “Redis instance {{ $labels.instance }} CPU usage is {{ $value }}%”

– alert: RedisConnectionsHigh
expr: redis_connected_clients > 1000
for: 5m
labels:
severity: warning
annotations:
summary: “Redis connections high”
description: “Redis instance {{ $labels.instance }} has {{ $value }} connections”

– alert: RedisReplicationLag
expr: redis_replication_offset_delay > 10
for: 5m
labels:
severity: warning
annotations:
summary: “Redis replication lag”
description: “Redis instance {{ $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监控面板（ID：763）

## 1. 场景描述
– 生产环境中的Redis实例需要设置告警
– 当Redis出现问题时，及时通知相关人员
– 确保问题能够得到及时处理

## 2. 解决方案
– 部署Alertmanager
– 配置告警规则和通知方式
– 测试告警通知

## 3. 实战操作
# 部署Alertmanager
$ wget https://github.com/prometheus/alertmanager/releases/download/v0.25.0/alertmanager-0.25.0.linux-amd64.tar.gz
$ tar -xzf alertmanager-0.25.0.linux-amd64.tar.gz
$ mv alertmanager-0.25.0.linux-amd64 /usr/local/alertmanager
$ vi /usr/local/alertmanager/alertmanager.yml

global:
resolve_timeout: 5m
smtp_smarthost: ‘smtp.example.com:587’
smtp_from: ‘alertmanager@example.com’
smtp_auth_username: ‘alertmanager’
smtp_auth_password: ‘password’

route:
group_by: [‘alertname’]
group_wait: 30s
group_interval: 5m
repeat_interval: 1h
receiver: ’email’

receivers:
– name: ’email’
email_configs:
– to: ‘admin@example.com’
send_resolved: true

inhibit_rules:
– source_match:
severity: ‘critical’
target_match:
severity: ‘warning’
equal: [‘alertname’, ‘instance’]

# 创建Alertmanager服务
$ vi /etc/systemd/system/alertmanager.service

[Unit]
Description=Alertmanager
After=network.target

[Service]
Type=simple
User=prometheus
ExecStart=/usr/local/alertmanager/alertmanager –config.file=/usr/local/alertmanager/alertmanager.yml
Restart=always

[Install]
WantedBy=multi-user.target

# 启动Alertmanager服务
$ systemctl daemon-reload
$ systemctl start alertmanager
$ systemctl enable alertmanager

# 配置Prometheus告警
$ vi /usr/local/prometheus/prometheus.yml

global:
scrape_interval: 15s
evaluation_interval: 15s

rule_files:
– “redis_rules.yml”

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

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

– job_name: “redis”
static_configs:
– targets: [“192.168.1.100:9121”]
labels:
instance: “redis-1”

# 重启Prometheus服务
$ systemctl restart prometheus

# 测试告警
# 模拟Redis不可用
$ systemctl stop redis

# 查看告警状态
$ curl http://localhost:9090/alerts

# 输出示例
{
“data”: {
“alerts”: [
{
“status”: “firing”,
“labels”: {
“alertname”: “RedisDown”,
“instance”: “redis-1”,
“job”: “redis”,
“severity”: “critical”
},
“annotations”: {
“description”: “Redis instance redis-1 is down”,
“summary”: “Redis down”
},
“startsAt”: “2024-08-01T12:00:00Z”,
“endsAt”: “0001-01-01T00:00:00Z”,
“generatorURL”: “http://localhost:9090/graph?g0.expr=redis_up%20%3D%3D%200&g0.tab=1”
}
]
},
“status”: “success”
}

# 恢复Redis服务
$ systemctl start redis

# 查看告警状态
$ curl http://localhost:9090/alerts

# 输出示例
{
“data”: {
“alerts”: [
{
“status”: “resolved”,
“labels”: {
“alertname”: “RedisDown”,
“instance”: “redis-1”,
“job”: “redis”,
“severity”: “critical”
},
“annotations”: {
“description”: “Redis instance redis-1 is down”,
“summary”: “Redis down”
},
“startsAt”: “2024-08-01T12:00:00Z”,
“endsAt”: “2024-08-01T12:05:00Z”,
“generatorURL”: “http://localhost:9090/graph?g0.expr=redis_up%20%3D%3D%200&g0.tab=1”
}
]
},
“status”: “success”
}

## 1. 场景描述
– 生产环境中的Redis实例需要可视化监控
– 方便查看Redis的运行状态和性能指标
– 及时发现和解决问题

## 2. 解决方案
– 部署Grafana
– 导入Redis监控面板
– 自定义监控面板

## 3. 实战操作
# 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
# 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：
# 1. 点击”Configuration” -> “Data sources”
# 2. 点击”Add data source”
# 3. 选择”Prometheus”
# 4. 设置URL为”http://localhost:9090″
# 5. 点击”Save & Test”

# 导入Redis监控面板
# 1. 点击”Dashboards” -> “Import”
# 2. 输入面板ID：763
# 3. 选择Prometheus数据源
# 4. 点击”Import”

# 自定义监控面板
# 1. 点击”Dashboards” -> “New dashboard”
# 2. 点击”Add a new panel”
# 3. 设置查询语句，如：redis_used_memory{instance=”redis-1″}
# 4. 设置面板标题和描述
# 5. 点击”Apply”

# 查看监控面板
# 访问Grafana Web界面：http://localhost:3000
# 点击”Dashboards” -> “Manage”
# 选择Redis监控面板

# 监控面板示例
# 面板1：内存使用情况
# 面板2：CPU使用率
# 面板3：连接数
# 面板4：命令执行情况
# 面板5：键空间使用情况
# 面板6：复制状态
# 面板7：持久化状态
# 面板8：集群状态

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监控与告警实战最佳实践：

• 全面监控：覆盖所有Redis实例，包括主从节点、集群节点等，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
• 及时通知：确保告警能够及时通知到相关人员
• 可视化监控：使用Grafana等工具创建可视化监控面板，方便查看Redis的运行状态
• 定期分析：定期分析监控数据，优化Redis的配置和性能
• 持续优化：根据实际情况，持续优化监控和告警策略

5.2 常见问题