Redis实用监控工具一览

2019 年 10 月 6 日
筆記

Redis已经成为web应用开发不可或缺的一个组成部分，在项目中的应用越来越广泛，这篇文章就来讲讲那些关于Redis监控的那点事。

redis-benchmark

1.1 简介

第一个就介绍一下，Redis自带的性能检测工具redis-benchmark, 该工具可以模拟 N 个客户端同时发出 Y 个请求。可以使用 redis-benchmark -h 来查看基准参数。

1.2 命令格式：

redis-benchmark [-h ] [-p ] [-c ] [-n <requests]> [-k ]

1.3 参数介绍：

1.4 实例：

1.4.1 同时执行1000个请求来检测性能：

redis-benchmark -n 1000 -q

1.4.2 50个并发请求，10000个请求，检测Redis性能：

redis-benchmark -h localhost -p 6379 -c 50 -n 10000

[root@localhost toutou]# redis-benchmark -h localhost -p 6379 -c 50 -n 10000  ====== PING_INLINE ======  requests completed in 0.11 seconds  parallel clients  bytes payload    keep alive: 1    96.25% <= 1 milliseconds  98.38% <= 2 milliseconds  99.01% <= 3 milliseconds  100.00% <= 4 milliseconds  88495.58 requests per second    ====== PING_BULK ======  requests completed in 0.10 seconds  parallel clients  bytes payload    keep alive: 1    97.74% <= 1 milliseconds  100.00% <= 2 milliseconds  95238.10 requests per second    ====== SET ======  requests completed in 0.11 seconds  parallel clients  bytes payload    keep alive: 1    98.44% <= 1 milliseconds  100.00% <= 1 milliseconds  93457.95 requests per second    ====== GET ======  requests completed in 0.11 seconds  parallel clients  bytes payload    keep alive: 1    98.33% <= 1 milliseconds  99.13% <= 2 milliseconds  100.00% <= 2 milliseconds  93457.95 requests per second    ====== INCR ======  requests completed in 0.10 seconds  parallel clients  bytes payload    keep alive: 1    98.28% <= 1 milliseconds  100.00% <= 1 milliseconds  95238.10 requests per second    ====== LPUSH ======  requests completed in 0.10 seconds  parallel clients  bytes payload    keep alive: 1    98.70% <= 1 milliseconds  100.00% <= 1 milliseconds  97087.38 requests per second    ====== RPUSH ======  requests completed in 0.10 seconds  parallel clients  bytes payload    keep alive: 1    98.66% <= 1 milliseconds  100.00% <= 1 milliseconds  95238.10 requests per second    ====== LPOP ======  requests completed in 0.15 seconds  parallel clients  bytes payload    keep alive: 1    93.78% <= 1 milliseconds  96.51% <= 2 milliseconds  97.35% <= 3 milliseconds  98.41% <= 4 milliseconds  99.02% <= 5 milliseconds  99.23% <= 6 milliseconds  99.46% <= 7 milliseconds  99.96% <= 8 milliseconds  99.97% <= 9 milliseconds  100.00% <= 9 milliseconds  67567.57 requests per second    ====== RPOP ======  requests completed in 0.31 seconds  parallel clients  bytes payload    keep alive: 1    65.78% <= 1 milliseconds  84.10% <= 2 milliseconds  90.96% <= 3 milliseconds  94.19% <= 4 milliseconds  95.72% <= 5 milliseconds  97.05% <= 6 milliseconds  98.33% <= 7 milliseconds  98.80% <= 8 milliseconds  99.40% <= 9 milliseconds  99.72% <= 10 milliseconds  100.00% <= 14 milliseconds  31746.03 requests per second    ====== SADD ======  requests completed in 0.19 seconds  parallel clients  bytes payload    keep alive: 1    93.00% <= 1 milliseconds  96.88% <= 2 milliseconds  98.33% <= 3 milliseconds  98.92% <= 6 milliseconds  98.94% <= 7 milliseconds  98.95% <= 9 milliseconds  99.04% <= 10 milliseconds  99.48% <= 12 milliseconds  99.61% <= 14 milliseconds  99.62% <= 15 milliseconds  99.99% <= 16 milliseconds  100.00% <= 16 milliseconds  52083.33 requests per second    ====== HSET ======  requests completed in 0.11 seconds  parallel clients  bytes payload    keep alive: 1    95.90% <= 1 milliseconds  99.95% <= 2 milliseconds  100.00% <= 2 milliseconds  90909.09 requests per second    ====== SPOP ======  requests completed in 0.11 seconds  parallel clients  bytes payload    keep alive: 1    97.04% <= 1 milliseconds  99.75% <= 2 milliseconds  99.78% <= 3 milliseconds  100.00% <= 3 milliseconds  90909.09 requests per second    ====== LPUSH (needed to benchmark LRANGE) ======  requests completed in 0.11 seconds  parallel clients  bytes payload    keep alive: 1    96.48% <= 1 milliseconds  99.46% <= 2 milliseconds  99.95% <= 3 milliseconds  100.00% <= 3 milliseconds  87719.30 requests per second    ====== LRANGE_100 (first 100 elements) ======  requests completed in 0.33 seconds  parallel clients  bytes payload    keep alive: 1    32.63% <= 1 milliseconds  93.24% <= 2 milliseconds  99.83% <= 3 milliseconds  100.00% <= 3 milliseconds  30303.03 requests per second    ====== LRANGE_300 (first 300 elements) ======  requests completed in 0.85 seconds  parallel clients  bytes payload    keep alive: 1    2.65% <= 1 milliseconds  23.01% <= 2 milliseconds  53.33% <= 3 milliseconds  77.25% <= 4 milliseconds  91.47% <= 5 milliseconds  98.58% <= 6 milliseconds  99.99% <= 7 milliseconds  100.00% <= 7 milliseconds  11764.71 requests per second    ====== LRANGE_500 (first 450 elements) ======  requests completed in 1.22 seconds  parallel clients  bytes payload    keep alive: 1    1.01% <= 1 milliseconds  9.09% <= 2 milliseconds  28.25% <= 3 milliseconds  50.31% <= 4 milliseconds  68.06% <= 5 milliseconds  81.18% <= 6 milliseconds  90.78% <= 7 milliseconds  96.96% <= 8 milliseconds  99.43% <= 9 milliseconds  100.00% <= 9 milliseconds  8196.72 requests per second    ====== LRANGE_600 (first 600 elements) ======  requests completed in 1.57 seconds  parallel clients  bytes payload    keep alive: 1    0.61% <= 1 milliseconds  4.90% <= 2 milliseconds  14.77% <= 3 milliseconds  28.67% <= 4 milliseconds  44.56% <= 5 milliseconds  59.45% <= 6 milliseconds  72.38% <= 7 milliseconds  82.29% <= 8 milliseconds  90.01% <= 9 milliseconds  95.42% <= 10 milliseconds  98.34% <= 11 milliseconds  99.78% <= 12 milliseconds  100.00% <= 12 milliseconds  6357.28 requests per second    ====== MSET (10 keys) ======  requests completed in 0.19 seconds  parallel clients  bytes payload    keep alive: 1    68.40% <= 1 milliseconds  98.61% <= 2 milliseconds  100.00% <= 3 milliseconds  53763.44 requests per second      [root@localhost toutou]#

redis-cli

2.1 简介

查看redis的连接及读写操作

2.2 命令格式

redis-cli -h xx -p yy monitor

2.3 实例：

2.4 redis-cli info：

Redis 监控最直接的方法就是使用系统提供的 info 命令，只需要执行下面一条命令，就能获得 Redis 系统的状态报告。

# Server  redis_version:5.0.2                    # Redis 的版本  redis_git_sha1:00000000  redis_git_dirty:0  redis_build_id:bf5d1747be5380f  redis_mode:standalone  os:Linux 2.6.32-220.7.1.el6.x86_64 x86_64  arch_bits:64  multiplexing_api:epoll  gcc_version:4.4.7                       #gcc版本  process_id:49324                        # 当前 Redis 服务器进程id  run_id:bbd7b17efcf108fdde285d8987e50392f6a38f48  tcp_port:6379  uptime_in_seconds:1739082               # 运行时间(秒)  uptime_in_days:20                       # 运行时间(天)  hz:10  lru_clock:1734729  config_file:/home/s/apps/RedisMulti_video_so/conf/zzz.conf    # Clients  connected_clients:1                     #连接的客户端数量  client_longest_output_list:0  client_biggest_input_buf:0  blocked_clients:0    # Memory  used_memory:821848                       #Redis分配的内存总量  used_memory_human:802.59K  used_memory_rss:85532672                 #Redis分配的内存总量(包括内存碎片)  used_memory_peak:178987632  used_memory_peak_human:170.70M           #Redis所用内存的高峰值  used_memory_lua:33792  mem_fragmentation_ratio:104.07           #内存碎片比率  mem_allocator:tcmalloc-2.0    # Persistence  loading:0  rdb_changes_since_last_save:0            #上次保存数据库之后，执行命令的次数  rdb_bgsave_in_progress:0                 #后台进行中的 save 操作的数量  rdb_last_save_time:1410848505            #最后一次成功保存的时间点，以 UNIX 时间戳格式显示  rdb_last_bgsave_status:ok  rdb_last_bgsave_time_sec:0  rdb_current_bgsave_time_sec:-1  aof_enabled:0                            #redis是否开启了aof  aof_rewrite_in_progress:0  aof_rewrite_scheduled:0  aof_last_rewrite_time_sec:-1  aof_current_rewrite_time_sec:-1  aof_last_bgrewrite_status:ok  aof_last_write_status:ok    # Stats  total_connections_received:5705          #运行以来连接过的客户端的总数量  total_commands_processed:204013          # 运行以来执行过的命令的总数量  instantaneous_ops_per_sec:0  rejected_connections:0  sync_full:0  sync_partial_ok:0  sync_partial_err:0  expired_keys:34401                       #运行以来过期的 key 的数量  evicted_keys:0                           #运行以来删除过的key的数量  keyspace_hits:2129                       #命中key 的次数  keyspace_misses:3148                     #没命中key 的次数  pubsub_channels:0                        #当前使用中的频道数量  pubsub_patterns:0                        #当前使用中的模式数量  latest_fork_usec:4391    # Replication  role:master                              #当前实例的角色master还是slave  connected_slaves:0  master_repl_offset:0  repl_backlog_active:0  repl_backlog_size:1048576  repl_backlog_first_byte_offset:0  repl_backlog_histlen:0    # CPU  used_cpu_sys:1551.61  used_cpu_user:1083.37  used_cpu_sys_children:2.52  used_cpu_user_children:16.79    # Keyspace  db0:keys=3,expires=0,avg_ttl=0             #各个数据库的 key 的数量，以及带有生存期的 key 的数量

redis-cli info

结果会返回 Server、Clients、Memory、Persistence、Stats、Replication、CPU、Keyspace 8个部分。从info大返回结果中提取相关信息，就可以达到有效监控的目的。

showlog

3.1 简介

redis的slowlog是redis用于记录记录慢查询执行时间的日志系统。由于slowlog只保存在内存中，因此slowlog的效率很高，完全不用担心会影响到redis的性能。Slowlog是Redis从2.2.12版本引入的一条命令。

3.2 命令格式

在redis-cli中有关于slowlog的设置：

CONFIG SET slowlog-log-slower-than 6000    CONFIG SET slowlog-max-len 25

3.3 实例：

上面介绍的都是关于Redis自带的命令化性能查询工具。下面介绍介绍一些第三方的Redis可视化性能监控工具。

RedisLive

4.1 简介

RedisLive是由Python编写的开源的图形化监控工具。核心服务部分只包括一个web服务和基于Redis自带的Info命令以及monitor命令的监控服务。支持多实例监控，监控信息可以使用redis存储和sqlite持久化存储。

4.2 安装

4.2.1 安装依赖环境

RedisLive是由Python2.X编写的，所以最好使用Python2.7来运行RedisLive，在CentOS 7中预安装了Python2.7，但没有安装Python的包管理器pip。

yum install epel-release  sudo yum install python-pip  pip install --upgrade pip  pip install tornado  pip install redis  pip install python-dateutil

4.2.2 安装RedisLive

git clone https://github.com/nkrode/RedisLive.git

4.2.3 修改配置文件redis-live.conf

cd RedisLive/src

//按照以下方式修改配置文件  {      "RedisServers":      [          #在此处添加需要监控的redis实例          {                "server": "127.0.0.1",                #redis监听地址，此处为本机                "port" : 6379,                        #redis端口号，可以通过lsof -i | grep redis-ser查看 redis-server端口号                "password" : "some-password"          #redis认证密码，如果没有可以删除该行，注意json格式          }      ],        "DataStoreType" : "redis",        #监控数据存储方案的配置，可选择redis或sqllite      #用来存储监控数据的 Redis 实例      "RedisStatsServer":      {          "server" : "127.0.0.1",          "port" : 6379,          "password" : "some-password"      },      #监控数据持久化数据存储配置      "SqliteStatsStore" :      {          "path":  "db/redislive.sqlite"    #redis数据文件      }  }

redis-live.conf的配置可以参考redis-live.conf.example

4.3 启动

启动监控服务，每60秒监控一次

./redis-monitor.py --duration=60

再次开启一个终端，进入/root/RedisLive/src目录，启动web服务

./redis-live.py

4.4 效果图

redis-faina

5.1 简介

5.1.1 背景

redis-faina是由Instagram开发并开源的一个 Redis 查询分析小工具。Instagram团队曾经使用 PGFouine 来作为其PostgreSQL的查询分析工具，他们觉得Redis也需要一个类似的工具来进行query分析工作，于是开发了 redis-faina。

5.1.2 概念

redis-faina 是通过Redis的 MONITOR命令来实现的，通过对在Redis上执行的query进行监控，统计出一段时间的query特性。

5.2 安装

git clone https://github.com/facebookarchive/redis-faina.git

5.3 命令介绍

[root@localhost toutou]# cd redis-faina/  [root@localhost redis-faina]# ls  heroku-redistogo-faina.sh  LICENSE  README.md  redis-faina.py  [root@localhost redis-faina]# ./redis-faina.py -h  usage: redis-faina.py [-h] [--prefix-delimiter PREFIX_DELIMITER]                        [--redis-version REDIS_VERSION]                        [input]    positional arguments:    input                 File to parse; will read from stdin otherwise    optional arguments:    -h, --help            show this help message and exit    --prefix-delimiter PREFIX_DELIMITER                          String to split on for delimiting prefix and rest of                          key    --redis-version REDIS_VERSION                          Version of the redis server being monitored  [root@localhost redis-faina]#

其中 –prefix-delimiter 主要用于统计前缀的key的数据。

可以通过 redis MONITOR 命令以及管道进行分析，例如：

redis-cli -p 6379 MONITOR | head -n | ./redis-faina.py [options]

或者

redis-cli -p 6379 MONITOR > outfile.txt    ./redis-faina.py ./outfile.txt

Overall Stats  ========================================  Lines Processed     117773  Commands/Sec        11483.44    Top Prefixes  ========================================  friendlist          69945  followedbycounter   25419  followingcounter    10139  recentcomments      3276  queued              7    Top Keys  ========================================  friendlist:zzz:1:2     534  followingcount:zzz     227  friendlist:zxz:1:2     167  friendlist:xzz:1:2     165  friendlist:yzz:1:2     160  friendlist:gzz:1:2     160  friendlist:zdz:1:2     160  friendlist:zpz:1:2     156    Top Commands  ========================================  SISMEMBER   59545  HGET        27681  HINCRBY     9413  SMEMBERS    9254  MULTI       3520  EXEC        3520  LPUSH       1620  EXPIRE      1598    Command Time (microsecs)  ========================================  Median      78.25  75%         105.0  90%         187.25  99%         411.0    Heaviest Commands (microsecs)  ========================================  SISMEMBER   5331651.0  HGET        2618868.0  HINCRBY     961192.5  SMEMBERS    856817.5  MULTI       311339.5  SADD        54900.75  SREM        40771.25  EXEC        28678.5    Slowest Calls  ========================================  3490.75     "SMEMBERS" "friendlist:zzz:1:2"  2362.0      "SMEMBERS" "friendlist:xzz:1:3"  2061.0      "SMEMBERS" "friendlist:zpz:1:2"  1961.0      "SMEMBERS" "friendlist:yzz:1:2"  1947.5      "SMEMBERS" "friendlist:zpz:1:2"  1459.0      "SISMEMBER" "friendlist:hzz:1:2" "zzz"  1416.25     "SMEMBERS" "friendlist:zhz:1:2"  1389.75     "SISMEMBER" "friendlist:zzx:1:2" "zzz"

总结

关于Redis的监控工具还有很多，这里就不一一列举了，下面给出其它几款优秀的Redis监控工具链接，感兴趣的可以看看。

其他监控工具：

https://github.com/junegunn/redis-stat https://github.com/steelThread/redmon https://github.com/oliver006/redis_exporter

作者：请叫我头头哥来源：https://www.cnblogs.com/toutou/p/redis_monitor.html