背景：
Open-Falcon 是小米运维部开源的一款互联网企业级监控系统解决方案，具体的安装和使用说明请见官网：http://open-falcon.org/，是一款比较全的监控。而且提供各种API，只需要把数据按照规定给出就能出图，以及报警、集群支持等等。
监控：
1) MySQL 收集信息脚本(mysql_monitor.py)
#!/bin/env python
# -*- encoding: utf-8 -*-from __future__ import division
import MySQLdb
import datetime
import time
import os
import sys
import fileinput
import requests
import json
import reclass MySQLMonitorInfo():def __init__(self,host,port,user,password):self.host = hostself.port = portself.user = userself.password = passworddef stat_info(self):try:m = MySQLdb.connect(host=self.host,user=self.user,passwd=self.password,port=self.port,charset='utf8')query = "SHOW GLOBAL STATUS"cursor = m.cursor()cursor.execute(query)Str_string = cursor.fetchall()Status_dict = {}for Str_key,Str_value in Str_string:Status_dict[Str_key] = Str_valuecursor.close()m.close()return Status_dictexcept Exception, e:print (datetime.datetime.now()).strftime("%Y-%m-%d %H:%M:%S")print eStatus_dict = {}return Status_dict def engine_info(self):try:m = MySQLdb.connect(host=self.host,user=self.user,passwd=self.password,port=self.port,charset='utf8')_engine_regex = re.compile(ur'(History list length) ([0-9]+\.?[0-9]*)\n')query = "SHOW ENGINE INNODB STATUS"cursor = m.cursor()cursor.execute(query)Str_string = cursor.fetchone()a,b,c = Str_stringcursor.close()m.close()return dict(_engine_regex.findall(c))except Exception, e:print (datetime.datetime.now()).strftime("%Y-%m-%d %H:%M:%S")print ereturn dict(History_list_length=0)if __name__ == '__main__':open_falcon_api = 'http://192.168.200.86:1988/v1/push'db_list= []for line in fileinput.input():db_list.append(line.strip())for db_info in db_list:
# host,port,user,password,endpoint,metric = db_info.split(',')host,port,user,password,endpoint = db_info.split(',')timestamp = int(time.time())step = 60
# tags = "port=%s" %porttags = ""conn = MySQLMonitorInfo(host,int(port),user,password)stat_info = conn.stat_info()engine_info = conn.engine_info()mysql_stat_list = []monitor_keys = [('Com_select','COUNTER'),('Qcache_hits','COUNTER'),('Com_insert','COUNTER'),('Com_update','COUNTER'),('Com_delete','COUNTER'),('Com_replace','COUNTER'),('MySQL_QPS','COUNTER'),('MySQL_TPS','COUNTER'),('ReadWrite_ratio','GAUGE'),('Innodb_buffer_pool_read_requests','COUNTER'),('Innodb_buffer_pool_reads','COUNTER'),('Innodb_buffer_read_hit_ratio','GAUGE'),('Innodb_buffer_pool_pages_flushed','COUNTER'),('Innodb_buffer_pool_pages_free','GAUGE'),('Innodb_buffer_pool_pages_dirty','GAUGE'),('Innodb_buffer_pool_pages_data','GAUGE'),('Bytes_received','COUNTER'),('Bytes_sent','COUNTER'),('Innodb_rows_deleted','COUNTER'),('Innodb_rows_inserted','COUNTER'),('Innodb_rows_read','COUNTER'),('Innodb_rows_updated','COUNTER'),('Innodb_os_log_fsyncs','COUNTER'),('Innodb_os_log_written','COUNTER'),('Created_tmp_disk_tables','COUNTER'),('Created_tmp_tables','COUNTER'),('Connections','COUNTER'),('Innodb_log_waits','COUNTER'),('Slow_queries','COUNTER'),('Binlog_cache_disk_use','COUNTER')]for _key,falcon_type in monitor_keys:if _key == 'MySQL_QPS':_value = int(stat_info.get('Com_select',0)) + int(stat_info.get('Qcache_hits',0))elif _key == 'MySQL_TPS':_value = int(stat_info.get('Com_insert',0)) + int(stat_info.get('Com_update',0)) + int(stat_info.get('Com_delete',0)) + int(stat_info.get('Com_replace',0))elif _key == 'Innodb_buffer_read_hit_ratio':try:_value = round((int(stat_info.get('Innodb_buffer_pool_read_requests',0)) - int(stat_info.get('Innodb_buffer_pool_reads',0)))/int(stat_info.get('Innodb_buffer_pool_read_requests',0)) * 100,3)except ZeroDivisionError:_value = 0elif _key == 'ReadWrite_ratio':try:_value = round((int(stat_info.get('Com_select',0)) + int(stat_info.get('Qcache_hits',0)))/(int(stat_info.get('Com_insert',0)) + int(stat_info.get('Com_update',0)) + int(stat_info.get('Com_delete',0)) + int(stat_info.get('Com_replace',0))),2)except ZeroDivisionError:_value = 0 else:_value = int(stat_info.get(_key,0))falcon_format = {'Metric': '%s' % (_key),'Endpoint': endpoint,'Timestamp': timestamp,'Step': step,'Value': _value,'CounterType': falcon_type,'TAGS': tags}mysql_stat_list.append(falcon_format)#_key : History list lengthfor _key,_value in engine_info.items():_key = "Undo_Log_Length"falcon_format = {'Metric': '%s' % (_key),'Endpoint': endpoint,'Timestamp': timestamp,'Step': step,'Value': int(_value),'CounterType': "GAUGE",'TAGS': tags}mysql_stat_list.append(falcon_format)print json.dumps(mysql_stat_list,sort_keys=True,indent=4)requests.post(open_falcon_api, data=json.dumps(mysql_stat_list)) 指标说明：收集指标里的COUNTER表示每秒执行次数，GAUGE表示直接输出值。
| 指标 | 类型 | 说明 |
| Undo_Log_Length | GAUGE | 未清除的Undo事务数 |
| Com_select | COUNTER | select/秒=QPS |
| Com_insert | COUNTER | insert/秒 |
| Com_update | COUNTER | update/秒 |
| Com_delete | COUNTER | delete/秒 |
| Com_replace | COUNTER | replace/秒 |
| MySQL_QPS | COUNTER | QPS |
| MySQL_TPS | COUNTER | TPS |
| ReadWrite_ratio | GAUGE | 读写比例 |
| Innodb_buffer_pool_read_requests | COUNTER | innodb buffer pool 读次数/秒 |
| Innodb_buffer_pool_reads | COUNTER | Disk 读次数/秒 |
| Innodb_buffer_read_hit_ratio | GAUGE | innodb buffer pool 命中率 |
| Innodb_buffer_pool_pages_flushed | COUNTER | innodb buffer pool 刷写到磁盘的页数/秒 |
| Innodb_buffer_pool_pages_free | GAUGE | innodb buffer pool 空闲页的数量 |
| Innodb_buffer_pool_pages_dirty | GAUGE | innodb buffer pool 脏页的数量 |
| Innodb_buffer_pool_pages_data | GAUGE | innodb buffer pool 数据页的数量 |
| Bytes_received | COUNTER | 接收字节数/秒 |
| Bytes_sent | COUNTER | 发送字节数/秒 |
| Innodb_rows_deleted | COUNTER | innodb表删除的行数/秒 |
| Innodb_rows_inserted | COUNTER | innodb表插入的行数/秒 |
| Innodb_rows_read | COUNTER | innodb表读取的行数/秒 |
| Innodb_rows_updated | COUNTER | innodb表更新的行数/秒 |
| Innodb_os_log_fsyncs | COUNTER | Redo Log fsync次数/秒 |
| Innodb_os_log_written | COUNTER | Redo Log 写入的字节数/秒 |
| Created_tmp_disk_tables | COUNTER | 创建磁盘临时表的数量/秒 |
| Created_tmp_tables | COUNTER | 创建内存临时表的数量/秒 |
| Connections | COUNTER | 连接数/秒 |
| Innodb_log_waits | COUNTER | innodb log buffer不足等待的数量/秒 |
| Slow_queries | COUNTER | 慢查询数/秒 |
| Binlog_cache_disk_use | COUNTER | Binlog Cache不足的数量/秒 |
使用说明：读取配置到都数据库列表执行，配置文件格式如下(mysqldb_list.txt)：
IP,Port,User,Password,endpoint
192.168.2.21,3306,root,123,mysql-21:3306 192.168.2.88,3306,root,123,mysql-88:3306
最后执行：
python mysql_monitor.py mysqldb_list.txt
2) Redis 收集信息脚本(redis_monitor.py)
#!/bin/env python
#-*- coding:utf-8 -*-import json
import time
import re
import redis
import requests
import fileinput
import datetimeclass RedisMonitorInfo():def __init__(self,host,port,password):self.host = hostself.port = portself.password = passworddef stat_info(self):try:r = redis.Redis(host=self.host, port=self.port, password=self.password)stat_info = r.info()return stat_infoexcept Exception, e:print (datetime.datetime.now()).strftime("%Y-%m-%d %H:%M:%S")print ereturn dict()def cmdstat_info(self):try:r = redis.Redis(host=self.host, port=self.port, password=self.password)cmdstat_info = r.info('Commandstats')return cmdstat_infoexcept Exception, e:print (datetime.datetime.now()).strftime("%Y-%m-%d %H:%M:%S")print ereturn dict()if __name__ == '__main__':open_falcon_api = 'http://192.168.200.86:1988/v1/push'db_list= []for line in fileinput.input():db_list.append(line.strip())for db_info in db_list:
# host,port,password,endpoint,metric = db_info.split(',')host,port,password,endpoint = db_info.split(',')timestamp = int(time.time())step = 60falcon_type = 'COUNTER'
# tags = "port=%s" %porttags = ""conn = RedisMonitorInfo(host,port,password)#查看各个命令每秒执行次数redis_cmdstat_dict = {}redis_cmdstat_list = []cmdstat_info = conn.cmdstat_info()for cmdkey in cmdstat_info:redis_cmdstat_dict[cmdkey] = cmdstat_info[cmdkey]['calls']for _key,_value in redis_cmdstat_dict.items():falcon_format = {'Metric': '%s' % (_key),'Endpoint': endpoint,'Timestamp': timestamp,'Step': step,'Value': int(_value),'CounterType': falcon_type,'TAGS': tags}redis_cmdstat_list.append(falcon_format)#查看Redis各种状态,根据需要增删监控项,str的值需要转换成intredis_stat_list = []monitor_keys = [('connected_clients','GAUGE'),('blocked_clients','GAUGE'),('used_memory','GAUGE'),('used_memory_rss','GAUGE'),('mem_fragmentation_ratio','GAUGE'),('total_commands_processed','COUNTER'),('rejected_connections','COUNTER'),('expired_keys','COUNTER'),('evicted_keys','COUNTER'),('keyspace_hits','COUNTER'),('keyspace_misses','COUNTER'),('keyspace_hit_ratio','GAUGE'),('keys_num','GAUGE'),]stat_info = conn.stat_info() for _key,falcon_type in monitor_keys:#计算命中率if _key == 'keyspace_hit_ratio':try:_value = round(float(stat_info.get('keyspace_hits',0))/(int(stat_info.get('keyspace_hits',0)) + int(stat_info.get('keyspace_misses',0))),4)*100except ZeroDivisionError:_value = 0#碎片率是浮点数elif _key == 'mem_fragmentation_ratio':_value = float(stat_info.get(_key,0))#拿到key的数量elif _key == 'keys_num':_value = 0 for i in range(16):_key = 'db'+str(i)_num = stat_info.get(_key)if _num:_value += int(_num.get('keys'))_key = 'keys_num'#其他的都采集成counter，intelse:try:_value = int(stat_info[_key])except:continuefalcon_format = {'Metric': '%s' % (_key),'Endpoint': endpoint,'Timestamp': timestamp,'Step': step,'Value': _value,'CounterType': falcon_type,'TAGS': tags}redis_stat_list.append(falcon_format)load_data = redis_stat_list+redis_cmdstat_listprint json.dumps(load_data,sort_keys=True,indent=4)requests.post(open_falcon_api, data=json.dumps(load_data)) 指标说明：收集指标里的COUNTER表示每秒执行次数，GAUGE表示直接输出值。
| 指标 | 类型 | 说明 |
| connected_clients | GAUGE | 连接的客户端个数 |
| blocked_clients | GAUGE | 被阻塞客户端的数量 |
| used_memory | GAUGE | Redis分配的内存的总量 |
| used_memory_rss | GAUGE | OS分配的内存的总量 |
| mem_fragmentation_ratio | GAUGE | 内存碎片率，used_memory_rss/used_memory |
| total_commands_processed | COUNTER | 每秒执行的命令数，比较准确的QPS |
| rejected_connections | COUNTER | 被拒绝的连接数/秒 |
| expired_keys | COUNTER | 过期KEY的数量/秒 |
| evicted_keys | COUNTER | 被驱逐KEY的数量/秒 |
| keyspace_hits | COUNTER | 命中KEY的数量/秒 |
| keyspace_misses | COUNTER | 未命中KEY的数量/秒 |
| keyspace_hit_ratio | GAUGE | KEY的命中率 |
| keys_num | GAUGE | KEY的数量 |
| cmd_* | COUNTER | 各种名字都执行次数/秒 |
使用说明：读取配置到都数据库列表执行，配置文件格式如下(redisdb_list.txt)：
IP,Port,Password,endpoint
192.168.1.56,7021,zhoujy,redis-56:7021 192.168.1.55,7021,zhoujy,redis-55:7021
最后执行：
python redis_monitor.py redisdb_list.txt
3) MongoDB 收集信息脚本(mongodb_monitor.py)
...后续添加
4）其他相关的监控（需要装上agent），比如下面的指标：
| 告警项 | 触发条件 | 备注 |
|---|---|---|
| load.1min | all(#3)>10 | Redis服务器过载，处理能力下降 |
| cpu.idle | all(#3)<10 | CPU idle过低，处理能力下降 |
| df.bytes.free.percent | all(#3)<20 | 磁盘可用空间百分比低于20%，影响从库RDB和AOF持久化 |
| mem.memfree.percent | all(#3)<15 | 内存剩余低于15%，Redis有OOM killer和使用swap的风险 |
| mem.swapfree.percent | all(#3)<80 | 使用20% swap,Redis性能下降或OOM风险 |
| net.if.out.bytes | all(#3)>94371840 | 网络出口流量超90MB,影响Redis响应 |
| net.if.in.bytes | all(#3)>94371840 | 网络入口流量超90MB,影响Redis响应 |
| disk.io.util | all(#3)>90 | 磁盘IO可能存负载，影响从库持久化和阻塞写 |
相关文档：
https://github.com/iambocai/falcon-monit-scripts(redis monitor)
https://github.com/ZhuoRoger/redismon(redis monitor)
https://www.cnblogs.com/zhoujinyi/p/6645104.html
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