Open-Falcon 监控系统监控 MySQL/Redis/MongoDB 状态监控
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 re class MySQLMonitorInfo(): def __init__(self,host,port,user,password): self.host = host self.port = port self.user = user self.password = password def 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_value cursor.close() m.close() return Status_dict except Exception, e: print (datetime.datetime.now()).strftime("%Y-%m-%d %H:%M:%S") print e Status_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_string cursor.close() m.close() return dict(_engine_regex.findall(c)) except Exception, e: print (datetime.datetime.now()).strftime("%Y-%m-%d %H:%M:%S") print e return 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" %port tags = "" 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 = 0 elif _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 length for _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 datetime class RedisMonitorInfo(): def __init__(self,host,port,password): self.host = host self.port = port self.password = password def stat_info(self): try: r = redis.Redis(host=self.host, port=self.port, password=self.password) stat_info = r.info() return stat_info except Exception, e: print (datetime.datetime.now()).strftime("%Y-%m-%d %H:%M:%S") print e return 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_info except Exception, e: print (datetime.datetime.now()).strftime("%Y-%m-%d %H:%M:%S") print e return 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 = 60 falcon_type = 'COUNTER' # tags = "port=%s" %port tags = "" 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int redis_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)*100 except 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,int else: try: _value = int(stat_info[_key]) except: continue falcon_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_list print 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)
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万物之中,希望至美
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