【分布式监控系统】第4章——监控报警策略设计

【分布式监控系统】第4章——监控报警策略设计

设计思路

数据库设计

class ServiceIndex(models.Model): name = models.CharField(max_length=64) #Linux cpu idle key =models.CharField(max_length=64,unique=True) #idle data_type_choices = ( ('int',"int"), ('float',"float"), ('str',"string") ) data_type = models.CharField(u'指标数据类型',max_length=32,choices=data_type_choices,default='int') memo = models.CharField(u"备注",max_length=128,blank=True,null=True) def __str__(self): return "%s.%s" %(self.name,self.key)class Service(models.Model): name = models.CharField(u'服务名称',max_length=64,unique=True) interval = models.IntegerField(u'监控间隔',default=60) plugin_name = models.CharField(u'插件名',max_length=64,default='n/a') items = models.ManyToManyField('ServiceIndex',verbose_name=u"指标列表",blank=True) has_sub_service = models.BooleanField(default=False,help_text=u"如果一个服务还有独立的子服务 ,选择这个,比如 网卡服务有多个独立的子网卡") #如果一个服务还有独立的子服务 ,选择这个,比如 网卡服务有多个独立的子网卡 memo = models.CharField(u"备注",max_length=128,blank=True,null=True) def __str__(self): return self.nameclass Template(models.Model): name = models.CharField(u'模版名称',max_length=64,unique=True) services = models.ManyToManyField('Service',verbose_name=u"服务列表") triggers = models.ManyToManyField('Trigger',verbose_name=u"触发器列表",blank=True) def __str__(self): return self.nameclass Trigger(models.Model): name = models.CharField(u'触发器名称', max_length=64) severity_choices = ( (1, 'Information'), (2, 'Warning'), (3, 'Average'), (4, 'High'), (5, 'Diaster'), ) # expressions = models.ManyToManyField(TriggerExpression,verbose_name=u"条件表达式") severity = models.IntegerField(u'告警级别', choices=severity_choices) enabled = models.BooleanField(default=True) memo = models.TextField(u"备注", blank=True, null=True) def __str__(self): return "" % (self.name, self.get_severity_display())class TriggerExpression(models.Model): trigger = models.ForeignKey('Trigger', verbose_name=u"所属触发器") service = models.ForeignKey(Service, verbose_name=u"关联服务") service_index = models.ForeignKey(ServiceIndex, verbose_name=u"关联服务指标") specified_index_key = models.CharField(verbose_name=u"只监控专门指定的指标key", max_length=64, blank=True, null=True) operator_type_choices = (('eq', '='), ('lt', '<'), ('gt', '>')) operator_type = models.CharField(u"运算符", choices=operator_type_choices, max_length=32) data_calc_type_choices = ( ('avg', 'Average'), ('max', 'Max'), ('hit', 'Hit'), ('last', 'Last'), ) data_calc_func = models.CharField(u"数据处理方式", choices=data_calc_type_choices, max_length=64) data_calc_args = models.CharField(u"函数传入参数", help_text=u"若是多个参数,则用,号分开,第一个值是时间", max_length=64) threshold = models.IntegerField(u"阈值") logic_type_choices = (('or', 'OR'), ('and', 'AND')) logic_type = models.CharField(u"与一个条件的逻辑关系", choices=logic_type_choices, max_length=32, blank=True, null=True) def __str__(self): return "%s %s(%s(%s))" % (self.service_index, self.operator_type, self.data_calc_func, self.data_calc_args) class Meta: pass # unique_together = ('trigger_id','service')class Action(models.Model): """报警策略""" name = models.CharField(max_length=64, unique=True) host_groups = models.ManyToManyField('HostGroup', blank=True) hosts = models.ManyToManyField('Host', blank=True) triggers = models.ManyToManyField('Trigger', blank=True, help_text=u"想让哪些trigger触发当前报警动作") interval = models.IntegerField(u'告警间隔(s)', default=300) operations = models.ManyToManyField('ActionOperation',verbose_name="报警动作") recover_notice = models.BooleanField(u'故障恢复后发送通知消息', default=True) recover_subject = models.CharField(max_length=128, blank=True, null=True) recover_message = models.TextField(blank=True, null=True) enabled = models.BooleanField(default=True) def __str__(self): return self.name class ActionOperation(models.Model): """报警动作""" name = models.CharField(max_length=64) step = models.SmallIntegerField(u"第n次告警", default=1, help_text="当trigger触发次数小于这个值时就执行这条记录里报警方式") action_type_choices = ( ('email', 'Email'), ('sms', 'SMS'), ('script', 'RunScript'), ) action_type = models.CharField(u"动作类型", choices=action_type_choices, default='email', max_length=64) notifiers = models.ManyToManyField('UserProfile', verbose_name=u"通知对象", blank=True) _msg_format = '''Host({hostname},{ip}) service({service_name}) has issue,msg:{msg}''' msg_format = models.TextField(u"消息格式", default=_msg_format) def __str__(self): return self.nameclass Host(models.Model): name = models.CharField(max_length=64,unique=True) ip_addr = models.GenericIPAddressField(unique=True) host_groups = models.ManyToManyField('HostGroup',blank=True) # A B C templates = models.ManyToManyField("Template",blank=True) # A D E monitored_by_choices = ( ('agent','Agent'), ('snmp','SNMP'), ('wget','WGET'), ) monitored_by = models.CharField(u'监控方式',max_length=64,choices=monitored_by_choices) status_choices= ( (1,'Online'), (2,'Down'), (3,'Unreachable'), (5,'Problem'), ) host_alive_check_interval = models.IntegerField(u"主机存活状态检测间隔", default=30) status = models.IntegerField(u'状态',choices=status_choices,default=1) memo = models.TextField(u"备注",blank=True,null=True) def __str__(self): return self.nameclass HostGroup(models.Model): name = models.CharField(max_length=64,unique=True) templates = models.ManyToManyField("Template",blank=True) memo = models.TextField(u"备注",blank=True,null=True) def __str__(self): return self.nameclass UserProfile(models.Model): user = models.OneToOneField(User) name = models.CharField(max_length=64,blank=True,null=True) def __str__(self): return self.nameclass EventLog(models.Model): """存储报警及其它事件日志""" event_type_choices = ((0, '报警事件'), (1, '维护事件')) event_type = models.SmallIntegerField(choices=event_type_choices, default=0) host = models.ForeignKey("Host") trigger = models.ForeignKey("Trigger", blank=True, null=True) log = models.TextField(blank=True, null=True) date = models.DateTimeField(auto_now_add=True) def __str__(self): return "host%s %s" % (self.host, self.log)

业务逻辑代码实现

url(r'client/service/report/$',api_views.service_report),

@csrf_exemptdef service_report(request): print("client data:",request.POST) if request.method == 'POST': #REDIS_OBJ.set("test_alex",'hahaha') try: print('host=%s, service=%s' %(request.POST.get('client_id'),request.POST.get('service_name') ) ) data = json.loads(request.POST['data']) #print(data) #StatusData_1_memory_latest client_id = request.POST.get('client_id') service_name = request.POST.get('service_name') #把数据存下来 data_saveing_obj = data_optimization.DataStore(client_id,service_name,data,REDIS_OBJ) #redis_key_format = "StatusData_%s_%s_latest" %(client_id,service_name) #data['report_time'] = time.time() #REDIS_OBJ.lpush(redis_key_format,json.dumps(data)) #同时触发trigger检查 print("-------触发trigger检查---------") host_obj = models.Host.objects.get(id=client_id) service_triggers = get_host_triggers(host_obj) trigger_handler = data_processing.DataHandler(settings,connect_redis=False) for trigger in service_triggers: trigger_handler.load_service_data_and_calulating(host_obj,trigger,REDIS_OBJ) print("service trigger::",service_triggers) except IndexError as e: print('----->err:',e) return HttpResponse(json.dumps("---report success---"))

#_*_coding:utf-8_*___author__ = 'Alex Li'from monitor import modelsimport json,timefrom django.core.exceptions import ObjectDoesNotExistclass ClientHandler(object): def __init__(self, client_id): self.client_id = client_id self.client_configs = { "services":{} } def fetch_configs(self): try: host_obj = models.Host.objects.get(id=self.client_id) template_list= list(host_obj.templates.select_related()) for host_group in host_obj.host_groups.select_related(): template_list.extend( host_group.templates.select_related() ) print(template_list) for template in template_list: #print(template.services.select_related()) for service in template.services.select_related(): #loop each service print(service) self.client_configs['services'][service.name] = [service.plugin_name,service.interval] except ObjectDoesNotExist: pass return self.client_configsdef get_host_triggers(host_obj): #host_obj = models.Host.objects.get(id=2) triggers = [] for template in host_obj.templates.select_related(): triggers.extend(template.triggers.select_related() ) for group in host_obj.host_groups.select_related(): for template in group.templates.select_related(): triggers.extend(template.triggers.select_related()) return set(triggers)……

#_*_coding:utf-8_*___author__ = 'Alex Li'import time,json,picklefrom django.conf import settingsfrom monitor import modelsfrom monitor.backends import redis_connimport operatorclass DataHandler(object): def __init__(self,django_settings,connect_redis=True): self.django_settings = django_settings self.poll_interval = 3 #每3秒进行一次全局轮训 self.config_update_interval = 120 #每120s重新从数据库加载一次配置数据 self.config_last_loading_time = time.time() self.global_monitor_dic = { #"h1":{"serivces":{"cpu":[1313],"disk":[333]}} } self.exit_flag = False if connect_redis: self.redis = redis_conn.redis_conn(django_settings) def looping(self): ''' start looping data ... 检测所有主机需要监控的服务的数据有没有按时汇报上来，只做基本检测 :return: ''' #get latest report data self.update_or_load_configs() #生成全局的监控配置dict count = 0 while not self.exit_flag: print("looping %s".center(50,'-') % count) count += 1 if time.time() - self.config_last_loading_time >= self.config_update_interval: print("\033[41;1mneed update configs ...\033[0m") self.update_or_load_configs() print("monitor dic",self.global_monitor_dic) if self.global_monitor_dic: for h,config_dic in self.global_monitor_dic.items(): '''config_dic {'services'{'cpu':[cpu_obj,0], 'mem':[mem_obj,0] }, 'trigger':{t1:t1_obj,} }''' print('handling host:\033[32;1m%s\033[0m' %h) for service_id,val in config_dic['services'].items(): #循环所有要监控的服务 #print(service_id,val) service_obj,last_monitor_time = val if time.time() - last_monitor_time >= service_obj.interval: #reached the next monitor interval print("\033[33;1mserivce [%s] has reached the monitor interval...\033[0m" % service_obj.name) self.global_monitor_dic[h]['services'][service_obj.id][1] = time.time() #self.load_service_data_and_calulating(h,service_obj) #only do basic data validataion here, alert if the client didn't report data to server in \ #the configured time interval self.data_point_validation(h,service_obj) #检测此服务最近的汇报数据 else: next_monitor_time = time.time() - last_monitor_time - service_obj.interval print("service [%s] next monitor time is %s" % (service_obj.name,next_monitor_time)) if time.time() - self.global_monitor_dic[h]['status_last_check'] >10: #检测 有没有这个机器的trigger,如果没有,把机器状态改成ok trigger_redis_key = "host_%s_trigger*" % (h.id) trigger_keys = self.redis.keys(trigger_redis_key) #print('len grigger keys....',trigger_keys) if len(trigger_keys) ==0: #没有trigger被触发,可以把状态改为ok了 h.status = 1 h.save() #looping triggers 这里是真正根据用户的配置来监控了 #for trigger_id,trigger_obj in config_dic['triggers'].items(): # #print("triggers expressions:",trigger_obj.triggerexpression_set.select_related()) # self.load_service_data_and_calulating(h,trigger_obj) time.sleep(self.poll_interval) def data_point_validation(self,host_obj,service_obj): ''' only do basic data validation here, alert if the client didn't report data to server in the configured time interval :param h: :param service_obj: :return: ''' service_redis_key = "StatusData_%s_%s_latest" %(host_obj.id,service_obj.name) #拼出此服务在redis中存储的对应key latest_data_point = self.redis.lrange(service_redis_key,-1,-1) if latest_data_point: #data list is not empty, latest_data_point = json.loads(latest_data_point[0].decode()) #print('laste::::',latest_data_point) print("\033[41;1mlatest data point\033[0m %s" % latest_data_point) latest_service_data,last_report_time = latest_data_point monitor_interval = service_obj.interval + self.django_settings.REPORT_LATE_TOLERANCE_TIME if time.time() - last_report_time > monitor_interval: #超过监控间隔但数据还没汇报过来,something wrong with client no_data_secs = time.time() - last_report_time msg = '''Some thing must be wrong with client [%s] , because haven't receive data of service [%s] \ for [%s]s (interval is [%s])\033[0m''' %(host_obj.ip_addr, service_obj.name,no_data_secs, monitor_interval) self.trigger_notifier(host_obj=host_obj,trigger_id=None,positive_expressions=None, msg=msg) print("\033[41;1m%s\033[0m" %msg ) if service_obj.name == 'uptime': #监控主机存活的服务 host_obj.status = 3 #unreachable host_obj.save() else: host_obj.status = 5 #problem host_obj.save() else: # no data at all print("\033[41;1m no data for serivce [%s] host[%s] at all..\033[0m" %(service_obj.name,host_obj.name)) msg = '''no data for serivce [%s] host[%s] at all..''' %(service_obj.name,host_obj.name) self.trigger_notifier(host_obj=host_obj,trigger_id=None,positive_expressions=None,msg=msg) host_obj.status = 5 #problem host_obj.save() #print("triggers:", self.global_monitor_dic[host_obj]['triggers']) def load_service_data_and_calulating(self,host_obj,trigger_obj,redis_obj): ''' fetching out service data from redis db and calculate according to each serivce's trigger configuration :param host_obj: :param trigger_obj: :param redis_obj: #从外面调用此函数时需传入redis_obj,以减少重复连接 :return: ''' #StatusData_1_LinuxCPU_10mins self.redis = redis_obj calc_sub_res_list= [] #先把每个expression的结果算出来放在这个列表里,最后再统一计算这个列表 positive_expressions = [] #报警的时候，让用户知道，是哪些条件导致触发器成立了 expression_res_string = '' #最终拼成的表达式运算字符串 for expression in trigger_obj.triggerexpression_set.select_related().order_by('id'): print(expression,expression.logic_type) expression_process_obj = ExpressionProcess(self,host_obj,expression) #单条表达式处理的实例 single_expression_res = expression_process_obj.process() #单条表达式处理方法，返回的是个dict, {'calc_res':True,'expression_obj':object} if single_expression_res: calc_sub_res_list.append(single_expression_res) #把单条结果放入表达式结果列表 if single_expression_res['expression_obj'].logic_type: #不是最后一条 expression_res_string += str(single_expression_res['calc_res']) + ' ' + \ single_expression_res['expression_obj'].logic_type + ' ' else: expression_res_string += str(single_expression_res['calc_res']) #把所有结果为True的expression提出来,报警时你得知道是谁出问题导致trigger触发了 if single_expression_res['calc_res'] == True: single_expression_res['expression_obj'] = single_expression_res['expression_obj'].id #要存到redis里,数据库对象转成id positive_expressions.append(single_expression_res) #else: #single expression不成立,随便加个东西,别让程序出错,这个地方我觉得是个bug # expression_res_string += 'None' print("whole trigger res:", trigger_obj.name,expression_res_string) if expression_res_string: trigger_res = eval(expression_res_string) #算整个Trigger表达式的结果 print("whole trigger res:", trigger_res ) if trigger_res:#终于走到这一步,该触发报警了 print("##############trigger alert:",trigger_obj.severity,trigger_res) self.trigger_notifier(host_obj,trigger_obj.id, positive_expressions,msg=trigger_obj.name) #msg 需要专门分析后生成, 这里是临时写的 def update_or_load_configs(self): ''' load monitor configs from Mysql DB :return: ''' all_enabled_hosts = models.Host.objects.all() for h in all_enabled_hosts: if h not in self.global_monitor_dic: # new host self.global_monitor_dic[h] = {'services':{}, 'triggers':{}} '''self.global_monitor_dic ={ 'h1':{'services'{'cpu':[cpu_obj,0], 'mem':[mem_obj,0] }, 'trigger':{t1:t1_obj,} } }''' #print(h.host_groups.select_related()) service_list = [] trigger_list = [] for group in h.host_groups.select_related(): #print("grouptemplates:", group.templates.select_related()) for template in group.templates.select_related(): #print("tempalte:",template.services.select_related()) #print("triigers:",template.triggers.select_related()) service_list.extend(template.services.select_related()) trigger_list.extend(template.triggers.select_related()) for service in service_list: if service.id not in self.global_monitor_dic[h]['services']: #first loop self.global_monitor_dic[h]['services'][service.id] = [service,0] else: self.global_monitor_dic[h]['services'][service.id][0] = service for trigger in trigger_list: #if not self.global_monitor_dic['triggers'][trigger.id]: self.global_monitor_dic[h]['triggers'][trigger.id] = trigger #print(h.templates.select_related() ) #print('service list:',service_list) for template in h.templates.select_related(): service_list.extend(template.services.select_related()) trigger_list.extend(template.triggers.select_related()) for service in service_list: if service.id not in self.global_monitor_dic[h]['services']: #first loop self.global_monitor_dic[h]['services'][service.id] = [service,0] else: self.global_monitor_dic[h]['services'][service.id][0] = service for trigger in trigger_list: self.global_monitor_dic[h]['triggers'][trigger.id] = trigger #print(self.global_monitor_dic[h]) #通过这个时间来确定是否需要更新主机状态 self.global_monitor_dic[h].setdefault('status_last_check',time.time()) self.config_last_loading_time = time.time() return True def trigger_notifier(self,host_obj,trigger_id, positive_expressions,redis_obj=None,msg=None): ''' all the triggers alerts need to be published through here :param host_obj: :param trigger_id: :param positive_expressions: it's list, contains all the expression has True result :param redis_obj: :return: ''' #alert.sendmail(msg ) #alert.sendsms(msg) if redis_obj: #从外部调用 时才用的到,为了避免重复调用 redis连接 self.redis = redis_obj print("\033[43;1mgoing to send alert msg to alert queue............\033[0m") print('trigger_notifier argv:',host_obj,trigger_id, positive_expressions,redis_obj) # msg_dic = {'host_id':host_obj.id, 'trigger_id':trigger_id, 'positive_expressions':positive_expressions, #实例 'msg':msg, 'time': time.strftime("%Y-%m-%d %H:%M:%S",time.localtime()), 'start_time':time.time() , 'duration':None } self.redis.publish(self.django_settings.TRIGGER_CHAN, pickle.dumps(msg_dic)) #先把之前的trigger加载回来,获取上次报警的时间,以统计 故障持续时间 trigger_redis_key = "host_%s_trigger_%s" % (host_obj.id, trigger_id) old_trigger_data = self.redis.get(trigger_redis_key) print("old_trigger_data",old_trigger_data) if old_trigger_data: old_trigger_data = old_trigger_data.decode() trigger_startime = json.loads(old_trigger_data)['start_time'] msg_dic['start_time'] = trigger_startime msg_dic['duration'] = round(time.time() - trigger_startime) #同时在redis中纪录这个trigger , 前端页面展示时要统计trigger 个数 self.redis.set(trigger_redis_key, json.dumps(msg_dic), 300) #一个trigger 纪录 5分钟后会自动清除, 为了在前端统计trigger个数用的class ExpressionProcess(object): ''' load data and calc it by different method ''' def __init__(self,main_ins,host_obj,expression_obj,specified_item=None): ''' :param main_ins: DataHandler 实例 :param host_obj: 具体的host obj :param expression_obj: :return: 计算单条表达式的结果 ''' self.host_obj = host_obj self.expression_obj = expression_obj #单条表达式 self.main_ins = main_ins #DataHandler instance self.service_redis_key = "StatusData_%s_%s_latest" %(host_obj.id,expression_obj.service.name) #拼出此服务在redis中存储的对应key self.time_range = self.expression_obj.data_calc_args.split(',')[0] #获取要从redis中取多长时间的数据,单位为minute print("\033[31;1m------>%s\033[0m" % self.service_redis_key) def load_data_from_redis(self): '''load data from redis according to expression's configuration''' time_in_sec = int(self.time_range) * 60 #下面的+60是默认多取一分钟数据,宁多勿少,多出来的后面会去掉 approximate_data_points = (time_in_sec + 60) / self.expression_obj.service.interval #获取一个大概要取的值 #stop_loading_flag = False #循环去redis里一个点一个点的取数据,直到变成True #while not stop_loading_flag: print("approximate dataset nums:", approximate_data_points,time_in_sec) data_range_raw = self.main_ins.redis.lrange(self.service_redis_key,-int(approximate_data_points),-1) #print("\033[31;1m------>%s\033[0m" % data_range) approximate_data_range = [json.loads(i.decode()) for i in data_range_raw] #存的依然是大概的数据量 data_range = [] #精确的需要的数据 列表 for point in approximate_data_range: #print('bread point:', point) val,saving_time = point if time.time() - saving_time < time_in_sec :#代表数据有效 data_range.append(point) #print("service index key:",self.expression_obj.service_index.key) #print(point) '''if val: #确保数据存在 if 'data' not in val:#代表这个dict没有sub_dict print("\033[44;1m%s\033[0m" %val[self.expression_obj.service_index.key]) #如何处理这些数据 呢? 是求avg(5), hit(5,3)....? 看来只能把数据集合交给不同的方法去处理了 #self.process(self.) #data_range.append( else: #像disk , nic这种有多个item的数据 for k,v in val['data'].items(): print("\033[45;1m%s, %s\033[0m" %(k,v)) print("\033[45;1m%s, %s\033[0m" %(k,v[self.expression_obj.service_index.key])) ''' #else: # print("data is invalid") print(data_range) return data_range def process(self): """取出指定的时间周期的数据，按照指定的数据 处理方法 对数据进行处理""" data_list = self.load_data_from_redis() #已经按照用户的配置把数据 从redis里取出来了, 比如 最近5分钟,或10分钟的数据 data_calc_func = getattr(self,'get_%s' % self.expression_obj.data_calc_func) #self.get_avg.... #data_calc_func = self.get_avg... single_expression_calc_res = data_calc_func(data_list) #[True,43,None] print("---res of single_expression_calc_res ",single_expression_calc_res) if single_expression_calc_res: #确保上面的条件 有正确的返回 res_dic = { 'calc_res':single_expression_calc_res[0], 'calc_res_val':single_expression_calc_res[1], 'expression_obj':self.expression_obj, 'service_item':single_expression_calc_res[2], } print("\033[41;1msingle_expression_calc_res:%s\033[0m" % single_expression_calc_res) return res_dic else: return False def get_avg(self,data_set): ''' return average value of given data set :param data_set: :return: ''' clean_data_list = []#['98','97',33,4,2] clean_data_dic = {} for point in data_set: val,save_time = point #print('---point:>', val) if val: if 'data' not in val:#没有子dict clean_data_list.append(val[self.expression_obj.service_index.key]) else: #has sub dict for k,v in val['data'].items(): if k not in clean_data_dic: clean_data_dic[k]=[] clean_data_dic[k].append(v[self.expression_obj.service_index.key]) if clean_data_list: clean_data_list = [float(i) for i in clean_data_list] #avg_res = 0 if sum(clean_data_list) == 0 else sum(clean_data_list)/ len(clean_data_list) avg_res = sum(clean_data_list)/ len(clean_data_list) print("\033[46;1m----avg res:%s\033[0m" % avg_res) return [self.judge(avg_res), avg_res,None] print('clean data list:', clean_data_list) elif clean_data_dic: for k,v in clean_data_dic.items(): clean_v_list = [float(i) for i in v] avg_res = 0 if sum(clean_v_list) == 0 else sum(clean_v_list) / len(clean_v_list) print("\033[46;1m-%s---avg res:%s\033[0m" % (k,avg_res)) if self.expression_obj.specified_index_key:#监控了特定的指标,比如有多个网卡,但这里只特定监控eth0 if k == self.expression_obj.specified_index_key:#就是监控这个特定指标,match上了 #在这里判断是否超越阈值 print("test res [%s] [%s] [%s]=%s") %(avg_res, self.expression_obj.operator_type, self.expression_obj.threshold, self.judge(avg_res), ) calc_res = self.judge(avg_res) if calc_res: return [calc_res,avg_res,k] #后面的循环不用走了,反正 已经成立了一个了 else:#监控这个服务 的所有项, 比如一台机器的多个网卡, 任意一个超过了阈值,都 算是有问题的 calc_res = self.judge(avg_res) if calc_res: return [calc_res,avg_res,k] print('specified monitor key:',self.expression_obj.specified_index_key) print('clean data dic:',k,len(clean_v_list), clean_v_list) else: #能走到这一步,代表 上面的循环判段都未成立 return [False,avg_res,k] else:#可能是由于最近这个服务 没有数据 汇报 过来,取到的数据 为空,所以没办法 判断阈值 return [False,None,None] def judge(self,calculated_val): ''' determine whether the index has reached the alert benchmark :param calculated_val: #已经算好的结果,可能是avg(5) or .... :return: ''' #expression_args = self.expression_obj.data_calc_args.split(',') #hit_times = expression_args[1] if len(expression_args)>1 else None #if hit_times:#定义了超过阈值几次的条件 calc_func = getattr(operator,self.expression_obj.operator_type) #calc_func = operator.eq.... return calc_func(calculated_val,self.expression_obj.threshold) def get_hit(self,data_set): ''' return hit times value of given data set :param data_set: :return: ''' pass

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