观测云可用性 SLO 之跨多空间年度汇总统计

import timeimport datetimeimport requestsimport json
OPEN_API_BASE_URL = DFF.ENV('OPEN_API_URL')
# 注意，此方法是获取工作空间列表的，如果空间不多的情况，可手动收集 空间 token、空间名称等信息。def get_workspace_list():    """ 可手动构造workspace空间信息,也可以通过openapi 调用接口获取 """    #import wksp_automation__main as wksp_token    #response = wksp_token.gc_get_all_wksp_token_list()        response = [        {"wksp_name": "业务空间1", "wksp_token":"t5t55oken_xxxxxxx","sys_no": "project_id_xxxx"},        {"wksp_name": "业务空间2", "wksp_token":"t5t55oken_xxxxxxx","sys_no": "project_id_xxxx"},        {"wksp_name": "业务空间3", "wksp_token":"t5t55oken_xxxxxxx","sys_no": "project_id_xxxx"}                ]                    return response

def get_rum_application_list_by_wksp_key(wksp_key):    url = OPEN_API_BASE_URL + '/api/v1/rum_cfg/quick_list'    params = {        "appId": ""    }    headers = {        "Content-Type": "application/json",        "DF-API-KEY": wksp_key    }    response = requests.get(url, params=params, headers=headers)    response = json.loads(response.text)    return response["content"]
def get_last_mounth_first_day():

    from datetime import datetime, timedelta
    # 获取当前日期    current_date = datetime.now()
    # 获取当前年份和月份    year = current_date.year    month = current_date.month
    # 如果当前是1月，则上个月是去年的12月    if month == 1:        year -= 1        month = 12    else:        month -= 1
    # 创建上个月1号的datetime对象    first_day_of_last_month = datetime(year, month, 1)
    # 将datetime对象转换为时间戳（秒）    timestamp = first_day_of_last_month.timestamp()
    # 将时间戳转换为毫秒    timestamp_milliseconds = int(timestamp * 1000)
    print("上个月1号的时间戳（毫秒）是:", timestamp_milliseconds)    return timestamp_milliseconds
def get_last_mounth_last_day():

    from datetime import datetime, timedelta
    # 获取当前日期    current_date = datetime.now()
    # 获取上个月的年份和月份    if current_date.month == 1:        last_month_year = current_date.year - 1        last_month = 12    else:        last_month_year = current_date.year        last_month = current_date.month
    # 获取上个月的最后一天    last_day_of_last_month = datetime(last_month_year, last_month, 1) - timedelta(days=1)
    # 将datetime对象转换为时间戳（秒）    timestamp = last_day_of_last_month.timestamp()
    # 将时间戳转换为毫秒    timestamp_milliseconds = int(timestamp * 1000)
    print("上个月最后一天的时间戳（毫秒）是:", timestamp_milliseconds)    return timestamp_milliseconds
def get_jour_1_day_time():    from datetime import datetime, timedelta
    # 获取当前年份    current_year = datetime.now().year
    # 创建本年度1月1日的datetime对象    january_first = datetime(current_year, 1, 1)
    # 将datetime对象转换为毫秒时间戳    timestamp_ms = january_first.timestamp() * 1000
    print("本年度1月1日的毫秒时间戳是:", int(timestamp_ms))    return int(timestamp_ms)
def get_last_day_time():
    from datetime import datetime, timedelta
    # 获取当前时间    now = datetime.now()
    # 计算今天0点的时间    midnight = datetime(now.year, now.month, now.day)
    # 如果需要时间戳（秒）    timestamp = midnight.timestamp()
    # 如果需要毫秒时间戳    timestamp_ms = int(timestamp * 1000)    return timestamp_ms

@DFF.API('slo_cost_day',timeout=1500)def measure_slo_by_day():    """  计算昨日的 slo cost数据  """
    # 构造DQL 语句    today_slo_cost_sum = "E::`slo`:(sum(`df_slo_cost`))"    # 获取当前时间戳    current_time = time.localtime()
    today_date_start_timestamp = time.mktime((current_time.tm_year, current_time.tm_mon, current_time.tm_mday, 0, 0, 0, current_time.tm_wday, current_time.tm_yday, current_time.tm_isdst))    # 获取昨天0点时间戳    yesterday_start_timestamp = today_date_start_timestamp - 86400
    # 获取昨天23点59分59秒的时间戳    yesterday_end_timestamp = today_date_start_timestamp - 1
    # 查询时间范围    time_range = [int(yesterday_start_timestamp)*1000,int(yesterday_end_timestamp)*1000]
    # 查询所有命名空间的数据（）    # 如果无法查询到空间信息，则可以手动拼接多个空间的数组信息，提供给下面for循环遍历。    all_workspace_list = get_workspace_list()
    central_dataway = DFF.CONN('gc_dataway', token="tkn_xxxxxxx")
    last_day_of_last_month_timestamp = get_last_mounth_last_day()
    # 构造上报数据的结构
    _tags = {}    _fields = {}    _measurement = "cost_time"    for  workspace in all_workspace_list:        # 遍历所有空间
        dataway = DFF.CONN('gc_dataway', token=workspace["wksp_token"])        slo_status_code, slo_list = dataway.query(dql=today_slo_cost_sum,time_range=time_range)
        # 获取有slo cost 数据的空间        if slo_list is not None and len(slo_list.get("series",[]))>0:            cost_time = slo_list.get("series")[0].get("values")[0][1]            _tags["project_name"] = workspace["wksp_name"]            _tags["project_id"] = workspace["sys_no"]            _tags["org_name"] = org_name            _tags["env"] = "test"            _tags["status"] = "info"            _tags["source"] = "cost_time"            _fields["cost_time"] = cost_time            time_tmp = 1725119880000  # 临时时间戳            # res = central_dataway.write_logging(measurement=_measurement, tags=_tags, fields=_fields, timestamp=yesterday_end_timestamp)            res = central_dataway.write_logging(measurement=_measurement, tags=_tags, fields=_fields, timestamp=time_tmp)            print(_measurement,_fields,last_day_of_last_month_timestamp)

@DFF.API('slo_by_mounth',timeout=1500)def measure_slo_by_mounth():    """ 计算月slo   """
    last_day_of_last_month_timestamp = get_last_mounth_last_day()    first_day_of_last_month_timestamp = get_last_mounth_first_day()
    # 查询时间范围    time_range = [first_day_of_last_month_timestamp,last_day_of_last_month_timestamp+86400000]
    mounth_slo_cost_dql = "L('slo_statistic')::`slo_statistic`:(sum(`cost_time`)){env = 'prod'} BY `env`,`project_name`,`project_id`"
    central_dataway = DFF.CONN('gc_dataway', token="tkn_xxxxx")
    # 获取各个服务上个月的slo cost 数据    slo_status_code, slo_list = central_dataway.query(dql=mounth_slo_cost_dql,time_range=time_range)
    # 构造存储格式    _tags = {}    _measurement = "slo_statistic"    _fields = {}    print(slo_list)    slo_list = slo_list.get("series",[])    print(time_range,"查询时间戳")    print(last_day_of_last_month_timestamp,"存储时间戳")    print(slo_list)    # 计算 月度 slo    for slo in slo_list:        _tags = slo.get("tags")        _tags["status"] = "info"        _tags["source"] = "info"        _measurement = _measurement        cost_time = slo.get("values")[0][1]
        total_time_min = (last_day_of_last_month_timestamp - first_day_of_last_month_timestamp)/60        slo_sum =  (1- cost_time/total_time_min) * 100        _fields["sys_month_availability"] = slo_sum        status_code,res = central_dataway.write_logging(measurement=_measurement, tags=_tags, fields=_fields, timestamp=last_day_of_last_month_timestamp)        status_code,res2 = central_dataway.write_metric(measurement=_measurement, tags=_tags, fields=_fields, timestamp=last_day_of_last_month_timestamp)        print(_tags,_fields,_measurement,print,res)

@DFF.API('slo_by_year',timeout=1500)def measure_slo_by_year():    """ 计算年度slo  (1 – (cost_time / (1月1日到T-1的天数) * 24 * 60) ) * 100  """
    # 获取今年1月1号时间戳    this_year_jan_1_timestamp = get_jour_1_day_time()
    # 获取昨天的时间戳    last_day_time_timestamp = get_last_day_time()
    # 计算 1月1号 到昨天 的总时长 s转换成min    this_yeaml_time_sum = (this_year_jan_1_timestamp - last_day_time_timestamp)/60
    _tags = {}    _tags["status"] = "info"    _tags["org_name"] = "IT新业务xxx"    _measurement = "sys_year_availability"    _fields = {}
    # 查询时间范围    time_range = [this_year_jan_1_timestamp,last_day_time_timestamp]    print(time_range)    year_slo_cost_dql = "L('slo_statistic')::`slo_statistic`:(sum(`cost_time`)){env = 'prod'} BY `env`,`project_name`,`project_id`"
    central_dataway = DFF.CONN('gc_dataway', token="tkn_xxxxxx")
    # 获取各个服务上个月的slo cost 数据

    slo_status_code, slo_data = central_dataway.query(dql=year_slo_cost_dql,time_range=time_range)   # print(slo_data)    for data in slo_data.get("series","[]"):        print(data)        _fields["project_name"] = data.get("tags",{}).get("project_name")        _fields["project_id"] = data.get("tags",{}).get("project_id")        cost_time_year_by_project = data.get("values",[])[0][1]
        cost_time_slo = (1- cost_time_year_by_project / this_yeaml_time_sum)*100        _fields["sys_year_availability"] = int(cost_time_slo)
        status_code,res = central_dataway.write_logging(measurement=_measurement, tags=_tags, fields=_fields, timestamp=time.time())        print(_fields)