Cloudwatch未使用boto3创建自定义日志度量标准

Question

我试图编写一个AWS，它将遍历所有Cloudwatch日志组，为每个日志组上的搜索项创建一个度量过滤器。

不幸的是，虽然我对put_metric_filter的所有调用都收到HTTP200个响应，但大多数调用都没有被创建(4/15调用导致创建过滤器)。

我有一个AWS Lambda，它的处理程序文件是'handler.py'：

from __future__ import print_function
from basicExample import ManageMetricsAndAlarms

import json, logging

log = logging.getLogger()
log.setLevel(logging.INFO)

def handler(event, context):
  log.info("Received event {}".format(json.dumps(event)))
  mc = ManageMetricsAndAlarms(event, context)
  response = mc.main()
  return json.dumps(response)

它从‘ManageMetricsAndAlarms’类调用'basicExample.py‘类，该类映射到一个日志组名称数组上，为每个类创建一个对术语“错误”进行筛选的度量：

from __future__ import print_function

import boto3, os, sys, json, botocore, logging

log = logging.getLogger()
log.setLevel(logging.INFO)

class ManageMetricsAndAlarms:

  # -------------------------------------------------
  def __init__(self,event,context):
    self.event   = event

  # -------------------------------------------------
  def main(self):
    cloudwatch = boto3.resource('cloudwatch')
    metricsNamespace = 'ExampleMetrics'
    errorFilter = '{ $.levelname = "ERROR" }'

    # Supposing that I have log groups for 10 imaginatively named lambdas
    logGroupNames = [
      '/aws/lambda/Lambda-1', '/aws/lambda/Lambda-2', 
      '/aws/lambda/Lambda-3', '/aws/lambda/Lambda-4',
      '/aws/lambda/Lambda-5', '/aws/lambda/Lambda-6',
      '/aws/lambda/Lambda-7', '/aws/lambda/Lambda-8',
      '/aws/lambda/Lambda-9', '/aws/lambda/Lambda-10'
    ]

    # map over the log groups adding a metric filter for 'ERROR' to each
    responses = map(lambda lg: self.createErrorFilter(metricsNamespace, errorFilter, lg), logGroupNames)
    return responses

  # -------------------------------------------------

  def createErrorFilter(self, metricsNamespace, filterPattern, logGroup):
    metricName = logGroup + '_ErrorCount'
    logs_client = boto3.client('logs')

    log.info('Put metric filter ' + metricName + ' with filter $.levelname-ERROR on logGroup: ' + logGroup)
    errorFilter = logs_client.put_metric_filter(
        logGroupName = logGroup,
        filterName ='ERROR-filter',
        filterPattern = filterPattern,
        metricTransformations = [
            {
                'metricNamespace': metricsNamespace,
                'metricValue': '1',
                'metricName': metricName,
            }
        ]
    )
    log.info('errorFilter response: ' + json.dumps(errorFilter))

    return errorFilter

  # -------------------------------------------------

我对python非常陌生，所以我想我错过了一些基本的东西，但是任何帮助都会很感激！

Answer 1

很少有事情需要考虑：

1. 你为什么要把这个放在灯笼上？你打算每分钟/每小时在同一块羊羔上放同样的过滤器吗？通常，您应该只执行一次脚本(或者在部署新lambdas之后)。
2. map是一个懒惰的评估器，所以您需要类似于 如果要执行函数，则为list(map(function x: print(x), iterable))。

下面是一个例子

import boto3


def createErrorFilter(metricsNamespace, filterPattern, logGroup):


    metricName = logGroup + '_example'
    logs_client = boto3.client('logs')

    errorFilter = logs_client.put_metric_filter(
    logGroupName = logGroup,
    filterName ='ERROR-filter',
    filterPattern = filterPattern,
    metricTransformations = [
        {
            'metricNamespace': metricsNamespace,
            'metricValue': '1',
            'metricName': metricName,
        }
    ]
    )
    print('ok')
    return 

cloudwatch = boto3.resource('cloudwatch')
metricsNamespace = 'ExampleMetrics-2'
errorFilter = 'ERROR'


logGroupNames = [
  '/aws/lambda/lambda1', '/aws/lambda/lambda2'
]

# map over the log groups adding a metric filter for 'ERROR' to each
responses = list(map(lambda lg: createErrorFilter(metricsNamespace, errorFilter, lg), logGroupNames))