AWS Hygiene Scripts

See also AUSPICES for setting up various hygiene scripts to automatically run in your AWS account.

Clean out old alarms

Python:

import boto3
import time

filterstring = 'MyProjectName'

client = boto3.client('cloudwatch')
alarms = client.describe_alarms(AlarmTypes=['MetricAlarm'],StateValue='INSUFFICIENT_DATA')
while True:
  for eachalarm in alarms['MetricAlarms']:
    if eachalarm['StateValue'] == 'INSUFFICIENT_DATA':
      if filterstring in eachalarm['AlarmName']:
        client.delete_alarms(AlarmNames = [eachalarm['AlarmName']])
        time.sleep(1) #avoid throttling
  token = alarms['NextToken']
  print(token)
  alarms = client.describe_alarms(AlarmTypes=['MetricAlarm'],StateValue='INSUFFICIENT_DATA',NextToken=token)

Clean out old log groups

Bash:

aws logs describe-log-groups| in2csv -f json --key logGroups > logs.csv

R:

(requires dplyr and readr)

library(dplyr)
library(readr)
read_csv(
  "logs.csv",
  col_types = cols_only(
    storedBytes = col_integer(),
    creationTime = col_double(),
    logGroupName = col_character()
  )
) %>%
  mutate(creationTime =
           as.POSIXct(creationTime / 1000,
                      origin = "1970-01-01")) %>%
  filter(storedBytes == 0) %>%
  select(logGroupName) %>%
  write_tsv("logs_clear.txt", col_names = F)

Bash:

parallel aws logs delete-log-group --log-group-name {1} :::: logs_clear.txt