Analyze clients(aws) when redis connection getting exhausted

parse_redis_clients.py

# find which aws instances have consumed connections

import boto3

ec2 = boto3.resource('ec2')

running_instances = ec2.instances.filter(Filters=[{
    'Name': 'instance-state-name',
    'Values': ['running']}])

ec2info = dict()
for instance in running_instances:
    if instance.tags:
      for tag in instance.tags:
          if 'Name' in tag['Key']:
              name = tag['Value']
    # Add instance info to a dictionary         
    ec2info[instance.private_ip_address] = {
        'Id': instance.id,
        'Name': name,
        'Type': instance.instance_type,
        'State': instance.state['Name'],
        'Private IP': instance.private_ip_address,
        'Public IP': instance.public_ip_address,
        'Launch Time': instance.launch_time
    }
        

ip_cnt = dict()

# redis-cli -h hostname client list >> client_list.txt
f = open('./client_list.txt', 'r')
lines = f.readlines()
for l in lines:
  ip = l.split()[1][5:].split(':')[0]
  cnt = ip_cnt.get(ip, 0)
  ip_cnt.update({ip: cnt+1})

# group ip by instance.tag.Name
keys = frozenset(ip_cnt.keys())
for key in keys:
  if key in ec2info:
    name = ec2info.get(key).get('Name')
    cnt = ip_cnt.get(name, 0)
    ip_cnt[name] = ip_cnt[key] + cnt
    del ip_cnt[key]

ip_cnt = {k: v for k, v in sorted(ip_cnt.items(), key=lambda item: -item[1])}

_sum=0
for k, v in ip_cnt.items():
  print('service - ' + k + ' : ' + str(v))
  _sum += v

print('connection sum: ' + str(_sum))


"""
output example:
service - abc : 15
service - eee : 10
service - cdf : 5
connection sum: 30
"""