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handler.py
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handler.py
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from collections import defaultdict
import boto3
import datetime
import os
import requests
import sys
n_days = 7
today = datetime.datetime.today()
week_ago = today - datetime.timedelta(days=n_days)
sparks = ['▁', '▂', '▃', '▄', '▅', '▆', '▇'] # Leaving out the full block because Slack doesn't like it: '█'
def sparkline(datapoints):
lower = min(datapoints)
upper = max(datapoints)
width = upper - lower
n_sparks = len(sparks) - 1
line = ""
for dp in datapoints:
scaled = 1 if width == 0 or upper == lower else (dp - lower) / width
which_spark = int(scaled * n_sparks)
line += (sparks[which_spark])
return line
def report_cost(event, context):
client = boto3.client('ce')
query = {
"TimePeriod": {
"Start": week_ago.strftime('%Y-%m-%d'),
"End": today.strftime('%Y-%m-%d'),
},
"Granularity": "DAILY",
"Filter": {
"Not": {
"Dimensions": {
"Key": "RECORD_TYPE",
"Values": [
"Credit",
"Refund",
"Upfront",
"Support",
]
}
}
},
"Metrics": ["UnblendedCost"],
"GroupBy": [
{
"Type": "DIMENSION",
"Key": "SERVICE",
},
],
}
result = client.get_cost_and_usage(**query)
buffer = "%-40s %-7s $%5s\n" % ("Service", "Last 7d", "Yday")
cost_per_day_by_service = defaultdict(list)
# Build a map of service -> array of daily costs for the time frame
for day in result['ResultsByTime']:
for group in day['Groups']:
key = group['Keys'][0]
cost = float(group['Metrics']['UnblendedCost']['Amount'])
cost_per_day_by_service[key].append(cost)
# Sort the map by yesterday's cost
most_expensive_yesterday = sorted(cost_per_day_by_service.items(), key=lambda i: i[1][-1], reverse=True)
for service_name, costs in most_expensive_yesterday[:5]:
buffer += "%-40s %s $%5.2f\n" % (service_name, sparkline(costs), costs[-1])
other_costs = [0.0] * n_days
for service_name, costs in most_expensive_yesterday[5:]:
for i, cost in enumerate(costs):
other_costs[i] += cost
buffer += "%-40s %s $%5.2f\n" % ("Other", sparkline(other_costs), other_costs[-1])
total_costs = [0.0] * n_days
for day_number in range(n_days):
for service_name, costs in most_expensive_yesterday:
try:
total_costs[day_number] += costs[day_number]
except IndexError:
total_costs[day_number] += 0.0
buffer += "%-40s %s $%5.2f\n" % ("Total", sparkline(total_costs), total_costs[-1])
credits_expire_date = os.environ.get('CREDITS_EXPIRE_DATE')
if credits_expire_date:
credits_expire_date = datetime.datetime.strptime(credits_expire_date, "%m/%d/%Y")
credits_remaining_as_of = os.environ.get('CREDITS_REMAINING_AS_OF')
credits_remaining_as_of = datetime.datetime.strptime(credits_remaining_as_of, "%m/%d/%Y")
credits_remaining = float(os.environ.get('CREDITS_REMAINING'))
days_left_on_credits = (credits_expire_date - credits_remaining_as_of).days
allowed_credits_per_day = credits_remaining / days_left_on_credits
relative_to_budget = (total_costs[-1] / allowed_credits_per_day) * 100.0
if relative_to_budget < 60:
emoji = ":white_check_mark:"
elif relative_to_budget > 110:
emoji = ":rotating_light:"
else:
emoji = ":warning:"
summary = "%s Yesterday's cost of $%5.2f is %.0f%% of credit budget $%5.2f for the day." % (
emoji,
total_costs[-1],
relative_to_budget,
allowed_credits_per_day,
)
else:
summary = "Yesterday's cost was $%5.2f." % (total_costs[-1])
hook_url = os.environ.get('SLACK_WEBHOOK_URL')
if hook_url:
resp = requests.post(
hook_url,
json={
"text": summary + "\n\n```\n" + buffer + "\n```",
}
)
if resp.status_code != 200:
print("HTTP %s: %s" % (resp.status_code, resp.text))
else:
print(summary)
print(buffer)