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How to create automated AWS billing reports

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Introduction

Amazon offers the skill to originate Billing Alarms which will moreover be ancient to alert every time your AWS bill exceeds a particular threshold. Nonetheless, this technique has just a few shortcomings:

  • You would like to role a predefined threshold. Whereas you are first starting up to use AWS, it’s tough to know what your AWS bill will leer esteem. deal of folks role this threshold stunning low to be marvelous.

  • An alert esteem this tends to be reactive as an different of proactive. The apprehension will get introduced about once the threshold has already crossed. As an illustration, I had forgotten to flip off an EC2 instance I used to be once now now now not utilizing nonetheless I simplest learned about per week later once my billing threshold crossed the restrict.

Cost Explorer does present a easy-to-use interface that can relief withhold you on high of your billing files. Nonetheless, this requires one to use the instrument on a phenomenal foundation to be distinct that we don’t leave out the relaxation.

On this text, we are in a position to leer at how that you would be in a position to enjoy a easy pipeline to send us billing reports over electronic mail. The generated characterize will leer esteem this:

billing-alert-email

The instruments we are in a position to use are:

  • AWS Lambda
  • Easy E-mail Service
  • Cost Explorer API

Getting Started

The provision code for the project is equipped at this repository.

Project Setup

Build a brand contemporary directory for the application

mkdir serverless-rate-indicators
cd serverless-rate-indicators

Setup a virtualenv for the application

virtualenv env
provide env/bin/in point of fact handy

Build requirements.txt with the whole dependencies

Install the dependencies

Speed the next elaborate in the shell to set up the whole dependencies.

pip set up -r requirements.txt

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Build scaffolding

We are going to originate a brand contemporary folder known as app which is in a job to retailer the application logic for the Cost Explorer API as properly as utilizing SES.

mkdir app
contact app/__init__.py app/cost_explorer.py app/electronic mail.py

We are going to moreover originate a file known as handler.py in the muse directory. This file will gain the logic ancient to generate billing reports.

Cost Explorer API

We shall be utilizing the Cost And Utilization endpoint from Cost Explorer to glean the billing files we need.

Replace the contents of the cost_explorer.py file we created earlier with this:


import boto3
from datetime import date, datetime, timedelta
from dateutil.relativedelta import relativedelta


class CostExplorer: 
    TODAY_DATE = datetime.utcnow().date()
    CUR_MONTH_DATE = TODAY_DATE.exchange(day=1)
    PREV_MONTH_DATE:  date = CUR_MONTH_DATE - relativedelta(months=+1)

    def __init__(self): 
        self.shopper = boto3.shopper("ce")
        self.metrics = ["UNBLENDED_COST"]
        self.foreign money: str = "USD"

        self.daily_report_kwargs = {
            "TimePeriod":  self._get_timeperiod(
                originate=self.TODAY_DATE - timedelta(days=2), # start_dt is inclusive
                finish=self.TODAY_DATE, # end_dt is exclusive
            ),
            "Metrics":  self.metrics,
            "Granularity":  "DAILY"
        }

        self.monthly_report_kwargs = {
            "TimePeriod":  self._get_timeperiod(
                originate=self.PREV_MONTH_DATE, # start_dt is inclusive
                finish=self.TODAY_DATE, # end_dt is exclusive
            ),
            "Metrics":  self.metrics,
            "Granularity":  "MONTHLY"
        }

    def _get_timeperiod(self, originate:  date, finish:  date): 
        return {
            "Commence":  originate.isoformat(),
            "Pause":  finish.isoformat(),
        }

    def _get_data(self, results): 
        """
        Retrieves the person billing rows from rate explorer files.
        """
        rows = []
        for v in results: 
            row = {"date": v["TimePeriod"]["Start"]}
            for i in v["Groups"]: 
                key = i["Keys"][0]
                row.update({key: waft(i["Metrics"]["UnblendedCost"]["Amount"])})
            row.update({"Entire": waft(v["Total"]["UnblendedCost"]["Amount"])})
            rows.append(row)

        return [f"{row['date']}: {round(row['Total'], 2)}" for row in rows]

    def generate_report(self, report_kwargs): 
        """
        Bag rate files in line with the granularity, originate date and finish date.
        """
        response = self.shopper.get_cost_and_usage(report_kwargs)
        return "n".join(self._get_data(response["ResultsByTime"]))

Key Substances

  • We’re attempting to generate two reports, one for the closing 2 days (day after day granularity) and one to compare the exhaust closing month vs the present month (monthly granularity).

  • We ancient Unblended prices to characterize our billing files. Extra files about this could perchance be found right here.

Easy E-mail Service (SES)

We shall be utilizing SES to send the billing reports to ourselves by strategy of electronic mail.

Requirements

SES requires a verified electronic mail contend with sooner than it might also simply moreover be ancient. Verification could also simply moreover be performed by strategy of the AWS console.

The utilization of SES

Replace the contents of electronic mail.py with the code snippet below:


import boto3


class EmailClient: 
    SENDER = "AWS Cost Alert <[email protected]>"
    SUBJECT = "Day-to-day AWS Billing Story"
    # The electronic mail body for recipients with non-HTML electronic mail purchasers.
    BODY_TEXT = """AWS Billing Signals rn
    Day-to-day billing characterizern
    {daily_billing_report}rn
    Monthly billing characterizern
    {monthly_billing_report}rn
    """

    # The HTML body of the electronic mail.
    BODY_HTML = """
    
    
    

AWS Billing Alert


Day-to-day Billing

{daily_billing_report}


Monthly Billing

{monthly_billing_report}

"""
# The persona encoding for the electronic mail. CHARSET = "UTF-8" # recipient electronic mail contend with RECIPIENT = "[email protected]" def __init__(self): self.shopper = boto3.shopper("ses") def send(self, daily_billing_report, monthly_billing_report): """Ship an electronic mail which incorporates AWS billing files""" email_text = self.BODY_TEXT.layout( daily_billing_report=daily_billing_report, monthly_billing_report=monthly_billing_report ) email_html = self.BODY_HTML.layout( daily_billing_report=daily_billing_report, monthly_billing_report=monthly_billing_report ) response = self.shopper.send_email( Destination={ "ToAddresses": [ self.RECIPIENT, ], }, Message={ "Body": { "Html": { "Charset": self.CHARSET, "Knowledge": email_html }, "Text": { "Charset": self.CHARSET, "Knowledge": email_text, }, }, "Field": { "Charset": self.CHARSET, "Knowledge": self.SUBJECT, }, }, Offer=self.SENDER, )

Key facets:

  • Replace SENDER and RECEPIENT with the electronic mail contend with you verified with SES.

Producing a billing characterize

We are going to now generate a characterize utilizing Cost Explorer and SES. Replace the contents of handler.py with the code snippet below:

from app.cost_explorer import CostExplorer
from app.electronic mail import EmailClient


def main(): 
    ce = CostExplorer()
    daily_report = ce.generate_report(ce.daily_report_kwargs)
    monthly_report = ce.generate_report(ce.monthly_report_kwargs)

    email_client = EmailClient()
    email_client.send(
        daily_billing_report=daily_report,
        monthly_billing_report=monthly_report
    )


if __name__ == "__main__": 
    main()

Subsequent, jog the script out of your terminal utilizing the next elaborate:

In case your AWS profile is setup with the categorical permissions, it’s good to in finding an electronic mail in conjunction with your billing files. This what the electronic mail have to leer esteem:

billing-alert-email

Integrating AWS Lambda

Now that we now have generated the billing characterize locally, we are in a position to compose use of the Serverless Framework to originate a serverless pipeline utilizing AWS Lambda.

Requirements

  1. Setup serverless framework by following the directions listed right here.

  2. Speed the next instructions after installing the serverless framework.

    npm init -f
    npm set up --set up-dev serverless-python-requirements
    

The serverless-python-requirements plugin automatically bundles dependencies from requirements.txt and makes them available to your Lambda feature.

Organising the serverless project

Subsequent, originate the file serverless.yml in your root directory and reproduction the next drawl material:


provider:  serverless-rate-indicators

plugins: 
  - serverless-python-requirements

equipment: 
  excludeDevDependencies:  factual
  exclude: 
    - node_modules/

custom: 
  pythonRequirements: 
    slim:  factual
    strip:  fallacious
    slimPatternsAppendDefaults:  factual
    slimPatterns: 
      - "/*.egg-data*"
      - "/*.dist-data*"
    dockerizePip:  factual

supplier: 
  name:  aws
  runtime:  python3.7
  stage:  dev
  intention:  us-west-2
  iamRoleStatements: 
    - Originate:  Allow
      Circulate: 
        - ses:SendEmail
      Resource: 
        - "*"
    - Originate:  Allow
      Circulate: 
        - ce:GetCostAndUsage
      Resource: 
        - "*"

capabilities: 
  send_daily_cost_report: 
    handler:  handler.generate_report
    occasions: 
      - http:  GET howdy

Key facets

  • The lambda feature will have the permission to query the CostAndUsage feature in Cost Explorer and SendEmail in SES.
  • To ascertain our Lambda feature, we are in a position to originate a short lived HTTP endpoint known as howdy.

Lambda Handler

Ahead of we deploy the Lambda feature to AWS, we pick to update the Lambda feature so as that it’s going to answer to an HTTP inquire. Replace the contents of your handler.py with the next code snippet:

from app.cost_explorer import CostExplorer
from app.electronic mail import EmailClient


def generate_report(match, context): 
    ce = CostExplorer()
    daily_report = ce.generate_report(ce.daily_report_kwargs)
    monthly_report = ce.generate_report(ce.monthly_report_kwargs)

    email_client = EmailClient()
    email_client.send(
        daily_billing_report=daily_report,
        monthly_billing_report=monthly_report
    )

    return {
        "statusCode":  200,
        "headers":  {
            "Speak material-Model":  "application/json",
        },
        "body":  "success",
    }

Now we are in a position to deploy the Lambda feature to AWS. Speed the next elaborate in your terminal:

If the deploy is successful, it’s good to be in a job to leer the HTTP endpoint to your Lambda esteem this:

sls-deploy

Whereas you click on on the HTTP endpoint, it’s good to leer output esteem this:

lambda-http

Scheduled Lambda

Lastly, we are in a position to update our Lambda feature to jog as a scheduled cron as an different of an HTTP endpoint. We are going to setup our Lambda feature to jog once a day.

Replace the capabilities share of serverless.yml:

capabilities: 
  send_daily_cost_report: 
    # handler: handler.generate_report
    # occasions:
    #   - http: GET howdy
    handler:  handler.generate_report
    occasions: 
      - time table:  cron(0 9 * * ? *)

Now now we have scheduled our Lambda feature to jog on on each day foundation foundation at 9 am.

Conclusion

I in actuality have been utilizing this setup for the previous couple of weeks and it has been precious in conserving on high of my AWS billing with out having to fear about checking the console repeatedly. The associated rate explorer API has a good deal of quite lots of reporting alternate choices and likewise that you would be in a position to generate a characterize that works for you.

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