---
AWSTemplateFormatVersion: '2010-09-09'

Description: HumanReadableAlertsForLookoutForMetrics IAM Policies, SNS Topic, SNS Subscription, and Lambda Function to deliver human readable alerts from Lookout for Metrics.

Parameters:

  SNSTopicName:
    Type: String
    Default: HumanReadableAlerts
    Description: Enter the name of the SNS Topic to be created for the alerts.

  EmailAddressForAlerts:
    Type: String
    Default: email@address.com
    Description: Enter the name email address where you wish to receive alerts.

Resources:
  # SNS Topic For Final Alerts
  SNSTopic:
    Type: AWS::SNS::Topic
    Properties:
      TopicName: !Ref SNSTopicName

  # SNS Subscription To Receive Alerts:
  MySubscription:
    Type: AWS::SNS::Subscription
    Properties:
      Endpoint: !Ref EmailAddressForAlerts
      Protocol: email
      TopicArn: !Ref SNSTopic

  # Role for Lambda
  HumanReadableAlertLambdaRole:
    DependsOn: SNSTopic
    Type: AWS::IAM::Role
    Properties:
      RoleName: HumanReadableAlertLambdaRole
      AssumeRolePolicyDocument:
        Statement:
          - Effect: Allow
            Principal:
              Service: lambda.amazonaws.com
            Action: sts:AssumeRole
      Policies: 
        - 
          PolicyName: "HumanReadableAlertPolicySNSLambda"
          PolicyDocument: 
            Version: "2012-10-17"
            Statement: 
              - 
                Effect: "Allow"
                Action: "sns:Publish"
                Resource: !Ref SNSTopic

  # Lambda Function To Deliver Alerts
  HumanReadableAlertsLambdaFunction:
    DependsOn: HumanReadableAlertLambdaRole
    Type: AWS::Lambda::Function
    Properties:
      FunctionName: HumanReadableAlerts
      Role:
        Fn::GetAtt:
          - HumanReadableAlertLambdaRole
          - Arn
      Runtime: python3.8
      Handler: index.lambda_handler
      Environment:
        Variables:
          topic_arn: !Ref SNSTopic
      Code:
        ZipFile: |
          import json
          import os
          import datetime
          from dateutil.parser import parse
          import boto3

          # Read in the topic as provided in an environment variable
          topic_arn = os.getenv('topic_arn')


          def send_to_sns(message):
              # This takes in a string and simply sends it onto SNS as a message, subject provided for Email clients
              sns = boto3.client("sns")
              sns.publish(TopicArn=topic_arn, 
                      Message=message, 
                      Subject="Lookout for Metrics Alert Update")


          def create_anomaly_string(input_json):
              """
              This function does most of the work, it takes in the entire message of the alert from Lookout for Metrics, then converts it into a readable and actionable message. Steps are commented below, feel free to update as needed.
              """
              # The time is a critical bit of informatin to sort first, this obtains the time and gets it ready for the message
              timestamp = parse(input_json['timestamp'], fuzzy_with_tokens=True)[0]
              timestamp1 = timestamp.strftime("%B %d %Y")
              timestamp2 = timestamp.strftime("%H:%M")
              # Write the first bit about the anomaly, what happened and when.
              response = "An anomaly in " + str(input_json['impactedMetric']['metricName']) + " was detected on " + timestamp1 + ' at ' + timestamp2 + ".\n"
              # Next grab the list of impacted time series
              num_of_time_series = len(input_json['impactedMetric']['relevantTimeSeries'])
              # Report the number of impacted time series to your user
              response += str(num_of_time_series) + " time series was impacted.\n\n"

              # Iterate over each time series, listing the dimensions and their value
              for ts in range(num_of_time_series):
                  response += "TimeSeries: " + str(num_of_time_series) + " was impacted on the following dimensions and values:\n"
                  for item in input_json['impactedMetric']['relevantTimeSeries'][ts]['dimensions']:
                      response += "\t" + item['dimensionName'] + " - " + item['dimensionValue'] + "\n"
                      
              # Report the anomaly score
              response += "\nThe Anomaly  score was: " + str(input_json['anomalyScore']) + "\n"
              
              # Generate a link to the console for the user to learn more
              runtime_region = os.environ['AWS_REGION']
              url = "https://" + runtime_region + ".console.aws.amazon.com/lookoutmetrics/home?region=" + runtime_region + "#"
              url += str(input_json['anomalyDetectorArn'])
              url += "/detectorDetails"
              response += "To learn more visit the Lookout for Metrics console at: " + url + " \n"
              return response

          def lambda_handler(event, context):
              # Call the create string function
              response = create_anomaly_string(input_json=event)
              # Send the string to SNS
              send_to_sns(message=response)
              # Report completed
              return {
                  'statusCode': 200,
                  'body': json.dumps('Message Delivered!')
              }