terraform-aws-connect-callcenter/eventbridge.tf at main · KHamwey/terraform-aws-connect-callcenter · GitHub

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################################################################################
# Fraud pipeline — Connect contact events → EventBridge → fraud scorer Lambda
################################################################################

data "archive_file" "fraud_scorer" {
  type        = "zip"
  source_file = "${path.module}/lambda/fraud_scorer.py"
  output_path = "${path.module}/lambda/fraud_scorer.zip"
}

resource "aws_cloudwatch_event_rule" "connect_contact_events" {
  name        = "${var.instance_alias}-connect-contact-events"
  description = "Route Amazon Connect contact events to the fraud scorer Lambda"

  event_pattern = jsonencode({
    source      = ["aws.connect"]
    detail-type = ["Amazon Connect Contact Event"]
    detail = {
      instanceArn = [try(module.amazon_connect.instance.arn, "")]
    }
  })
}

resource "aws_cloudwatch_event_target" "fraud_scorer" {
  rule      = aws_cloudwatch_event_rule.connect_contact_events.name
  target_id = "fraud-scorer-lambda"
  arn       = aws_lambda_function.fraud_scorer.arn
}

resource "aws_lambda_permission" "eventbridge_fraud_scorer" {
  statement_id  = "AllowEventBridgeInvoke"
  action        = "lambda:InvokeFunction"
  function_name = aws_lambda_function.fraud_scorer.function_name
  principal     = "events.amazonaws.com"
  source_arn    = aws_cloudwatch_event_rule.connect_contact_events.arn
}

resource "aws_cloudwatch_event_rule" "fraud_demo_events" {
  name        = "${var.instance_alias}-fraud-demo-events"
  description = "Synthetic fraud test events for pipeline validation (scripts/inject-test-event.sh)"

  event_pattern = jsonencode({
    source = ["fraud.demo"]
  })
}

resource "aws_cloudwatch_event_target" "fraud_scorer_demo" {
  rule      = aws_cloudwatch_event_rule.fraud_demo_events.name
  target_id = "fraud-scorer-lambda-demo"
  arn       = aws_lambda_function.fraud_scorer.arn
}

resource "aws_lambda_permission" "eventbridge_fraud_scorer_demo" {
  statement_id  = "AllowEventBridgeDemoInvoke"
  action        = "lambda:InvokeFunction"
  function_name = aws_lambda_function.fraud_scorer.function_name
  principal     = "events.amazonaws.com"
  source_arn    = aws_cloudwatch_event_rule.fraud_demo_events.arn
}

data "aws_iam_policy_document" "fraud_scorer_assume" {
  statement {
    effect  = "Allow"
    actions = ["sts:AssumeRole"]
    principals {
      type        = "Service"
      identifiers = ["lambda.amazonaws.com"]
    }
  }
}

resource "aws_iam_role" "fraud_scorer" {
  name               = "${var.instance_alias}-fraud-scorer"
  assume_role_policy = data.aws_iam_policy_document.fraud_scorer_assume.json
}

resource "aws_iam_role_policy_attachment" "fraud_scorer_basic" {
  role       = aws_iam_role.fraud_scorer.name
  policy_arn = "arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole"
}

data "aws_iam_policy_document" "fraud_scorer" {
  statement {
    sid    = "WriteFraudEvents"
    effect = "Allow"
    actions = [
      "s3:PutObject",
    ]
    resources = ["${aws_s3_bucket.fraud_events.arn}/raw/*"]
  }

  statement {
    sid    = "VelocityTracking"
    effect = "Allow"
    actions = [
      "dynamodb:GetItem",
      "dynamodb:PutItem",
      "dynamodb:UpdateItem",
    ]
    resources = [aws_dynamodb_table.fraud_velocity.arn]
  }

  statement {
    sid    = "StartFraudWorkflow"
    effect = "Allow"
    actions = [
      "states:StartExecution",
    ]
    resources = [aws_sfn_state_machine.fraud_workflow.arn]
  }
}

resource "aws_iam_role_policy" "fraud_scorer" {
  name   = "fraud-scorer"
  role   = aws_iam_role.fraud_scorer.id
  policy = data.aws_iam_policy_document.fraud_scorer.json
}

resource "aws_lambda_function" "fraud_scorer" {
  function_name = "${var.instance_alias}-fraud-scorer"
  role          = aws_iam_role.fraud_scorer.arn
  handler       = "fraud_scorer.handler"
  runtime       = "python3.12"
  timeout       = 30

  filename         = data.archive_file.fraud_scorer.output_path
  source_code_hash = data.archive_file.fraud_scorer.output_base64sha256

  environment {
    variables = {
      FRAUD_EVENTS_BUCKET     = aws_s3_bucket.fraud_events.id
      VELOCITY_TABLE_NAME     = aws_dynamodb_table.fraud_velocity.name
      FRAUD_STATE_MACHINE_ARN = aws_sfn_state_machine.fraud_workflow.arn
      VELOCITY_THRESHOLD      = tostring(var.fraud_velocity_threshold)
      KNOWN_GOOD_CALLERS      = join(",", var.fraud_known_good_callers)
    }
  }

  depends_on = [
    aws_iam_role_policy_attachment.fraud_scorer_basic,
    aws_sfn_state_machine.fraud_workflow,
  ]
}