Deploying a cloudwatch dashboard for monitoring Lambda Function Using Terragrunt

Introduction:-

Before we begin creating the CloudWatch dashboard, make sure you have the following prerequisites:

• An AWS account with appropriate permissions to create CloudWatch dashboards.

• #Terraform and #Terragrunt should be installed on your local machine.

• AWS credentials properly configured.

Step 1: Create a directory called cloudwatch-dashboard.

Create a folder with name lambda-dashboard in your homedirectory. with in that lambda-dashboard create a new folder module. In that module create file named main.tf and add the following code as mention in the below

Along with the dashboard we are also creating cloud watch alarm to trigger and notify you, when the lambda function breaches the threshold.

resource "aws_cloudwatch_dashboard" "lambda_dashboard" {
  dashboard_name = var.dashboard_name
  dashboard_body = jsonencode({
     widgets = [
      {
         type = "metric",
         x = 0,
         y = 6,
         width = 12,
         height = 6,
         properties = {
          metrics = [
            [
              "AWS/Lambda",
              "GetFunctionEventInvokeConfig",
              "FunctionName",
              "${var.lambda_function_name}",
              "Resource",
              "GetFunctionEventInvokeConfig"
            ],
            [
              "AWS/Usage",
              "CallCount",
              "Type",
              "API",
              ".",
              "GetFunctionEventInvokeConfig",
              "Service",
              "Lambda",
              "Class",
              "None"
            ],
          ]
          period = 300
          stat   = "Sum"
          visible = false
          region = "us-west-2"
           title = "Lambda Function Invocations"
        }
      },
      {
         type = "metric",
         x = 0,
         y = 12,
         width = 12,
         height = 6,
         properties = {
           metrics = [
            [
              "AWS/Lambda",
              "GetRuntimeManagementConfig",
              "FunctionName",
              "${var.lambda_function_name}",
              "Resource",
              "GetRuntimeManagementConfig"
            ],
            [
              "AWS/Usage",
              "CallCount",
              "Type",
              "API",
              ".",
              "GetRuntimeManagementConfig",
              "Service",
              "Lambda",
              "Class",
              "None"
            ],
          ]
          period = 300
          stat   = "Sum"
          visible = false
          region = "us-west-2"
           title = "Lambda Function Runtime Management"
        }
      }
    ]
  })
}

resource "aws_cloudwatch_metric_alarm" "duration_alarm" {
  alarm_name          = var.alarm_name
  comparison_operator = "GreaterThanOrEqualToThreshold"
  evaluation_periods  = 1
  metric_name         = "Duration"
  namespace           = "AWS/Lambda"
  period              = 300
  statistic           = "Average"
  threshold           = 5000
  alarm_description   = "This alarm is triggered if Lambda duration exceeds 5 seconds"
  alarm_actions       =  var.alarm_actions
}
resource "aws_cloudwatch_metric_alarm" "invocations_alarm" {
  alarm_name        = var.alarm_name1
  comparison_operator = "GreaterThanOrEqualToThreshold"
  evaluation_periods  = 1
  metric_name         = "Invocations"
  namespace           = "AWS/Lambda"
  period              = 300
  statistic           = "Sum"
  threshold           = 1000
  alarm_description   = "This alarm is triggered if Lambda invocations exceed 1000"
  alarm_actions       = var.alarm_actions
}

step 2: In the module folder, create one-more file called variable.tf file and paste the code mentioned below

variable "dashboard_name" {
    type = string
    description = "Name of the Dashboard"
}
variable "alarm_name" {
   type = string
   description = "Alarm name"
}
variable "alarm_name1" {
   type = string
   description = "Alarm name"
}
variable "region" {
   type = string
   description = "default region"
}
variable "alarm_actions" {
  type        = set(string)
  description = "Alarm Actions"
  default     = []
}
variable "lambda_function_name" {
  type = string
  description = "Lambda Function name"
}
variable "lambda_function_arn" {
    type   = string
    description = "lambda function arn"
}

Step 3:- Now Create a one more folder in called lambda in your lambda-dashboard directory and with in that lambda folder create a file called terragrunt.hcl & then copy paste the below code.

terraform {
  source = "../module"
}

include "root" {
path = find_in_parent_folders()
}

locals {
   function_name  = "example-lambda"
   function_arn   = "arn:aws:lambda:us-east-1:123456789012:function:my-lambda-function"
   sns_topic_arn  = "arn:aws:sns:us-east-1:123456789012:my-sns-topic"
}

 inputs = {
  alarm_name  = "lambda-monitor"
  alarm_name1  = "lambda-monitor2"
  alarm_name2  = "lambda-monitor3"
  dashboard_name = "lambda-dashboard"
  region        = "us-east-1"
  alarm_actions = [local.sns_topic_arn]
  lambda_function_name  = local.function_name
  lambda_function_arn  = local.function_arn
 }

Step 4:- Once all the setup is done locate to your cloud-watch folder and run terragrunt apply to deploy your code using terragrunt.

Step 5:- As you can see that there is a dashboard called lambda dashboard is being created in your aws cloud watch

Source-code Link :- “github.com/MahiraTechnology/Mahira-medium.git”.

Conclusion:-

In this tutorial, we explored how to create and deploy a #CloudWatch dashboard using #Terraform. We leveraged the power of #infrastructure-as-code to define the dashboard #configuration and #automate its #deployment. With the CloudWatch dashboard in place, you can easily monitor the key metrics of your #Lambda functions, such as# invocations, errors, duration, and more.