(4) GCP Cloud function 모듈로 관리하기

Cloud function을 모듈로 만들어 관리하는 방법에 대해 기술한다.

 

1.cloud_functions.tf

cloud function 소스 코드 저장하는 버킷을 생성하고 cloud function 모듈을 만들어 추가해준다.

참고할 점은 functions_version이라는 변수를 주어 1st, 2nd 버전을 구분하도록 설정하였다.

#clouid function 소스 코드 저장 버킷

resource "google_storage_bucket" "function_bucket" {

  name = "function-bucket-hr"

  location = "ASIA"

  project = "pjt-an3-dev-vm-2"

  force_destroy = false

}

# function_version으로  버전 구분 (1st , 2nd)

module "my_cloud_function" {

  source = "./modules/cloud_function"

  # 소스 코드 저장  zip 파일로 저장

  object_name = "test/function.zip"

  bucket_name           = google_storage_bucket.function_bucket.name

  gcs_source ="./hello_http/hello_http.zip"

  function_version = 1

  function_name          = "my-function2"

  description            = "My Cloud Function"

  runtime                = "python39"

  entry_point            = "hello_http"

  timeout                = 60

  region                 = "asia-northeast3"

  project                = "pjt-an3-dev-vm-2"

 

  trigger_http           = true

  available_memory_mb    = 256

  environment_variables  = {

    EXAMPLE_KEY = "example-value"

  }

  service_account_email  = module.svcacc_test_account_2.service_account_email

}

 

 

cloud_function 모듈 정보

 

1) main.tf

google_storage_bucket_object 리소스를 통해 버킷에 로컬에 있는 소스 파일을 업로드한다.

count를 통해 functions_version이 1 혹은 2일 경우 해당 리소스를 생성하도록 설정한다.

resource "google_storage_bucket_object" "archive" {

  name   = var.object_name

  bucket = var.bucket_name

  source = var.gcs_source

}

resource "google_cloudfunctions_function" "function_1st_gen" {

  count       = var.function_version == 1 ? 1 : 0

  name        = var.function_name

  description = var.description

  runtime     = var.runtime

  entry_point = var.entry_point

  timeout     = var.timeout

  region      = var.region

  project     = var.project

  source_archive_bucket = var.bucket_name

  source_archive_object = var.object_name

  trigger_http = var.trigger_http

  available_memory_mb = var.available_memory_mb

  environment_variables = var.environment_variables

  service_account_email = var.service_account_email

}

resource "google_cloudfunctions2_function" "function_2nd_gen" {

  count       = var.function_version == 2 ? 1 : 0

  name        = var.function_name

  location    = var.region

  description = var.description

  project     = var.project

  build_config {

    runtime     = var.runtime

    entry_point = var.entry_point

    source {

      storage_source {

        bucket = var.bucket_name

        object = var.object_name

      }

    }

  }

  service_config {

    max_instance_count = 1

    available_memory   = var.available_memory_mb

    timeout_seconds    = var.timeout

    environment_variables = var.environment_variables

    service_account_email = var.service_account_email

  }

}

2) output

3) variables.tf

function_version 변수에 validation 설정을 통해 1,2 값만 전달되도록 설정했다.

variable "function_version" {

  description = "Cloud Function version (1 or 2)"

  default     = 1

  validation {

    condition     = var.function_version == 1 || var.function_version == 2

    error_message = "Version must be either 1 or 2"

  }

}

variable "object_name" {

  description = "Name of the GCS object_name"

}

variable "gcs_source" {

  description = "Name of the GCS source"

}

variable "function_name" {

  description = "Name of the Cloud Function"

}

variable "description" {

  description = "Description of the Cloud Function"

}

variable "runtime" {

  description = "Runtime of the Cloud Function"

}

variable "entry_point" {

  description = "Entry point of the Cloud Function"

}

variable "timeout" {

  description = "Timeout for the Cloud Function execution"

}

variable "region" {

  description = "Region for the Cloud Function deployment"

}

variable "project" {

  description = "Project ID where the Cloud Function will be deployed"

}

variable "bucket_name" {

  description = "Name of the Cloud Storage bucket containing the Cloud Function code"

}

 

variable "trigger_http" {

  description = "Whether the Cloud Function should be triggered by HTTP requests"

}

variable "available_memory_mb" {

  description = "Available memory for the Cloud Function execution"

}

variable "environment_variables" {

  description = "Environment variables for the Cloud Function"

  type        = map(string)

}

variable "service_account_email" {

  description = "Email address of the service account associated with the Cloud Function"

}

 

 

2. GCP 콘솔에서 생성 확인

 

GCS 

 

Cloud function