GCP Setup

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Introduction

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Prerequisites

1. Terraform installed.
2. Google Cloud SDK (gcloud) configured with your GCP account.
3. Pre-existing GCP resources:
   • VPC Network
   • Private subnets
   • GKE cluster
   • Subnet groups for Cloud SQL and Memorystore
   • Access to the Cloud Run service’s container image hosted by Raven

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Step-by-Step Guide

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1. Clone the Repository

git clone https://gitlab.com/Raven-IO/gcp-terraform-example.git
cd gcp-terraform-example

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2. Configure Backend

terraform {
  backend "gcs" {
    bucket = "your-terraform-state-bucket"
    prefix = "raven/terraform.tfstate"
  }
}

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3. Configure GCP Provider

provider "google" {
  project = var.gcp_project
  region  = var.gcp_region
}

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4. Initialize Terraform

terraform init

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5. Review and Modify Variables

variable "gcp_project" {
  description = "The GCP project ID to deploy resources."
  type        = string
}

variable "gcp_region" {
  description = "The GCP region to deploy resources."
  default     = "us-central1"
}

variable "private_subnets" {
  type        = list(string)
  description = "The private subnets to deploy the Compute Engine instance."
}

variable "vpc_id" {
  type        = string
  description = "The VPC ID to deploy the resources."
}

variable "additional_labels" {
  default = {
    "terraform" = "true"
  }
  description = "Additional labels to attach to the resources."
}

variable "memorystore_subnet_name" {
  type        = string
  description = "The name of the Memorystore subnet to use for the Redis instance."
}

variable "allowed_cidr_blocks" {
  type        = list(string)
  description = "The CIDR blocks that are allowed to access the Cloud SQL (Postgres) / Memorystore (Redis) / Compute Engine (ClickHouse) instance."
}

variable "allowed_service_accounts" {
  type        = list(string)
  description = "The service accounts that are allowed to access the Cloud SQL (Postgres) / Memorystore (Redis) instance."
}

variable "cloud_sql_subnet_name" {
  type        = string
  description = "The name of the Cloud SQL subnet to use for the Postgres instance."
}

variable "container_image_uri" {
  type        = string
  description = "The URI of the container image to use for the Cloud Run service | Your GCP project should have access to this image."
}

variable "prefix" {
  type        = string
  description = "The prefix to use for the resources."
}

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6. Plan the Deployment

terraform plan

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7. Apply the Terraform Configuration

terraform apply

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Terraform Configuration Details

• Compute Engine Instances: The configuration includes setting up Compute Engine instances with appropriate IAM roles and security settings.
  • Defined in compute.tf, the script provisions Compute Engine instances, attaches IAM roles, and configures firewall rules to allow necessary traffic.
  • We use Bitnami official image to deploy ClickHouse. You can change this in the clickhouse.tf file.
• Memorystore for Redis: Managed Redis instances using Memorystore.
  • Found in memorystore.tf, it sets up Redis with specified node types and cluster settings, ensuring proper subnet and security group configurations.
  • This module exports redis_host and redis_port which will then be passed to the Cloud Run service as environment variables.
• Cloud SQL (PostgreSQL): Provisions a managed database instance.
  • The cloudsql.tf file includes configurations for instance type, storage, and security groups, tailored to meet the requirements of the SaaS product.
• Cloud Run: Sets up Cloud Run services triggered by Cloud Storage events.
  • In cloudrun.tf, the configuration includes creating Cloud Run services, assigning IAM roles, and setting up Cloud Storage event triggers.
  • This module exports the following outputs:
    • cloudrun_service_url which will be used to configure Cloud Storage bucket to send events to the Cloud Run service.
    • cloudrun_service_account which will be used to allow the Cloud Run service to access the Memorystore/Redis database.

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Post Deployment

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Clean Up

terraform destroy