Showing posts with label Google Cloud. Show all posts
Showing posts with label Google Cloud. Show all posts

Sunday, April 14, 2024

Veeam Backup & Replication Architecture for Disaster Recovery in Google Cloud

In the following article we look at a DR architecture for Veeam Backup & Replication using Google Cloud as a disaster recovery location and implementing read only access to shared backup repository. 

Having a disaster recovery (DR) plan is not a nice to have, but a core requirement for any business that wants to survive a crisis situation. For any disaster recovery plan we need a secondary location where to restart the services. This secondary location can actually be a public cloud service provider. Veeam Backup & Replication enables recovery of virtual machines backups and agent based backups directly to the cloud. 

We propose to implement a solution with two backup servers (VBR) accessing the same backup data. We deploy one backup server on premises (ON PREM VBR in the following diagram). It acts as our operational server managing backups, backup copy jobs and restores. The second backup server (DR VBR) is deployed in Google Cloud (GCE). It acts as our DR backup server. For the most of the time it will not be used. It becomes active during testing or during a real DR situation. 


On premises VBR is configured to write backups to a local repository. A backup copy job creates a copy of the primary backups to a Google Cloud Storage repository. To write data to the Cloud Storage repository, the on premises VBR will use a HMAC key associated with a service account that has read/write permissions to that bucket. Since we do not plan to use on premises VBR to restore to Google Cloud, these are the only permissions that it needs. It also needs to be the only VBR that has write permission to that bucket. 

The DR VBR is deployed on a GCE VM in backup project. We are using a separate projects to host the backup infrastructure. It uses a service account with read only permissions to Cloud Storage to access data copied by the on premises VBR. Using the read only account we make sure that there will be no incompatibility or data corruption at the repository level. 

Since the cloud VBR is used to recover VMs in case of a DR situation, it needs an additional service account with restore to GCE permissions (listed here). The service account is configured in the project where we will restore the VMs (production project) and added to VBR using service account key. 

The proposed implementation can be further adapted for other scenarios such as sending backups directly to cloud or even cloud only environments.

By using the proposed architecture, we implement 3-2-1 rule and enable fast and secure restores in case of a disaster while keeping flexibility, low costs and RTO/RPO for on premises restores.


Sunday, July 9, 2023

Veeam Backup for Google Cloud - Zero Trust Architecture with Cloud Identity-Aware Proxy

Having security embedded by design into your architecture is more than just a best practice. It is how any one should actually start their work in any kind of project in public, private or hybrid cloud. Veeam Backup for Google Cloud (VBG) is one of the technologies that enables data security and resiliency by backing up and protecting your data running in the cloud. However, VBG is also residing in the same cloud and one of the first things is to make sure it is deployed and accessed in a secure manner. 

The challenge rises from the need to access VBG console for configuration and operation activities. The focus of this post is securing this access. 

In a standard deployment you would have your VBG appliance installed in a VPC, apply firewall rules to restrict access to VBG and then using an SSL encrypted web browser connect to the console. This connectivity can be done over Internet or in some more complex scenarios over VPN or interconnect links.  If you are connecting to VBG over Internet, you would need to expose VBG using a public IP address and restrict access to that IP address from your source IP. This is the use case that we are treating in our article. Another scenario using bastion servers and private connectivity is not treated now, however principals and mechanisms learned here can still apply. 


As you can easily see there are some disadvantages in the having VBG directly accessed from Internet. First, VBG is directly accessed from Internet. Having a firewall rule that limits source IP addresses allowed to connect to the external IP address of VBG increases the security trust, but it does not apply zero trust principles. We don't know who is hiding behind that allowed source IP address. There is no user identification and authorization in place before allowing the user to open a session to VBG console. Anyone connecting from that specific source IP address is automatically trusted.

How can we make sure that whoever or whatever trying to connect to VBG is actually allowed to do it? Please mind that we are talking about the connection to VBG console before any authentication and authorization into VBG is applied. We want to make sure that whoever tries to enter credentials in VBG console is identified and has the permissions to do that action. 

Think of use cases where your user has lost his rights to manage backups, however still has access to the backup infrastructure. You would want to have a secure and simple way of controlling that access and being able to easily revoke it. In this situation we can use Cloud Identity and Access Management (IAP) and Cloud Identity-Aware Proxy (IAP).

How does it work?

Cloud IAP implements TCP forwarding which encrypts any type of TCP traffic between the client initiating the session and IAP using HTTPS. In our case we normally connect to VBG console using HTTPS (web browser). Adding IAP TCP forwarding, the initial HTTPS traffic will be encrypted in another HTTPS connection. From IAP to VBG, the traffic will be sent without the additional layer of encryption. The purpose of using IAP is to keep VBG connected to private networks only and control which users can actually connect by using permissions and IAM users. 

Public IP of VBG will be removed and if outbound connectivity is needed, then use a NAT gateway to enable it, but this is out of scope for the current post.

To summarize, instead of allowing anyone behind an IP address to connect to our VBG portal, we restrict this connectivity to specific IAM users. Additionally we keep VBG on a private network.

Guide

Start by preparing the project: enable Cloud Identity-Aware Proxy API. In the console 

  • APIs & Services > Enable APIs and Services 
  • search for Cloud Identity-Aware Proxy API  and press enable.
Once enabled you will see it displayed in the list APIs


Allow IAP to connect to your VM by creating a firewall rule. In console go to VPC network > Firewall and press Create Firewall Rule
  • name: allow-ingress-from-iap
  • targets: Specifed target tags and select the tag of your VBG instance. We are using "vbg-europe" network tag. If you don't use network tags you can select "All instances in the network"
  • source IPv4 ranges: Add the range 35.235.240.0/20 which contains all IP addresses that IAP uses for TCP forwarding.
  • protocols and ports - specify the port you want to access - TCP 443
  • press Save


Grant to users (or groups) permissions to use IAP TCP forwarding and specify to which instance to make it as restrictive as possible. Grant the roles/iap.tunnelResourceAccessor role to VBG instance by opening IAP admin page in console (Security > Identity-Aware Proxy). Go to SSH and TCP Resources page (you may ignore the OAuth warning).


Select your VBG instance and press Add principal. Give to the IAM principal IAP-Secured Tunnel User role. You may want to restrict access to VBG to specific periods of time or days of the week. In this case add an IAM time based condition as seen in the example below.

Save the configuration and now you are ready to connect to your isolated VBG instance. On the machine where you want to initialize the connection you would need to have gcloud cli installed (Cloud SDK). Run the following command to open a TCP forwarding tunnel to VBG instance on port 443.

gcloud compute start-iap-tunnel  your-vbg-instance-name 443 --local-host-port=localhost:0  --zone=your-instance-zone

When the tunnel is established you will see a message in the console with the local TCP port that is used for forwarding, similar to below image:

To be able to execute gcloud compute start-iap-tunnel you need to have compute.instances.get and compute.instances.list permissions on the project where VBG instance runs. You may grant the permissions to the users or groups using a custom role.

In case the user is not authorized in IAP or an IAM condition applied, then you will get the following message when trying to start the tunnel:


Finally it's time to open your browser, point it to the localhost and TCP port returned by gcloud command and connect to your VBG instance in the cloud: 

The proposed solution is suitable for management and operations of VBG. However, please keep in mind that IAP TCP forwarding is not intended for bulk data data transfer. Also, IAP automatically disconnects sessions after one hour of inactivity. 

In this post we've seen how to use Cloud IAP and Cloud IAM to enable secure access to Veeam Backup for Google Cloud console using zero trust architecture principals.

Sunday, April 23, 2023

A Quick Look At Terraform Provider for Ansible

Terraform Provider for Ansible v1.0.0 has been release recently and while reading a couple of articles about it I actually wanted to see how it work end to end. 

We're going to look in this article at an use case where we provision cloud infrastructure with Terraform and then use Ansible to configure that infrastructure.

To be more specific, in our scenario we are looking at achieving the following

1. use Terraform to deploy an infrastructure in Google Cloud: VPC, VM instance with an external IP address and firewall rule to allow access to the instance 

2. automatically and transparently update Ansible inventory file 

3. automatically configure the newly provisioned VM instance with Ansible  


We use Terraform provider for Ansible and Ansible Terraform collection. From the collection we will be using the inventory plugin. Everything is run from a management machine installed with Terraform, Ansible and the Ansible collection (for installation please see the GitHub project linked above).

We will orchestrate everything from Terraform. We'll use Ansible provider to place the newly created VM instance to a specific Ansible group called "nginx_hosts" and execute Ansible commands to update the inventory and run the playbook that installs nginx. 

For simplicity we use a flat structure with a single Terraform configuration file, an Ansible inventory file and an Ansible playbook. 


We start by looking at the Ansible files.

inventory.yml contains only one line that references the collection inventory plugin:

plugin: cloud.terraform.terraform_provider

This way we make sure the inventory file is actually created dynamically based on the Terraform state file. 

nginx_install.yml is the playbook that installs nginx on the VM instance. It's a very simple playbook that checks the latest version is installed and that it is started. We will be using Ubuntu for our Linux distribution. 

---
- hosts: nginx_hosts
  tasks:
    - name: ensure nginx is at the latest version
      apt: name=nginx state=latest update_cache=true
      become: true
    - name: start nginx
      service:
          name: nginx
          state: started

Based on the code written so far, if we add any host to the group named "nginx_hosts" running the playbook will ensure latest version of nginx is installed. We have no knowledge of IP addresses or the hostnames of those hosts. We actually have no idea if there are any hosts in the group. 


The Ansible hosts that we want to configure are created using Terraform. For simplicity there is only one flat file - main.tf file. We start by defining the Ansible provider.

terraform {
  required_providers {
    ansible = {
      source  = "ansible/ansible"
      version = "1.0.0"
    }
  }
}

Next we define the variables. We are using Google Cloud provider and we need some variables to configure it and deploy the resources. We are using a user_id to generate unique resource name for each deployment. We add GCP provider variables (region, AZ, project) and variables for the network.

variable "user_id" {
  type = string
  description = "unique id used to create resources"  
  default = "tfansible001"
}

variable "gcp_region" {
  type = string
  description = "Google Cloud region where to deploy the resources"  
  default = "europe-west4"
}

variable "gcp_zone" {
  type = string
  description = "Google Cloud availability zone where to deploy resources"  
  default = "europe-west4-a"
}

variable "gcp_project" {
  type = string
  description = "Google Cloud project name where to deploy resources" 
  default = "your-project"
}

variable "networks" {
  description = "list of VPC names and subnets"
  type        = map(any)
  default = {
    web = "192.168.0.1/24"
  }
}

variable "fwl_allowed_tcp_ports" {
  type        = map(any)
  description = "list of firewall ports to open for each VPC"
  default = {
    web = ["22", "80", "443"]
  }
}

We need also variables for Ansible provider resources: ansible user that can connect and configure the instance, the path the the ssh key file and the path to python executable. In case you use just want to test this, you can use your Google Cloud user. 

variable "ansible_user" {
  type = string
  description = "Ansible user used to connect to the instance"
  default = "ansible_user"
}

variable "ansible_ssh_key" {
  type = string
  description = "ssh key file to use for ansible_user"
  default = "path_to_ssh_key_for_ansible_user"
}

variable "ansible_python" {
  type = string
  description = "path to python executable"
  default = "/usr/bin/python3"
}

Then we configure the Google Cloud provider. Note that in Terraform it is not mandatory to define a provider with requried_provider block. Also note that for Ansible provider there is no configuration. 

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


Time to create the resources. We start with the VPC, subnet and firewall rules. The code iterates through the map object defined in variables section:

resource "google_compute_network" "main" {
  for_each                = var.networks
  name                    = "vpc-${each.key}-${var.user_id}"
  auto_create_subnetworks = "false"
}

resource "google_compute_subnetwork" "main" {
  for_each                 = var.networks
  name                     = "subnet-${each.key}-${var.user_id}"
  ip_cidr_range            = each.value
  network                  = google_compute_network.main[each.key].id
  private_ip_google_access = "true"
}

resource "google_compute_firewall" "allow" {
  for_each = var.fwl_allowed_tcp_ports
  name     = "allow-${each.key}"
  network  = google_compute_network.main[each.key].name

  allow {
    protocol = "tcp"
    ports    = each.value
  }

  source_ranges = ["0.0.0.0/0"]

  depends_on = [
    google_compute_network.main
  ]
}

Then we deploy the VM instance and we inject the ssh key using VM metadata. Again, ansible_user could be your Google user if you are using this for a quick test.

resource "google_compute_instance" "web" {
  name         = "web-vm-${var.user_id}"
  machine_type = "e2-medium"

  boot_disk {
    initialize_params {
      image = "projects/ubuntu-os-cloud/global/images/ubuntu-2210-kinetic-amd64-v20230125"
    }
  }

  network_interface {
    network    = google_compute_network.main["web"].self_link
    subnetwork = google_compute_subnetwork.main["web"].self_link
    access_config {}
  }

  metadata = {
    "ssh-keys" = <<EOT
      ansible_user:ssh-rsa AAAAB3NzaC1y...
     EOT
  }

}


So far we have the infrastructure deployed. We now need to configure the VM instance. We will configure a resource of type ansible_host. The resource will be used to dynamically update the Ansible inventory. 

resource "time_sleep" "wait_20_seconds" {
  depends_on      = [google_compute_instance.web]
  create_duration = "20s"
}

resource "ansible_host" "gcp_instance" {
  name   = google_compute_instance.web.network_interface.0.access_config.0.nat_ip
  groups = ["nginx_hosts"]
  variables = {
    ansible_user                 = "${var.ansible_user}",
    ansible_ssh_private_key_file = "${var.ansible_ssh_key}",
    ansible_python_interpreter   = "${var.ansible_python}"
  }

  depends_on = [time_sleep.wait_20_seconds]
}

We've added a sleep time to make sure the VM instance is powered on and services are running. Please note that we add the public IP of the VM instance, whatever that is, as the host name in Ansible. The host is added to "nginx_hosts" group. We also let Ansible know what user, ssh key and python version to use. 

Last thing to do is to update Ansible inventory and run the playbook. We will use terraform_data resources to execute Ansible command line.

resource "terraform_data" "ansible_inventory" {
  provisioner "local-exec" {
    command = "ansible-inventory -i inventory.yml --graph --vars"
  }
  depends_on = [ansible_host.gcp_instance]
}

resource "terraform_data" "ansible_playbook" {
  provisioner "local-exec" {
    command = "ansible-playbook -i inventory.yml nginx_install.yml"
  }
  depends_on = [terraform_data.ansible_inventory]
}

And that's it. Once you update the code above with your information and run terraform apply, it will automatically deploy a Google Cloud VM instance and configure it with Ansible. All transparent and dynamic, all driven from Terraform. 

In this article you've seen how to use Terraform to deploy a cloud VM instance and automatically and transparently configure it with Ansible.