VM Deployment
Introduction
The following provides the basic information to deploy a VM with Terraform on the TFGrid.
Template
terraform {
required_providers {
grid = {
source = "threefoldtech/grid"
version = "1.8.1-dev"
}
}
}
provider "grid" {
mnemonic = "FROM THE CREATE TWIN STEP"
network = "dev" # or test to use testnet
}
locals {
name = "testvm"
}
resource "grid_scheduler" "sched" {
requests {
name = "node1"
cru = 3
sru = 1024
mru = 2048
node_exclude = [33] # exlude node 33 from your search
public_ips_count = 0 # this deployment needs 0 public ips
public_config = false # this node does not need to have public config
}
}
resource "grid_network" "net1" {
name = local.name
nodes = [grid_scheduler.sched.nodes["node1"]]
ip_range = "10.1.0.0/16"
description = "newer network"
}
resource "grid_deployment" "d1" {
name = local.name
node = grid_scheduler.sched.nodes["node1"]
network_name = grid_network.net1.name
vms {
name = "vm1"
flist = "https://hub.grid.tf/tf-official-apps/base:latest.flist"
cpu = 2
memory = 1024
entrypoint = "/sbin/zinit init"
env_vars = {
SSH_KEY = file("~/.ssh/id_rsa.pub")
}
planetary = true
}
vms {
name = "anothervm"
flist = "https://hub.grid.tf/tf-official-apps/base:latest.flist"
cpu = 1
memory = 1024
entrypoint = "/sbin/zinit init"
env_vars = {
SSH_KEY = file("~/.ssh/id_rsa.pub")
}
planetary = true
}
}
output "vm1_ip" {
value = grid_deployment.d1.vms[0].ip
}
output "vm1_planetary_ip" {
value = grid_deployment.d1.vms[0].planetary_ip
}
output "vm2_ip" {
value = grid_deployment.d1.vms[1].ip
}
output "vm2_planetary_ip" {
value = grid_deployment.d1.vms[1].planetary_ip
}
Using scheduler
- If the user decided to choose scheduler to find a node for him, then he will use the node returned from the scheduler as the example above
Using Grid Explorer
- If not, the user can still specify the node directly if he wants using the grid explorer to find a node that matches his requirements
Describing the overlay network for the project
resource "grid_network" "net1" {
nodes = [grid_scheduler.sched.nodes["node1"]]
ip_range = "10.1.0.0/16"
name = "network"
description = "some network"
add_wg_access = true
}
We tell terraform we will have a network one node having the node ID returned from the scheduler
using the IP Range 10.1.0.0/16
and add wireguard access for this network
Describing the deployment
resource "grid_deployment" "d1" {
name = local.name
node = grid_scheduler.sched.nodes["node1"]
network_name = grid_network.net1.name
vms {
name = "vm1"
flist = "https://hub.grid.tf/tf-official-apps/base:latest.flist"
cpu = 2
memory = 1024
entrypoint = "/sbin/zinit init"
env_vars = {
SSH_KEY = file("~/.ssh/id_rsa.pub")
}
planetary = true
}
vms {
name = "anothervm"
flist = "https://hub.grid.tf/tf-official-apps/base:latest.flist"
cpu = 1
memory = 1024
entrypoint = "/sbin/zinit init"
env_vars = {
SSH_KEY = file("~/.ssh/id_rsa.pub")
}
planetary = true
}
}
It's bit long for sure but let's try to dissect it a bit
node = grid_scheduler.sched.nodes["node1"]
network_name = grid_network.net1.name
ip_range = lookup(grid_network.net1.nodes_ip_range, 2, "")
node = grid_scheduler.sched.nodes["node1"]
means this deployment will happen on node returned from the scheduler. Otherwise the user can specify the node asnode = 2
and in this case the choice of the node is completely up to the user at this point. They need to do the capacity planning. Check the Node Finder to know which nodes fits your deployment criteria.network_name
which network to deploy our project on, and here we choose thename
of networknet1
ip_range
here we lookup the iprange of node2
and initially load it with""
Advannced note: Direct map access fails during the planning if the key doesn't exist which happens in cases like adding a node to the network and a new deployment on this node. So it's replaced with this to make a default empty value to pass the planning validation and it's validated anyway inside the plugin.
Which flists to use
see list of flists
Remark multiple VMs
in terraform you can define items of a list like the following
listname {
}
listname {
}
So to add a VM
vms {
name = "vm1"
flist = "https://hub.grid.tf/tf-official-apps/base:latest.flist"
cpu = 1
publicip = true
memory = 1024
entrypoint = "/sbin/zinit init"
env_vars = {
SSH_KEY ="ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQCeq1MFCQOv3OCLO1HxdQl8V0CxAwt5AzdsNOL91wmHiG9ocgnq2yipv7qz+uCS0AdyOSzB9umyLcOZl2apnuyzSOd+2k6Cj9ipkgVx4nx4q5W1xt4MWIwKPfbfBA9gDMVpaGYpT6ZEv2ykFPnjG0obXzIjAaOsRthawuEF8bPZku1yi83SDtpU7I0pLOl3oifuwPpXTAVkK6GabSfbCJQWBDSYXXM20eRcAhIMmt79zo78FNItHmWpfPxPTWlYW02f7vVxTN/LUeRFoaNXXY+cuPxmcmXp912kW0vhK9IvWXqGAEuSycUOwync/yj+8f7dRU7upFGqd6bXUh67iMl7 ahmed@ahmedheaven"
}
}
- We give it a name within our deployment
vm1
flist
is used to define the flist to run within the VM. Check the list of flistscpu
andmemory
are used to define the cpu and memorypublicip
is usued to define if it requires a public IP or notentrypoint
is used define the entrypoint which in most of the cases in/sbin/zinit init
, but in case of flists based on vms it can be specific to each flistenv_vars
are used to define te environment variables, in this example we defineSSH_KEY
to authorize me accessing the machine Here we say we will have this deployment on node withtwin ID 2
using the overlay network defined from beforegrid_network.net1.name
and use the ip range allocated to that specific node2
The file describes only the desired state which is a deployment of two VMs and their specifications in terms of cpu and memory, and some environment variables e.g sshkey to ssh into the machine
Reference
A complete list of VM workload parameters can be found here.
terraform {
required_providers {
grid = {
source = "threefoldtech/grid"
}
}
}
provider "grid" {
}
resource "grid_network" "net1" {
nodes = [8]
ip_range = "10.1.0.0/16"
name = "network"
description = "newer network"
add_wg_access = true
}
resource "grid_deployment" "d1" {
node = 8
network_name = grid_network.net1.name
ip_range = lookup(grid_network.net1.nodes_ip_range, 8, "")
vms {
name = "vm1"
flist = "https://hub.grid.tf/tf-official-apps/base:latest.flist"
cpu = 2
publicip = true
memory = 1024
entrypoint = "/sbin/zinit init"
env_vars = {
SSH_KEY = "ssh-rsa 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 omar@omar-Predator-PT315-52"
}
planetary = true
}
vms {
name = "anothervm"
flist = "https://hub.grid.tf/tf-official-apps/base:latest.flist"
cpu = 1
memory = 1024
entrypoint = "/sbin/zinit init"
env_vars = {
SSH_KEY = "ssh-rsa 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 omar@omar-Predator-PT315-52"
}
}
}
output "wg_config" {
value = grid_network.net1.access_wg_config
}
output "node1_zmachine1_ip" {
value = grid_deployment.d1.vms[0].ip
}
output "node1_zmachine2_ip" {
value = grid_deployment.d1.vms[1].ip
}
output "public_ip" {
value = grid_deployment.d1.vms[0].computedip
}
output "planetary_ip" {
value = grid_deployment.d1.vms[0].planetary_ip
}