A padlock and chain on a rusted gate

Using #NetworkFirewall and #Route53 #DNS #Firewall to protect a private subnet’s egress traffic in #AWS

I wrote this post in January 2023, and it’s been languishing in my Drafts folder since then. I’ve had a look through it, and I can’t see any glaring reasons why I didn’t publish it so… it’s published… Enjoy 😁

If you’ve ever built a private subnet in AWS, you know it can be a bit tricky to get updates from the Internet – you end up having a NAT gateway or a self-managed proxy, and you can never be 100% certain that the egress traffic isn’t going somewhere you don’t want it to.

In this case, I wanted to ensure that outbound HTTPS traffic was being blocked if the SNI didn’t explicitly show the DNS name I wanted to permit through, and also, I only wanted specific DNS names to resolve. To do this, I used AWS Network Firewall and Route 53 DNS Firewall.

I’ve written this blog post, and followed along with this, I’ve created a set of terraform files to represent the steps I’ve taken.

The Setup

Let’s start this story from a simple VPC with three private subnets for my compute resources, and three private subnets for the VPC Endpoints for Systems Manager (SSM).

Here’s our network diagram, with the three subnets containing the VPC Endpoints at the top, and the three instances at the bottom.

I’ve created a tag in my Github repo at this “pre-changes” state, called step 1.

At this point, none of those instances can reach anything outside the network, with the exception of the SSM environment. So, we can’t install any packages, we can’t get data from outside the network or anything similar.

Getting Protected Internet Access

In order to get internet access, we need to add 4 things;

  1. An internet gateway
  2. A NAT gateway in each AZ
  3. Which needs three new subnets
  4. And three Elastic IP addresses
  5. Route tables in all the subnets

To clarify, a NAT gateway acts like a DSL router. It hides the source IP address of outbound traffic behind a single, public IP address (using an Elastic IP from AWS), and routes any return traffic back to wherever that traffic came from. To reduce inter-AZ data transfer rates, I’m putting one in each AZ, but if there’s not a lot of outbound traffic or the outbound traffic isn’t critical enough to require resiliency, this could all be centralised to a single NAT gateway. To put a NAT gateway in each AZ, you need a subnet in each AZ, and to get out to the internet (by whatever means you have), you need an internet gateway and route tables for how to reach the NAT and internet gateways.

We also should probably add, at this point, four additional things.

  1. The Network Firewall
  2. Subnets for the Firewall interfaces
  3. Stateless Policy
  4. Stateful Policy

The Network Firewall acts like a single appliance, and uses a Gateway Load Balancer to present an interface into each of the availability zones. It has a stateless policy (which is very fast, but needs to address both inbound and outbound traffic flows) to do IP and Port based filtering (referred to as “Layer 3” filtering) and then specific traffic can be passed into a stateful policy (which is slower) to do packet and flow inspection.

In this case, I only want outbound HTTPS traffic to be passed, so my stateless rule group is quite simple;

  • VPC range on any port β†’ Internet on TCP/443; pass to Stateful rule groups
  • Internet on TCP/443 β†’ VPC range on any port; pass to Stateful rule groups

I have two stateful rule groups, one is defined to just allow access out to example.com and any relevant subdomains, using the “Domain List” stateful policy item. The other allows access to example.org and any relevant subdomains, using a Suricata stateful policy item, to show the more flexible alternative route. (Suricata has lots more filters than just the SNI value, you can check for specific SSH versions, Kerberos CNAMEs, SNMP versions, etc. You can also add per-rule logging this way, which you can’t with the Domain List route).

These are added to the firewall policy, which also defines that if a rule doesn’t match a stateless rule group, or an established flow doesn’t match a stateful rule group, then it should be dropped.

New network diagram with more subnets and objects, but essentially, as described in the paragraphs above. Traffic flows from the instances either down towards the internet, or up towards the VPCe.

I’ve created a tag in my Github repo at this state, with the firewall, NAT Gateway and Internet Gateway, called step 2.

So far, so good… but why let our users even try to resolve the DNS name of a host they’re not permitted to reach. Let’s turn on DNS Firewalling too.

Turning on Route 53 DNS Firewall

You’ll notice that in the AWS Network Firewall, I didn’t let DNS out of the network. This is because, by default, AWS enables Route 53 as it’s local resolver. This lives on the “.2” address of the VPC, so in my example environment, this would be 198.18.0.2. Because it’s a local resolver, it won’t cross the Firewall exiting to the internet. You can also make Route 53 use your own DNS servers for specific DNS resolution (for example, if you’re running an Active Directory service inside your network).

Any Network Security Response team members you have working with you would appreciate it if you’d turn on DNS Logging at this point, so I’ll do it too!

In March 2021, AWS announced “Route 53 DNS Firewall”, which allow this DNS resolver to rewrite responses, or even to completely deny the existence of a DNS record. With this in mind, I’m going to add some custom DNS rules.

The first thing I want to do is to only permit traffic to my specific list of DNS names – example.org, example.com and their subdomains. DNS quite likes to terminate DNS names with a dot, signifying it shouldn’t try to resolve any higher up the chain, so I’m going to make a “permitted domains” DNS list;

example.com.
example.org.
*.example.com.
*.example.org.

Nice and simple! Except, this also stops me from being able to access the instances over SSM, so I’ll create a separate “VPCe” DNS list:

ssm.ex-ample-1.amazonaws.com.
*.ssm.ex-ample-1.amazonaws.com.
ssmmessages.ex-ample-1.amazonaws.com.
*.ssmmessages.ex-ample-1.amazonaws.com.
ec2messages.ex-ample-1.amazonaws.com.
*.ec2messages.ex-ample-1.amazonaws.com.

Next I create a “default deny” DNS list:

*.

And then build a DNS Firewall Policy which allows access to the “permitted domains”, “VPCe” lists, but blocks resolution of any “default deny” entries.

I’ve created a tag in my Github repo at this state, with the Route 53 DNS Firewall configured, called step 3.

In conclusion…

So there we have it. While the network is not “secure” (there’s still a few gaps here) it’s certainly MUCH more secure than it was, and it certainly would take a lot more work for anyone with malicious intent to get your content out.

Feel free to have a poke around, and leave comments below if this has helped or is of interest!

"Fishing fleet" by "Nomad Tales" on Flickr

Using Terraform to select multiple Instance Types for an Autoscaling Group in AWS

Tale as old as time, the compute instance type you want to use in AWS is highly contested (or worse yet, not as available in every availability zone in your region)! You plead with your TAM or AM “Please let us have more of that instance type” only to be told “well, we can put in a request, but… haven’t you thought about using a range of instance types”?

And yes, I’ve been on both sides of that conversation, sadly.

The commented terraform

# This is your legacy instance_type variable. Ideally we'd have
# a warning we could raise at this point, telling you not to use
# this variable, but... it's not ready yet.
variable "instance_type" {
  description = "The legacy single-instance size, e.g. t3.nano. Please migrate to instance_types ASAP. If you specify instance_types, this value will be ignored."
  type        = string
  default     = null
}

# This is your new instance_types value. If you don't already have
# some sort of legacy use of the instance_type variable, then don't
# bother with that variable or the locals block below!
variable "instance_types" {
  description = "A list of instance sizes, e.g. [t2.nano, t3.nano] and so on."
  type        = list(string)
  default     = null
}

# Use only this locals block (and the value further down) if you
# have some legacy autoscaling groups which might use individual
# instance_type sizes.
locals {
  # This means if var.instance_types is not defined, then use it,
  # otherwise create a new list with the single instance_type
  # value in it!
  instance_types = var.instance_types != null ? var.instance_types : [ var.instance_type ]
}

resource "aws_launch_template" "this" {
  # The prefix for the launch template name
  # default "my_autoscaling_group"
  name_prefix = var.name

  # The AMI to use. Calculated outside this process.
  image_id = data.aws_ami.this.id

  # This block ensures that any new instances are created
  # before deleting old ones.
  lifecycle {
    create_before_destroy = true
  }

  # This block defines the disk size of the root disk in GB
  block_device_mappings {
    device_name = data.aws_ami.centos.root_device_name
    ebs {
      volume_size = var.disksize # default "10"
      volume_type = var.disktype # default "gp2"
    }
  }

  # Security Groups to assign to the instance. Alternatively
  # create a network_interfaces{} block with your
  # security_groups = [ var.security_group ] in it.
  vpc_security_group_ids = [ var.security_group ]

  # Any on-boot customizations to make.
  user_data = var.userdata
}

resource "aws_autoscaling_group" "this" {
  # The name of the Autoscaling Group in the Web UI
  # default "my_autoscaling_group"
  name = var.name

  # The list of subnets into which the ASG should be deployed.
  vpc_zone_identifier = var.private_subnets
  # The smallest and largest number of instances the ASG should scale between
  min_size            = var.min_rep
  max_size            = var.max_rep

  mixed_instances_policy {
    launch_template {
      # Use this template to launch all the instances
      launch_template_specification {
        launch_template_id = aws_launch_template.this.id
        version            = "$Latest"
      }

      # This loop can either use the calculated value "local.instance_types"
      # or, if you have no legacy use of this module, remove the locals{}
      # and the variable "instance_type" {} block above, and replace the
      # for_each and instance_type values (defined as "local.instance_types")
      # with "var.instance_types".
      #
      # Loop through the whole list of instance types and create a
      # set of "override" values (the values are defined in the content{}
      # block).
      dynamic "override" {
        for_each = local.instance_types
        content {
          instance_type = local.instance_types[override.key]
        }
      }
    }

    instances_distribution {
      # If we "enable spot", then make it 100% spot.
      on_demand_percentage_above_base_capacity = var.enable_spot ? 0 : 100
      spot_allocation_strategy                 = var.spot_allocation_strategy
      spot_max_price                           = "" # Empty string is "on-demand price"
    }
  }
}

So what is all this then?

This is two Terraform resources; an aws_launch_template and an aws_autoscaling_group. These two resources define what should be launched by the autoscaling group, and then the settings for the autoscaling group.

You will need to work out what instance types you want to use (e.g. “must have 16 cores and 32 GB RAM, have an x86_64 architecture and allow up to 15 Gigabit/second throughput”)

When might you use this pattern?

If you have been seeing messages like “There is no Spot capacity available that matches your request.” or “We currently do not have sufficient <size> capacity in the Availability Zone you requested.” then you need to consider diversifying the fleet that you’re requesting for your autoscaling group. To do that, you need to specify more instance types. To achieve this, I’d use the above code to replace (something like) one of the code samples below.

If you previously have had something like this:

resource "aws_launch_configuration" "this" {
  iam_instance_profile        = var.instance_profile_name
  image_id                    = data.aws_ami.this.id
  instance_type               = var.instance_type
  name_prefix                 = var.name
  security_groups             = [ var.security_group ]
  user_data_base64            = var.userdata
  spot_price                  = var.spot_price

  root_block_device {
    volume_size = var.disksize
  }

  lifecycle {
    create_before_destroy = true
  }
}

resource "aws_autoscaling_group" "this" {
  capacity_rebalance   = false
  launch_configuration = aws_launch_configuration.this.id
  max_size             = var.max_rep
  min_size             = var.min_rep
  name                 = var.name
  vpc_zone_identifier  = var.private_subnets
}

Or this:

resource "aws_launch_template" "this" {
  lifecycle {
    create_before_destroy = true
  }

  block_device_mappings {
    device_name = data.aws_ami.this.root_device_name
    ebs {
      volume_size = var.disksize
    }
  }

  iam_instance_profile {
    name = var.instance_profile_name
  }

  network_interfaces {
    associate_public_ip_address = true
    security_groups             = local.node_security_groups
  }

  image_id      = data.aws_ami.this.id
  name_prefix   = var.name
  instance_type = var.instance_type
  user_data     = var.userdata

  instance_market_options {
    market_type = "spot"
    spot_options {
      spot_instance_type = "one-time"
    }
  }

  metadata_options {
    http_tokens                 = var.imds == 1 ? "optional" : "required"
    http_endpoint               = "enabled"
    http_put_response_hop_limit = 1
  }
}

resource "aws_autoscaling_group" "this" {
  name                = var.name
  vpc_zone_identifier = var.private_subnets
  min_size            = var.min_rep
  max_size            = var.max_rep

  launch_template {
    id      = aws_launch_template.this.id
    version = "$Latest"
  }
}

Then this new method is a much better idea :) Even more so if you had two launch templates to support spot and non-spot instance types!

Hat-tip to former colleague Paul Moran who opened my eyes to defining your fleet of variable instance types, as well as to my former customer (deliberately unnamed) and my current employer who both stumbled into the same documentation issue. Without Paul’s advice with my prior customer’s issue I’d never have known what I was looking for this time around!

Featured image is β€œFishing fleet” by β€œNomad Tales” on Flickr and is released under a CC-BY-SA license.

A series of gold blocks, each crossed, and one of the lower blocks has engraved "Eduardo Nery 1995-1998 Aleluia - Secla"

Deploying the latest build of a template (machine) image with #Xen #Orchestrator

In my current role we are using Packer to build images on a Xen Orchestrator environment, use a CI/CD system to install that image into both a Xen Template and an AWS AMI, and then we use Terraform to use that image across our estate. The images we build with Packer have this stanza in it:

locals {
  timestamp = regex_replace(timestamp(), "[- TZ:]", "")
}
variable "artifact_name" {
  default = "SomeLinux-version.iso"
}
source "xenserver-iso" "this" {
  vm_name = "${var.artifact_name}-${local.timestamp}"
  # more config below
}

As a result, the built images include a timestamp.

When we use the AMI in Terraform, we can locate it with this code:

variable "ami_name" {
  default = "SomeLinux-version.iso-"
}

data "aws_ami" "this" {
  most_recent = true

  filter {
    name   = "name"
    values = [var.ami_name]
  }

  filter {
    name   = "virtualization-type"
    values = ["hvm"]
  }

  owners = [var.owner]
}

But, because Xen doesn’t track when a template is created, instead I needed to do something different. Enter get_xoa_template.sh.

#!/bin/bash
trap cleanup SIGINT SIGTERM EXIT
exit_message=""
set_exit=0
fail() {
[ -n "$1" ] && echo "$1" >&2
[ "$2" -gt 0 ] && exit $2
}
cleanup() {
trap – SIGINT SIGTERM EXIT
[ "$UNREGISTER" -eq 1 ] && [ "$STATE" == "signed_in" ] && xo-cli –unregister 2>&1
[ -n "$exit_message" ] && fail "$exit_message" $set_exit
}
log_debug() {
[ -n "$DEBUG" ] && echo "$1" >> "$DEBUG"
}
parse_params() {
UNREGISTER=1
DEBUG=""
while :; do
case "${1-}" in
-h | –help)
echo "usage: get_xoa_template.sh –template SomeTemplatePrefix" >&2
echo "" >&2
echo "Options:" >&2
echo " -t | –template MyTemplatePrefix = The template to look for (required)" >&2
echo " -s | –server ws://192.0.2.1 = Sign into Xen Orchestrator on 192.0.2.1" >&2
echo " [Default to using XOA_URL environment variable]" >&2
echo " -u | –user username@example.org = Sign into Xen Orchestrator using this username" >&2
echo " [Default to using XOA_USER environment variable]" >&2
echo " -p | –password hunter2 = Sign into Xen Orchestrator using this password" >&2
echo " [Default to using XOA_PASSWORD environment variable]" >&2
echo " -l | –pool MyXenPool1 = Use this pool when looking for the template." >&2
echo " [Omit to ignore]" >&2
echo " -x | –no-unregister = Don't log out from the XOA server once connected." >&2
echo " -d | –debug = Log output to /tmp/xocli_output" >&2
echo " -d | –debug /path/to/debug = Log output to the specified path" >&2
echo " –debug=/path/to/debug = Log output to the specified path" >&2
exit 255
;;
-s | –server)
XOA_URL="${2-}"
shift
;;
-u | –user)
XOA_USER="${2-}"
shift
;;
-p | –password)
XOA_PASSWORD="${2-}"
shift
;;
-l | –pool)
XOA_POOL="${2-}"
shift
;;
-t | –template)
TEMPLATE="${2-}"
shift
;;
-x | –no-unregister)
UNREGISTER=0
;;
-d | –debug)
DEBUG=/tmp/xocli_output
[ -n "${2-}" ] && [ "$(echo "${2-}" | cut -c1)" != "-" ] && DEBUG="${2-}" && shift
;;
–debug=*)
DEBUG="$(echo $1 | sed -E -e 's/^[^=]+=//')"
;;
*)
break
;;
esac
shift
done
}
sign_in() {
[ -z "$XOA_URL" ] || [ -z "$XOA_USER" ] || [ -z "$XOA_PASSWORD" ] && fail "Missing sign-in details" 1
log_debug "Logging in"
if [ -n "$DEBUG" ]
then
xo-cli –register –au "$XOA_URL" "$XOA_USER" "$XOA_PASSWORD" 2>&1 | tee -a "$DEBUG" | grep -q 'Successfully' || fail "Login failed" 2
else
xo-cli –register –au "$XOA_URL" "$XOA_USER" "$XOA_PASSWORD" 2>&1 | grep -q 'Successfully' || fail "Login failed" 2
fi
STATE="signed_in"
}
get_pool() {
[ -z "$XOA_POOL" ] && log_debug "No Pool" && return 0
log_debug "Getting Pool ID"
if [ -n "$DEBUG" ]
then
POOL_ID="\$pool=$(xo-cli –list-objects type=pool | jq -c -r ".[] | select(.name_label | match(\"${XOA_POOL}\")) | .uuid" | sort | tail -n 1 | tee -a "$DEBUG")"
else
POOL_ID="\$pool=$(xo-cli –list-objects type=pool | jq -c -r ".[] | select(.name_label | match(\"${XOA_POOL}\")) | .uuid" | sort | tail -n 1)"
fi
[ "$POOL_ID" == "\$pool=" ] && fail "Pool provided but no ID received" 3
}
get_template() {
log_debug "Getting template"
if [ -n "$DEBUG" ]
then
TEMPLATE_IS="$(xo-cli –list-objects type=VM-template "${POOL_ID-}" | jq -c ".[] | select(.name_label | match(\"${TEMPLATE}\")) | .name_label" | sort | tail -n 1 | tee -a "$DEBUG")"
else
TEMPLATE_IS="$(xo-cli –list-objects type=VM-template "${POOL_ID-}" | jq -c ".[] | select(.name_label | match(\"${TEMPLATE}\")) | .name_label" | sort | tail -n 1)"
fi
[ -z "$TEMPLATE_IS" ] && fail "Could not match this template" 4
if [ -n "$DEBUG" ]
then
echo "{\"is\": ${TEMPLATE_IS}}" | tee -a "$DEBUG"
else
echo "{\"is\": ${TEMPLATE_IS}}"
fi
}
[ -n "$(command -v xo-cli)" ] || fail "xo-cli is missing, and is a required dependency for this script. Please install it; \`sudo npm -g install xo-cli\`" 5
parse_params "$@"
if [ -n "$DEBUG" ]
then
rm -f "$DEBUG"
log_debug "Invoked: $(date)"
log_debug "Template: $TEMPLATE"
log_debug "Pool: $XOA_POOL"
fi
sign_in
get_pool
get_template

This script is invoked from your terraform like this:

variable "template_name" {
  default     = "SomeLinux-version.iso-"
  description = "A regex, partial or full string to match in the template name"
}

variable "poolname" {
  default = "MyPool"
}

data "external" "get_xoa_template" {
  program = [
    "/bin/bash", "${path.module}/get_xoa_template.sh",
    "--template", var.template_name,
    "--pool", var.poolname
  ]
}

data "xenorchestra_pool" "pool" {
  name_label = var.poolname
}

data "xenorchestra_template" "template" {
  name_label = data.external.get_xoa_template.result.is
  pool_id    = data.xenorchestra_pool.pool.id
}

And that’s how you do it. Oh, and if you need to pin to a specific version? Change the template_name value from the partial or regex version to the full version, like this:

variable "template_name" {
  # This assumes your image was minted at midnight on 1970-01-01
  default     = "SomeLinux-version.iso-19700101000000"
}

Featured image is β€œBarcelos and Braga-18” by β€œGraeme Churchard” on Flickr and is released under a CC-BY license.

"Sensitive Species" by "Rennett Stowe" on Flickr

HOWTO: Do DynDNS-style (DDNS) updates with Terraform (without leaking your credentials in the console)

For some of my projects, I run a Dynamic DNS server service attached to one of the less-standard DNS Names I own, and use that to connect to the web pages I’m spinning up. In a recent demo, I noticed that the terraform “changes” log where it shows what things are being updated showed the credentials I was using, because I was using “simple” authentication, like this:

data "http" "ddns_web" {
  url = "https://my.ddns.example.org/update?secret=${var.ddns_secret}&domain=web&addr=192.0.2.1"
}

variable "ddns_secret" {
  default = "bob"
}

For context, that would ask the DDNS service running at ddns.example.org to create a DNS record for web.ddns.example.org with an A record of 192.0.2.1.

While this is fine for my personal projects, any time this goes past, anyone who spots that update line would see the credentials I use for this service. Not great.

I had a quick look at the other options I had for authentication, and noticed that the DDNS server I’m running also supports the DynDNS update mechanism. In that case, we need to construct things a little differently!

data "http" "ddns_web" {
  url             = "https://my.ddns.example.org/nic/update?hostname=web&myip=192.0.2.1"
  request_headers = {
    Authorization = "Basic ${base64encode("user:${var.ddns_secret}")}"
  }
}

variable "ddns_secret" {
  type      = string
  sensitive = true
  default   = "bob"
}

So now, we change the URL to include the /nic/ path fragment, we use different names for the variables and we’re using Basic Authentication which is a request header. It’s a little frustrating that the http data source doesn’t also have a query type or a path constructor we could have used, but…

In this context the request header of “Authorization” is a string starting “Basic” but then with a Base64 encoded value of the username (which for this DDNS service, can be anything, so I’ve set it as the word “user”), then a colon and then the password. By setting the ddns_secret variable as being “sensitive”, if I use terraform console, and ask it for the value of data.http.ddns_web I get

> data.http.ddns_web
{
  "body" = <<-EOT
  good 192.0.2.1
  
  EOT
  "id" = "https://my.ddns.example.org/nic/update?hostname=web&myip=192.0.2.1"
  "request_headers" = tomap({
    "Authorization" = (sensitive)
  })
  "response_body" = <<-EOT
  good 192.0.2.1
  
  EOT
  "response_headers" = tomap({
    "Content-Length" = "18"
    "Content-Type" = "text/plain; charset=utf-8"
    "Date" = "Thu, 01 Jan 1970 00:00:00 UTC"
    "Server" = "nginx"
    "Strict-Transport-Security" = "max-age=31536000; includeSubDomains"
    "X-Content-Type-Options" = "nosniff"
    "X-Xss-Protection" = "1; mode=block"
  })
  "url" = "https://my.ddns.example.org/nic/update?hostname=web&myip=192.0.2.1"
}
>

Note that if your DDNS service has a particular username requirement, this can also be entered, in the same way, by changing the string “user” to something like ${var.ddns_user}.

Featured image is β€œSensitive Species” by β€œRennett Stowe” on Flickr and is released under a CC-BY license.

"2015_12_06_VisΓ©_135942" by "Norbert Schnitzler" on Flickr

Idea for Reusable “Custom Data” templates across multiple modules with Terraform

A few posts ago I wrote about building Windows virtual machines with Terraform, and a couple of days ago, “YoureInHell” on Twitter reached out and asked what advice I’d give about having several different terraform modules use the same basic build of custom data.

They’re trying to avoid putting the same template file into several repos (I suspect so that one team can manage the “custom-data”, “user-data” or “cloud-init” files, and another can manage the deployment terraform files), and asked if I had any suggestions.

I had three ideas.

Using a New Module

This was my initial thought; create a new module called something like “Standard Build File”, and this build file contains just the following terraform file, and a template file called “build.tmpl”.

variable "someKey" {
  default = "someVar"
}

variable "hostName" {
  default = "hostName"
}

variable "unsetVar" {}

output "template" {
  value = templatefile("build.tmpl",
    {
      someKey  = var.someKey
      hostName = var.hostName
      unsetVar = var.unsetVar
    }
  )
}

Now, in your calling module, you can do:

module "buildTemplate" {
  source   = "git::https://git.example.net/buildTemplate.git?ref=latestLive"
  # See https://www.terraform.io/docs/language/modules/sources.html
  #   for more details on how to specify the source of this module
  unsetVar = "Set To This String"
}

output "RenderedTemplate" {
  value = module.buildTemplate.template
}

And that means that you can use the module.buildTemplate.template anywhere you’d normally specify your templateFile, and get a consistent, yet customizable template (and note, because I specified a particular tag, you can use that to move to the “current latest” or “the version we released into live on YYYY-MM-DD” by using a tag, or a commit ref.)

Now, the downside to this is that you’ve now got a whole separate module for creating your instances that needs to be maintained. What are our other options?

Git Submodules for your template

I use Git Submodules a LOT for my code. It’s a bit easy to get into a state with them, particularly if you’re not great at keeping on top of them, but… if you are OK with them, you’d create a repo, again, let’s use “https://git.example.net/buildTemplate.git” as our git repo, and put your template in there. In your terraform git repo, you’d run this command: git submodule add https://git.example.net/buildTemplate.git and this would add a directory to your repo called “buildTemplate” that you can use your templatefile function in Terraform against (like this: templatefile("buildTemplate/build.tmpl", {someVar="var"})).

Now, this means that you’ve effectively got two git repos in one tree, and if any changes occur in your submodule repo, you’d need to do git checkout main ; git pull to get the latest updates from your main branch, and when you check it out initially on another machine, you’ll need to do git clone https://git.example.net/terraform --recurse-submodules to get the submodules populated at the same time.

A benefit to this is that because it’s “inline” with the rest of your tree, if you need to make any changes to this template, it’s clearly where it’s supposed to be in your tree, you just need to remember about the submodule when it comes to making PRs and suchforth.

How about that third idea?

Keep it simple, stupid 😁

Why bother with submodules, or modules from a git repo? Terraform can be quite easy to over complicate… so why not create all your terraform files in something like this structure:

project\build.tmpl
project\web_servers\main.tf
project\logic_servers\main.tf
project\database_servers\main.tf

And then in each of your terraform files (web_servers, logic_servers and database_servers) just reference the file in your project root, like this: templatefile("../build.tmpl", {someVar="var"})

The downside to this is that you can’t as easily farm off the control of that build script to another team, and they’d be making (change|pull|merge) requests against the same repo as you… but then again, isn’t that the idea for functional teams? πŸ˜ƒ

Featured image is β€œ2015_12_06_VisΓ©_135942” by β€œNorbert Schnitzler” on Flickr and is released under a CC-BY-SA license.

"pharmacy" by "Tim Evanson" on Flickr

AWX – The Gateway Drug to Ansible Tower

A love letter to Ansible Tower

I love Ansible… I mean, I really love Ansible. You can ask anyone, and they’ll tell you my first love is my wife, then my children… and then it’s Ansible.

OK, maybe it’s Open Source and then Ansible, but either way, Ansible is REALLY high up there.

But, while I love Ansible, I love what Ansible Tower brings to an environment. See, while you get to easily and quickly manage a fleet of machines with Ansible, Ansible Tower gives you the fine grained control over what you need to expose to your developers, your ops team, or even, in a fit of “what-did-you-just-do”-ness, your manager. (I should probably mention that Ansible Tower is actually part of a much larger portfolio of products, called Ansible Automation Platform, and there’s some hosted SaaS stuff that goes with it… but the bit I really want to talk about is Tower, so I’ll be talking about Tower and not Ansible Automation Platform. Sorry!)

Ansible Tower has a scheduling engine, so you can have a “Go” button, for deploying the latest software to your fleet, or just for the 11PM patching cycle. It has a credential store, so your teams can’t just quickly go and perform an undocumented quick fix on that “flaky” box – they need to do their changes via Ansible. And lastly, it has an inventory, so you can see that the last 5 jobs failed to deploy on that host, so maybe you’ve got a problem with it.

One thing that people don’t so much love to do, is to get a license to deploy Tower, particularly if they just want to quickly spin up a demonstration for some colleagues to show how much THEY love Ansible. And for those people, I present AWX.

The first hit is free

One of the glorious and beautiful things that RedHat did, when they bought Ansible, was to make the same assertion about the Ansible products that they make to the rest of their product line, which is… while they may sell a commercial product, underneath it will be an Open Source version of that product, and you can be part of developing and improving that version, to help improve the commercial product. Thus was released AWX.

Now, I hear the nay-sayers commenting, “but what if you have an issue with AWX at 2AM, how do you get support on that”… and to those people, I reply: “If you need support at 2AM for your box, AWX is not the tool for you – what you need is Tower.”… Um, I mean Ansible Automation Platform. However, Tower takes a bit more setting up than what I’d want to do for a quick demo, and it has a few more pre-requisites. ANYWAY, enough about dealing with the nay-sayers.

AWX is an application inside Docker containers. It’s split into three parts, the AWX Web container, which has the REST API. There’s also a PostgreSQL database inside there too, and one “Engine”, which is the separate container which gets playbooks from your version control system, asks for any dynamic inventories, and then runs those playbooks on your inventories.

I like running demos of Tower, using AWX, because it’s reasonably easy to get stood up, and it’s reasonably close to what Tower looks and behaves like (except for the logos)… and, well, it’s a good gateway to getting people interested in what Tower can do for them, without them having to pay (or spend time signing up for evaluation licenses) for the environment in the first place.

And what’s more, it can all be automated

Yes, folks, because AWX is just a set of docker containers (and an install script), and Ansible knows how to start Docker containers (and run an install script), I can add an Ansible playbook to my cloud-init script, Vagrantfile or, let’s face it, when things go really wrong, put it in a bash script for some poor keyboard jockey to install for you.

If you’re running a demo, and you don’t want to get a POC (proof of concept) or evaluation license for Ansible Tower, then the chances are you’re probably not running this on RedHat Enterprise Linux (RHEL) either. That’s OK, once you’ve sold the room on using Tower (by using AWX), you can sell them on using RHEL too. So, I’ll be focusing on using CentOS 8 instead. Partially because there’s a Vagrant box for CentOS 8, but also because I can also use CentOS 8 on AWS, where I can prove that the Ansible Script I’m putting into my Vagrantfile will also deploy nicely via Cloud-Init too. With a very small number of changes, this is likely to work on anything that runs Docker, so everything from Arch to Ubuntu… probably 😁

“OK then. How can you work this magic, eh?” I hear from the back of the room. OK, pipe down, nay-sayers.

First, install Ansible on your host. You just need to run dnf install -y ansible.

Next, you need to install Docker. This is a marked difference between AWX and Ansible Tower, as AWX is based on Docker, but Ansible Tower uses other magic to make it work. When you’re selling the benefits of Tower, note that it’s not a 1-for-1 match at this point, but it’s not a big issue. Fortunately, CentOS can install Docker Community edition quite easily. At this point, I’m swapping to using Ansible playbooks. At the end, I’ll drop a link to where you can get all this in one big blob… In fact, we’re likely to use it with our Cloud-Init deployment.

Aw yehr, here’s the good stuff

tasks:
- name: Update all packages
  dnf:
    name: "*"
    state: latest

- name: Add dependency for "yum config-manager"
  dnf:
    name: yum-utils
    state: present

- name: Add the Docker Repo
  shell: yum config-manager --add-repo https://download.docker.com/linux/centos/docker-ce.repo
  args:
    creates: /etc/yum.repos.d/docker-ce.repo
    warn: false

- name: Install Docker
  dnf:
    name:
    - docker-ce
    - docker-ce-cli
    - containerd.io
    state: present
  notify: Start Docker

That first stanza – update all packages? Well, that’s because containerd.io relies on a newer version of libseccomp, which hasn’t been built in the CentOS 8 Vagrantbox I’m using.

The next one? That ensures I can run yum config-manager to add a repo. I could use the copy module in Ansible to create the repo files so yum and/or dnf could use that instead, but… meh, this is a single line shell command.

And then we install the repo, and the docker-ce packages we require. We use the “notify” statement to trigger a handler call to start Docker, like this:

handlers:
- name: Start Docker
  systemd:
    name: docker
    state: started

Fab. We’ve got Docker. Now, let’s clone the AWX repo to our machine. Again, we’re doing this with Ansible, naturally :)

tasks:
- name: Clone AWX repo to local path
  git:
    repo: https://github.com/ansible/awx.git
    dest: /opt/awx

- name: Get latest AWX tag
  shell: |
    if [ $(git status -s | wc -l) -gt 0 ]
    then
      git stash >/dev/null 2>&1
    fi
    git fetch --tags && git describe --tags $(git rev-list --tags --max-count=1)
    if [ $(git stash list | wc -l) -gt 0 ]
    then
      git stash pop >/dev/null 2>&1
    fi
  args:
    chdir: /opt/awx
  register: latest_tag
  changed_when: false

- name: Use latest released version of AWX
  git:
    repo: https://github.com/ansible/awx.git
    dest: /opt/awx
    version: "{{ latest_tag.stdout }}"

OK, there’s a fair bit to get from this, but essentially, we clone the repo from Github, then ask (using a collection of git commands) for the latest released version (yes, I’ve been bitten by just using the head of “devel” before), and then we check out that released version.

Fab, now we can configure it.

tasks:
- name: Set or Read admin password
  set_fact:
    admin_password_was_generated: "{{ (admin_password is defined or lookup('env', 'admin_password') != '') | ternary(false, true) }}"
    admin_password: "{{ admin_password | default (lookup('env', 'admin_password') | default(lookup('password', 'pw.admin_password chars=ascii_letters,digits length=20'), true) ) }}"

- name: Configure AWX installer
  lineinfile:
    path: /opt/awx/installer/inventory
    regexp: "^#?{{ item.key }}="
    line: "{{ item.key }}={{ item.value }}"
  loop:
  - key: "awx_web_hostname"
    value: "{{ ansible_fqdn }}"
  - key: "pg_password"
    value: "{{ lookup('password', 'pw.pg_password chars=ascii_letters,digits length=20') }}"
  - key: "rabbitmq_password"
    value: "{{ lookup('password', 'pw.rabbitmq_password chars=ascii_letters,digits length=20') }}"
  - key: "rabbitmq_erlang_cookie"
    value: "{{ lookup('password', 'pw.rabbitmq_erlang_cookie chars=ascii_letters,digits length=20') }}"
  - key: "admin_password"
    value: "{{ admin_password }}"
  - key: "secret_key"
    value: "{{ lookup('password', 'pw.secret_key chars=ascii_letters,digits length=64') }}"
  - key: "create_preload_data"
    value: "False"
  loop_control:
    label: "{{ item.key }}"

If we don’t already have a password defined, then create one. We register the fact we’ve had to create one, as we’ll need to tell ourselves it once the build is finished.

After that, we set a collection of values into the installer – the hostname, passwords, secret keys and so on. It loops over a key/value pair, and passes these to a regular expression rewrite command, so at the end, we have the settings we want, without having to change this script between releases.

When this is all done, we execute the installer. I’ve seen this done two ways. In an ideal world, you’d throw this into an Ansible shell module, and get it to execute the install, but the problem with that is that the AWX install takes quite a while, so I’d much rather actually be able to see what’s going on… and so, instead, we exit our prepare script at this point, and drop back to the shell to run the installer. Let’s look at both options, and you can decide which one you want to do. In my script, I’m doing the first, but just because it’s a bit neater to have everything in one place.

- name: Run the AWX install.
  shell: ansible-playbook -i inventory install.yml
  args:
    chdir: /opt/awx/installer
cd /opt/awx/installer
ansible-playbook -i inventory install.yml

When this is done, you get a prepared environment, ready to access using the username admin and the password of … well, whatever you set admin_password to.

AWX takes a little while to stand up, so you might want to run this next Ansible stanza to see when it’s ready to go.

- name: Test access to AWX
  tower_user:
    tower_host: "http://{{ ansible_fqdn }}"
    tower_username: admin
    tower_password: "{{ admin_password }}"
    email: "admin@{{ ansible_fqdn }}"
    first_name: "admin"
    last_name: ""
    password: "{{ admin_password }}"
    username: admin
    superuser: yes
    auditor: no
  register: _result
  until: _result.failed == false
  retries: 240 # retry 240 times
  delay: 5 # pause for 5 sec between each try

The upshot to using that command there is that it sets the email address of the admin account to “admin@your.awx.example.org“, if the fully qualified domain name (FQDN) of your machine is your.awx.example.org.

Moving from the Theoretical to the Practical

Now we’ve got our playbook, let’s wrap this up in both a Vagrant Vagrantfile and a Terraform script, this means you can deploy it locally, to test something internally, and in “the cloud”.

To simplify things, and because the version of Ansible deployed on the Vagrant box isn’t the one I want to use, I am using a single “user-data.sh” script for both Vagrant and Terraform. Here that is:

#!/bin/bash
if [ -e "$(which yum)" ]
then
  yum install git python3-pip -y
  pip3 install ansible docker docker-compose
else
  echo "This script only supports CentOS right now."
  exit 1
fi

git clone https://gist.github.com/JonTheNiceGuy/024d72f970d6a1c6160a6e9c3e642e07 /tmp/Install_AWX
cd /tmp/Install_AWX
/usr/local/bin/ansible-playbook Install_AWX.yml

While they both have their differences, they both can execute a script once the machine has finished booting. Let’s start with Vagrant.

Vagrant.configure("2") do |config|
  config.vm.box = "centos/8"

  config.vm.provider :virtualbox do |v|
    v.memory = 4096
  end

  config.vm.provision "shell", path: "user-data.sh"

  config.vm.network "forwarded_port", guest: 80, host: 8080, auto_correct: true
end

To boot this up, once you’ve got Vagrant and Virtualbox installed, run vagrant up and it’ll tell you that it’s set up a port forward from the HTTP port (TCP/80) to a “high” port – TCP/8080. If there’s a collision (because you’re running something else on TCP/8080), it’ll tell you what port it’s forwarded the HTTP port to instead. Once you’ve finished, run vagrant destroy to shut it down. There are lots more tricks you can play with Vagrant, but this is a relatively quick and easy one. Be aware that you’re not using HTTPS, so traffic to the AWX instance can be inspected, but if you’re running this on your local machine, it’s probably not a big issue.

How about running this on a cloud provider, like AWS? We can use the exact same scripts – both the Ansible script, and the user-data.sh script, using Terraform, however, this is a little more complex, as we need to create a VPC, Internet Gateway, Subnet, Security Group and Elastic IP before we can create the virtual machine. What’s more, the Free Tier (that “first hit is free” thing that Amazon Web Services provide to you) does not have enough horsepower to run AWX, so, if you want to look at how to run up AWX in EC2 (or to tweak it to run on Azure, GCP, Digital Ocean or one of the fine offerings from IBM or RedHat), then click through to the gist I’ve put all my code from this post into. The critical lines in there are to select a “CentOS 8” image, open HTTP and SSH into the machine, and to specify the user-data.sh file to provision the machine. Everything else is cruft to make the virtual machine talk to, and be seen by, hosts on the Internet.

To run this one, you need to run terraform init to load the AWS plugin, then terraform apply. Note that this relies on having an AWS access token defined, so if you don’t have them set up, you’ll need to get that sorted out first. Once you’ve finished with your demo, you should run terraform destroy to remove all the assets created by this terraform script. Again, when you’re running that demo, note that you ONLY have HTTP access set up, not HTTPS, so don’t use important credentials on there!

Once you’ve got your AWX environment running, you’ve got just enough AWX there to demo what Ansible Tower looks like, what it can bring to your organisation… and maybe even convince them that it’s worth investing in a license, rather than running AWX in production. Just in case you have that 2AM call-out that we all dread.

Featured image is β€œpharmacy” by β€œTim Evanson” on Flickr and is released under a CC-BY-SA license.

"centos login" by "fsse8info" on Flickr

Getting the default username and AMI for an OS with #Terraform

I have a collection of AWS AMIs I use for various builds at work. These come from two places – the AWS Marketplace and our internal Build process.

Essentially, our internal builds (for those who work for my employer – these are the OptiMISe builds) are taken from specific AWS Marketplace builds and hardened.

Because I don’t want to share the AMI details when I put stuff on GitHub, I have an override.tf file that handles the different AMI search strings. So, here’s the ami.tf file I have with the AWS Marketplace version:

data "aws_ami" "centos7" {
  most_recent = true

  filter {
    name   = "name"
    values = ["CentOS Linux 7 x86_64 HVM EBS ENA*"]
  }

  filter {
    name   = "architecture"
    values = ["x86_64"]
  }

  owners = ["679593333241"] # CentOS Project
}

And here’s an example of the override.tf file I have:

data "aws_ami" "centos7" {
  most_recent = true

  filter {
    name   = "name"
    values = ["SomeUniqueString Containing CentOS*"]
  }

  owners = ["123456789012"]
}

Next, I put these AMI images into a “null” data source, which is evaluated at runtime:

data "null_data_source" "os" {
  inputs = {
    centos7 = data.aws_ami.centos7.id
  }
}

I always forget which username goes with each image, so in the ami.tf file, I also have this:

variable "username" {
  type = map(string)
  default = {
    centos7 = "centos"
  }
}

And in the override.tf file, I have this:

variable "username" {
  type = map(string)
  default = {
    centos7 = "someuser"
  }
}

To get the right combination of username and AMI, I have this in the file where I create my “instance” (virtual machine):

variable "os" {
  default = "centos7"
}

resource "aws_instance" "vm01" {
  ami = data.null_data_source.os.outputs[var.os]
  # additional lines omitted for brevity
}

output "username" {
  value = var.username[var.os]
}

output "vm01" {
  value = aws_instance.vm01.public_ip
}

And that way, I get the VM’s default username and IP address on build. Nice.

Late edit – 2020-09-20: It’s worth noting that this is fine for short-lived builds, proof of concept, etc. But, for longer lived environments, you should be calling out exactly which AMI you’re using, right from the outset. That way, your builds will (or should) all start out from the same point, no ambiguity about exactly which point release they’re getting, etc.

Featured image is β€œcentos login” by β€œfsse8info” on Flickr and is released under a CC-BY-SA license.

"Stockholms Stadsbibliotek" by "dilettantiquity" on Flickr

Terraform templates with Maps

For a project I’m working on, I needed to define a list of ports, and set some properties on some of them. In the Ansible world, you’d use statements like:

{% if data.somekey is defined %}something {{ data.somekey }}{% endif %}

or

{{ data.somekey | default('') }}

In a pinch, you can also do this:

{{ (data | default({}) ).somekey | default('') }}

With Terraform, I was finding it much harder to work out how to find whether a value as part of a map (the Terraform term for a Dictionary in Ansible terms, or an Associative Array in PHP terms), until I stumbled over the Lookup function. Here’s how that looks for just a simple Terraform file:

output "test" {
    value = templatefile(
        "template.tmpl",
        {
            ports = {
                "eth0": {"ip": "192.168.1.1/24", "name": "public"}, 
                "eth1": {"ip": "172.16.1.1/24", "name": "protected"}, 
                "eth2": {"ip": "10.1.1.1/24", "name": "management", "management": true}, 
                "eth3": {}
            },
            management = "1"
        }
    )
}

And the template that goes with that?

%{ for port, data in ports ~}
Interface: ${port}%{ if lookup(data, "name", "") != ""}
Alias: ${ lookup(data, "name", "") }%{ endif }
Services: ping%{ if lookup(data, "management", false) == true } ssh https%{ endif }
IP: ${ lookup(data, "ip", "Not Defined") }

%{ endfor }

This results in the following output:

C:\tf>terraform.exe apply -auto-approve

Apply complete! Resources: 0 added, 0 changed, 0 destroyed.

Outputs:

test = Interface: eth0
Alias: public
Services: ping
IP: 192.168.1.1/24

Interface: eth1
Alias: protected
Services: ping
IP: 172.16.1.1/24

Interface: eth2
Alias: management
Services: ping ssh https
IP: 10.1.1.1/24

Interface: eth3
Services: ping
IP: Not Defined

Naturally, using this in your own user-data or Custom Data field will probably make more sense than just writing it to “output” 😁

Featured image is β€œStockholms Stadsbibliotek” by β€œdilettantiquity” on Flickr and is released under a CC-BY-SA license.

"Sydney Observatory I" by "Newtown grafitti" on Flickr

Using Feature Flags in Terraform with Count Statements

In a project I’m working on in Terraform, I’ve got several feature flags in a module. These flags relate to whether this module should turn on a system in a cloud provider, or not, and looks like this:

variable "turn_on_feature_x" {
  description = "Setting this to 'yes' will enable Feature X. Any other value will disable it. (Default 'yes')"
  value = "yes"
}

variable "turn_on_feature_y" {
  description = "Setting this to 'yes' will enable Feature Y. Any other value will disable it. (Default 'no')"
  value = "no"
}

When I call the module, I then can either leave the feature with the default values, or selectively enable or disable them, like this:

module "region1" {
  source = "./my_module"
}

module "region2" {
  source = "./my_module"
  turn_on_feature_x = "no"
  turn_on_feature_y = "yes"
}

module "region3" {
  source = "./my_module"
  turn_on_feature_y = "yes"
}

module "region4" {
  source = "./my_module"
  turn_on_feature_x = "no"
}

# Result:
# region1 has X=yes, Y=no
# region2 has X=no, Y=yes
# region3 has X=yes, Y=yes
# region4 has X=no, Y=no

When I then want to use the feature, I have to remember a couple of key parts.

  1. Normally this feature check is done with a “count” statement, and the easiest way to use this is to use the ternary operator to check values and return a “1” or a “0” for if you want the value used.

    Ternary operators look like this: var.turn_on_feature_x == "yes" ? 1 : 0 which basically means, if the value of the variable turn_on_feature_x is set to “yes”, then return 1 otherwise return 0.

    This can get a bit complex, particularly if you want to check several flags a few times, like this: var.turn_on_feature_x == "yes" ? var.turn_on_feature_y == "yes" ? 1 : 0 : 0. I’ve found that wrapping them in brackets helps to understand what you’re getting, like this:

    (
      var.turn_on_feature_x == "yes" ?
      (
        var.turn_on_feature_y == "yes" ?
        1 :
        0
      ) :
      0
    )
  2. If you end up using a count statement, the resulting value must be treated as an 0-indexed array, like this: some_provider_service.my_name[0].result

    This is because, using the count value says “I want X number of resources”, so Terraform has to treat it as an array, in case you actually wanted 10 instead of 1 or 0.

Here’s an example of that in use:

resource "aws_guardduty_detector" "Region" {
  count = var.enable_guardduty == "yes" ? 1 : 0
  enable = true
}

resource "aws_cloudwatch_event_rule" "guardduty_finding" {
  count = (var.enable_guardduty == "yes" ? (var.send_guardduty_findings_to_sns == "yes" ? 1 : (var.send_guardduty_findings_to_sqs == "yes" ? 1 : 0)) : 0)
  name = "${data.aws_caller_identity.current.account_id}-${data.aws_region.current.name}-${var.sns_guardduty_finding_suffix}"
  event_pattern = <<PATTERN
{
  "source": [
    "aws.guardduty"
  ],
  "detail-type": [
    "GuardDuty Finding"
  ]
}
PATTERN
}

resource "aws_cloudwatch_event_target" "sns_guardduty_finding" {
  count = (var.enable_guardduty == "yes" ? (var.send_guardduty_findings_to_sns == "yes" ? 1 : 0) : 0)
  rule = aws_cloudwatch_event_rule.guardduty_finding[0].name
  target_id = aws_sns_topic.guardduty_finding[0].name
  arn = aws_sns_topic.guardduty_finding[0].arn
}

resource "aws_cloudwatch_event_target" "sqs_guardduty_finding" {
  count = (var.enable_guardduty == "yes" ? (var.send_guardduty_findings_to_sqs == "yes" ? 1 : 0) : 0)
  rule = aws_cloudwatch_event_rule.guardduty_finding[0].name
  target_id = "SQS"
  arn = aws_sqs_queue.guardduty_finding[0].arn
}

One thing that bit me rather painfully around this was that if you change from an uncounted resource, like this:

resource "some_tool" "this" {
  some_setting = 1
}

To a counted resource, like this:

resource "some_tool" "this" {
  count = var.some_tool == "yes" ? 1 : 0
  some_setting = 1
}

Then, Terraform will promptly destroy some_tool.this to replace it with some_tool.this[0], because they’re not the same referenced thing!

Fun, huh? 😊

Featured image is β€œSydney Observatory I” by β€œNewtown grafitti” on Flickr and is released under a CC-BY license.

"Tracking Methane Sources and Movement Around the Globe" by "NASA/Scientific Visualization Studio" on Nasa.gov

Flexibly loading files in Terraform to license a FortiGate firewall on AWS, Azure and other Cloud platforms

One of the things I’m currently playing with is a project to deploy some FortiGate Firewalls into cloud platforms. I have a couple of Evaluation Licenses I can use (as we’re a partner), but when it comes to automatically scaling, you need to use the PAYG license.

To try to keep my terraform files as reusable as possible, I came up with this work around. It’s likely to be useful in other places too. Enjoy!

This next block is stored in license.tf and basically says “by default, you have no license.”

variable "license_file" {
  default = ""
  description = "Path to the license file to load, or leave blank to use a PAYG license."
}

We can either override this with a command line switch terraform apply -var 'license_file=mylicense.lic', or (more likely) the above override file named license_override.tf (ignored in Git) which has this next block in it:

variable "license_file" {
  default = "mylicense.lic"
}

This next block is also stored in license.tf and says “If var.license is not empty, load that license file [var.license != "" ? var.license] but if it is empty, check whether /dev/null exists (*nix platforms) [fileexists("/dev/null")] in which case, use /dev/null, otherwise use the NUL: device (Windows platforms).”

data "local_file" "license" {
  filename = var.license_file != "" ? var.license_file : fileexists("/dev/null") ? "/dev/null" : "NUL:"
}

πŸ‘‰ Just as an aside, I’ve seen this “ternary” construct in a few languages. It basically looks like this: boolean_operation ? true_value : false_value

That check, logically, could have been written like this instead: "%{if boolean_operation}${true_value}%{else}${false_value}%{endif}"

By combining two of these together, while initially it looks far more messy and hard to parse, I’ve found that, especially in single-line statements, it’s much more compact and eventually easier to read than the alternative if/else/endif structure.

So, this means that we can now refer to data.local_file.license as our data source.

Next, I want to select either the PAYG (Pay As You Go) or BYOL (Bring Your Own License) licensed AMI in AWS (the same principle applies in Azure, GCP, etc), so in this block we provide a different value to the filter in the AMI Data Source, suggesting the string “FortiGate-VM64-AWS *x.y.z*” if we have a value provided license, or “FortiGate-VM64-AWSONDEMAND *x.y.z*” if we don’t.

data "aws_ami" "FortiGate" {
  most_recent = true

  filter {
    name   = "name"
    values = ["FortiGate-VM64-AWS%{if data.local_file.license.content == ""}ONDEMAND%{endif} *${var.release}*"]
  }

  filter {
    name   = "virtualization-type"
    values = ["hvm"]
  }

  owners = ["679593333241"] # AWS
}

And the very last thing is to create the user-data template (known as customdata in Azure), using this block:

data "template_cloudinit_config" "config" {
  gzip          = false
  base64_encode = false

  part {
    filename     = "config"
    content_type = "multipart/mixed"
    content      = templatefile(
      "${path.module}/user_data.txt.tmpl",
      {
        hostname = "firewall"
      }
    )
  }

  part {
    filename     = "license"
    content_type = "text/plain"
    content      = data.local_file.license.content
  }
}

And so that is how I can elect to provide a license, or use a pre-licensed image from AWS, and these lessons can also be applied in an Azure or GCP environment too.

Featured image is β€œTracking Methane Sources and Movement Around the Globe” by β€œNASA/Scientific Visualization Studio”