2019-03-05 21:18:40 +01:00
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---
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layout: "docs"
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page_title: "Module Composition"
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sidebar_current: "docs-modules-composition"
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description: |-
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Module composition allows infrastructure to be described from modular
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building blocks.
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---
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# Module Composition
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2019-03-18 19:49:30 +01:00
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-> This section is written for **Terraform v0.12 or later**. The general patterns
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described in this section _do_ apply to earlier versions, but the examples
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shown are using v0.12-only syntax and features. For general information
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on module usage in prior versions, see
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[/docs/configuration-0-11/modules.html](the v0.11 documentation about modules).
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2019-03-05 21:18:40 +01:00
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In a simple Terraform configuration with only one root module, we create a
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flat set of resources and use Terraform's expression syntax to describe the
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relationships between these resources:
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```hcl
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resource "aws_vpc" "example" {
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cidr_block = "10.1.0.0/16"
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}
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resource "aws_subnet" "example" {
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vpc_id = aws_vpc.example.id
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availability_zone = "us-west-2b"
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cidr_block = cidrsubnet(aws_vpc.example.cidr_block, 4, 1)
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}
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```
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When we introduce `module` blocks, our configuration becomes heirarchical
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rather than flat: each module contains its own set of resources, and possibly
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its own child modules, which can potentially create a deep, complex tree of
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resource configurations.
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However, in most cases we strongly recommend keeping the module tree flat,
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with only one level of child modules, and use a technique similar to the
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above of using expressions to describe the relationships between the modules:
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```hcl
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module "network" {
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source = "./modules/aws-network"
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base_cidr_block = "10.0.0.0/8"
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}
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module "consul_cluster" {
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source = "./modules/aws-consul-cluster"
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vpc_id = module.network.vpc_id
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subnet_ids = module.network.subnet_ids
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}
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```
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We call this flat style of module usage _module composition_, because it
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takes multiple [composable](https://en.wikipedia.org/wiki/Composability)
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building-block modules and assembles them together to produce a larger system.
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Instead of a module _embedding_ its dependencies, creating and managing its
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own copy, the module _receives_ its dependencies from the root module, which
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can therefore connect the same modules in different ways to produce different
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results.
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The rest of this page discusses some more specific composition patterns that
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may be useful when describing larger systems with Terraform.
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## Dependency Inversion
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In the example above, we saw a `consul_cluster` module that presumably describes
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a cluster of [HashiCorp Consul](https://www.consul.io/) servers running in
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an AWS VPC network, and thus it requires as arguments the identifiers of both
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the VPC itself and of the subnets within that VPC.
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An alternative design would be to have the `consul_cluster` module describe
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its _own_ network resources, but if we did that then it would be hard for
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the Consul cluster to coexist with other infrastructure in the same network,
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and so where possible we prefer to keep modules relatively small and pass in
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their dependencies.
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This [dependency inversion](https://en.wikipedia.org/wiki/Dependency_inversion_principle)
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approach also improves flexibility for future
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refactoring, because the `consul_cluster` module doesn't know or care how
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those identifiers are obtained by the calling module. A future refactor may
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separate the network creation into its own configuration, and thus we may
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pass those values into the module from data sources instead:
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```hcl
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data "aws_vpc" "main" {
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tags {
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Environment = "production"
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}
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}
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data "aws_subnet_ids" "main" {
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vpc_id = data.aws_vpc.main.id
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}
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module "consul_cluster" {
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source = "./modules/aws-consul-cluster"
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vpc_id = data.aws_vpc.main.id
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subnet_ids = data.aws_subnet_ids.main.ids
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}
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```
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This technique is also an answer to the common situation where in one
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configuration a particular object already exists and just needs to be queried,
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while in another configuration the equivalent object must be managed directly.
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This commonly arises, for example, in development environment scenarios where
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certain infrastructure may be shared across development environments for cost
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reasons but managed directly inline in production for isolation.
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This is the best way to model such situations in Terraform. We do not recommend
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attempting to construct "if this already exists then use it, otherwise create it"
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conditional configurations; instead, decompose your system into modules and
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decide for each configuration whether each modular object is directly managed or
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merely used by reference. This makes each configuration a more direct description
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of your intent, allowing Terraform to produce a more accurate plan, and making
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it clearer to future maintainers how each configuration is expected to behave.
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## Multi-cloud Abstractions
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Terraform itself intentionally does not attempt to abstract over similar
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services offered by different vendors, because we want to expose the full
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functionality in each offering and yet unifying multiple offerings behind a
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single interface will tend to require a "lowest common denominator" approach.
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However, through composition of Terraform modules it is possible to create
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your own lightweight multi-cloud abstractions by making your own tradeoffs
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about which platform features are important to you.
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Opportunities for such abstractions arise in any situation where multiple
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vendors implement the same concept, protocol, or open standard. For example,
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the basic capabilities of the domain name system are common across all vendors,
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and although some vendors differentiate themselves with unique features such
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as geolocation and smart load balancing, you may conclude that in your use-case
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you are willing to eschew those features in return for creating modules that
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abstract the common DNS concepts across multiple vendors:
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```hcl
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module "webserver" {
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source = "./modules/webserver"
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}
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locals {
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fixed_recordsets = [
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{
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name = "www"
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type = "CNAME"
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ttl = 3600
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records = [
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"webserver01",
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"webserver02",
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"webserver03",
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]
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},
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]
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server_recordsets = [
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for i, addr in module.webserver.public_ip_addrs : {
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name = format("webserver%02d", i)
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type = "A"
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records = [addr]
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}
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]
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}
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module "dns_records" {
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source = "./modules/route53-dns-records"
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route53_zone_id = var.route53_zone_id
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recordsets = concat(local.fixed_recordsets, local.server_recordsets)
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}
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```
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In the above example, we've created a lightweight abstraction in the form of
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a "recordset" object. This contains the attributes that describe the general
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idea of a DNS recordset that should be mappable onto any DNS provider.
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We then instantiate one specific _implementation_ of that abstraction as a
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module, in this case deploying our recordsets to Amazon Route53.
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If we later wanted to switch to a different DNS provider, we'd need only to
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replace the `dns_records` module with a new implementation targeting that
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provider, and all of the configuration that _produces_ the recordset
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definitions can remain unchanged.
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We can create lightweight abstractions like these by defining Terraform object
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types representing the concepts involved and then using these object types
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for module input variables. In this case, all of our "DNS records"
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implementations would have the following variable declared:
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```hcl
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variable "recordsets" {
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type = object({
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name = string
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type = string
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ttl = number
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records = list(string)
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})
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}
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```
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While DNS serves as a simple example, there are many more opportunities to
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exploit common elements across vendors. A more complex example is Kubernetes,
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where there are now many different vendors offering hosted Kubernetes clusters
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and even more ways to run Kubernetes yourself.
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If the common functionality across all of these implementations is sufficient
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for your needs, you may choose to implement a set of different modules that
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describe a particular Kubernetes cluster implementation and all have the common
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trait of exporting the hostname of the cluster as an output value:
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```hcl
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output "hostname" {
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value = azurerm_kubernetes_cluster.main.fqdn
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}
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```
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You can then write _other_ modules that expect only a Kubernetes cluster
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hostname as input and use them interchangably with any of your Kubernetes
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cluster modules:
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```hcl
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module "k8s_cluster" {
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source = "modules/azurerm-k8s-cluster"
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# (Azure-specific configuration arguments)
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}
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module "monitoring_tools" {
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source = "modules/monitoring_tools"
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cluster_hostname = module.k8s_cluster.hostname
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}
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```
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## Data-only Modules
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Most modules contain `resource` blocks and thus describe infrastructure to be
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created and managed. It may sometimes be useful to write modules that do not
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describe any new infrastructure at all, but merely retrieve information about
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existing infrastructure that was created elsewhere using
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[data sources](/docs/configuration/data-sources.html).
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As with conventional modules, we suggest using this technique only when the
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module raises the level of abstraction in some way, in this case by
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encapsulating exactly how the data is retrieved.
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A common use of this technique is when a system has been decomposed into several
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subsystem configurations but there is certain infrastructure that is shared
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across all of the subsystems, such as a common IP network. In this situation,
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we might write a shared module called `join-network-aws` which can be called
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by any configuration that needs information about the shared network when
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deployed in AWS:
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```
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module "network" {
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source = "./modules/join-network-aws"
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environment = "production"
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}
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module "k8s_cluster" {
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source = "./modules/aws-k8s-cluster"
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subnet_ids = module.network.aws_subnet_ids
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}
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```
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The `network` module itself could retrieve this data in a number of different
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ways: it could query the AWS API directly using
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[`aws_vpc`](/docs/providers/aws/d/vpc.html)
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and
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[`aws_subnet_ids`](/docs/providers/aws/d/subnet_ids.html)
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data sources, or it could read saved information from a Consul cluster using
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[`consul_keys`](https://www.terraform.io/docs/providers/consul/d/keys.html),
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or it might read the outputs directly from the state of the configuration that
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manages the network using
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[`terraform_remote_state`](https://www.terraform.io/docs/providers/terraform/d/remote_state.html).
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The key benefit of this approach is that the source of this information can
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change over time without updating every configuration that depends on it.
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Furthermore, if you design your data-only module with a similar set of outputs
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as a corresponding management module, you can swap between the two relatively
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easily when refactoring.
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