Terraform: Difference between revisions
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The '.tf' files in your working directory when you run 'terraform plan' or 'terraform apply' together form the root module. That module may call other modules and connect them together by passing output values from one to input values of another. | The '.tf' files in your working directory when you run 'terraform plan' or 'terraform apply' together form the root module. That module may call other modules and connect them together by passing output values from one to input values of another. | ||
=== Strcuture === | |||
* Input variables to accept values from the calling module. | |||
* Output variables to return results to the calling module, which it can then use to populate arguments elsewhere. | |||
* Resources to define one or more infrastructure objects that the module will manage. | |||
To define a module, create a new directory for it and place one or more .tf files inside just as the user would do for a root module. Terraform can load modules either from local relative paths or from remote repositories; if a module will be re-used by lots of configurations you may wish to place it in its own version control repository. | |||
Modules can also call other modules using a module block, but the recommendation is keeping the module tree relatively flat and using module composition as an alternative to a deelpy-nested tree of modules, because this makes the individual modules easier to re-use in different combinations. | |||
=== See also === | === See also === |
Revision as of 10:00, 20 May 2020
Overview
Terraform 내용 정리.
CLI
Usage: terraform [-version] [-help] <command> [args] Common commands: apply Builds or changes infrastructure console Interactive console for Terraform interpolations destroy Destroy Terraform-managed infrastructure env Workspace management fmt Rewrites config files to canonical format get Download and install modules for the configuration graph Create a visual graph of Terraform resources import Import existing infrastructure into Terraform init Initialize a Terraform working directory output Read an output from a state file plan Generate and show an execution plan providers Prints a tree of the providers used in the configuration refresh Update local state file against real resources show Inspect Terraform state or plan taint Manually mark a resource for recreation untaint Manually unmark a resource as tainted validate Validates the Terraform files version Prints the Terraform version workspace Workspace management All other commands: 0.12upgrade Rewrites pre-0.12 module source code for v0.12 debug Debug output management (experimental) force-unlock Manually unlock the terraform state push Obsolete command for Terraform Enterprise legacy (v1) state Advanced state management
Configurations
Syntax
Provider
provider "google" { credentials = "${file("account.json")}" project = "my-project-id" region = "us-central1" }
Module
A module is a container for multiple resources that are used together. Modules can be used to create lightweight abstractions, so that you can describe your infrastructure in terms of its architecture, rather than directly in terms of physical objects.
The '.tf' files in your working directory when you run 'terraform plan' or 'terraform apply' together form the root module. That module may call other modules and connect them together by passing output values from one to input values of another.
Strcuture
- Input variables to accept values from the calling module.
- Output variables to return results to the calling module, which it can then use to populate arguments elsewhere.
- Resources to define one or more infrastructure objects that the module will manage.
To define a module, create a new directory for it and place one or more .tf files inside just as the user would do for a root module. Terraform can load modules either from local relative paths or from remote repositories; if a module will be re-used by lots of configurations you may wish to place it in its own version control repository.
Modules can also call other modules using a module block, but the recommendation is keeping the module tree relatively flat and using module composition as an alternative to a deelpy-nested tree of modules, because this makes the individual modules easier to re-use in different combinations.