The core Terraform workflow has three steps:
This guide walks through how each of these three steps plays out in the context of working as an individual practitioner, how they evolve when a team is collaborating on infrastructure, and how HCP Terraform enables this workflow to run smoothly for entire organizations.
Let's first walk through how these parts fit together as an individual working on infrastructure as code.
You write Terraform configuration just like you write code: in your editor of choice. It's common practice to store your work in a version controlled repository even when you're just operating as an individual.
# Create repository
$ git init my-infra && cd my-infra
Initialized empty Git repository in /.../my-infra/.git/
# Write initial config
$ vim main.tf
# Initialize Terraform
$ terraform init
Initializing provider plugins...
# ...
Terraform has been successfully initialized!
As you make progress on authoring your config, repeatedly running plans can help flush out syntax errors and ensure that your config is coming together as you expect.
# Make edits to config
$ vim main.tf
# Review plan
$ terraform plan
# Make additional edits, and repeat
$ vim main.tf
This parallels working on application code as an individual, where a tight feedback loop between editing code and running test commands is useful.
When the feedback loop of the Write step has yielded a change that looks good, it's time to commit your work and review the final plan.
$ git add main.tf
$ git commit -m 'Managing infrastructure as code!'
[main (root-commit) f735520] Managing infrastructure as code!
1 file changed, 1 insertion(+)
Because terraform apply will display a plan for confirmation before
proceeding to change any infrastructure, that's the command you run for final
review.
$ terraform apply
An execution plan has been generated and is shown below.
# ...
After one last check, you are ready to tell Terraform to provision real infrastructure.
Do you want to perform these actions?
Terraform will perform the actions described above.
Only 'yes' will be accepted to approve.
Enter a value: yes
# ...
Apply complete! Resources: 1 added, 0 changed, 0 destroyed.
At this point, it's common to push your version control repository to a remote location for safekeeping.
$ git remote add origin https://github.com/*user*/*repo*.git
$ git push origin main
This core workflow is a loop; the next time you want to make changes, you start the process over from the beginning.
Notice how closely this workflow parallels the process of writing application code or scripts as an individual? This is what we mean when we talk about Terraform enabling infrastructure as code.
Once multiple people are collaborating on Terraform configuration, new steps must be added to each part of the core workflow to ensure everyone is working together smoothly. You'll see that many of these steps parallel the workflow changes we make when we work on application code as teams rather than as individuals.
While each individual on a team still makes changes to Terraform configuration in their editor of choice, they save their changes to version control branches to avoid colliding with each other's work. Working in branches enables team members to resolve mutually incompatible infrastructure changes using their normal merge conflict workflow.
$ git checkout -b add-load-balancer
Switched to a new branch 'add-load-balancer'
Running iterative plans is still useful as a feedback loop while authoring configuration, though having each team member's computer able to run them becomes more difficult with time. As the team and the infrastructure grows, so does the number of sensitive input variables (e.g. API Keys, SSL Cert Pairs) required to run a plan.
To avoid the burden and the security risk of each team member arranging all sensitive inputs locally, it's common for teams to migrate to a model in which Terraform operations are executed in a shared Continuous Integration (CI) environment. The work needed to create such a CI environment is nontrivial, and is outside the scope of this core workflow overview, but a full deep dive on this topic can be found in our Running Terraform in Automation guide.
This longer iteration cycle of committing changes to version control and then waiting for the CI pipeline to execute is often lengthy enough to prohibit using speculative plans as a feedback loop while authoring individual Terraform configuration changes. Speculative plans are still useful before new Terraform changes are applied or even merged to the main development branch, however, as we'll see in a minute.
For teams collaborating on infrastructure, Terraform's plan output creates an opportunity for team members to review each other's work. This allows the team to ask questions, evaluate risks, and catch mistakes before any potentially harmful changes are made.
The natural place for these reviews to occur is alongside pull requests within version control--the point at which an individual proposes a merge from their working branch to the shared team branch. If team members review proposed config changes alongside speculative plan output, they can evaluate whether the intent of the change is being achieved by the plan.
The problem becomes producing that speculative plan output for the team to review. Some teams that still run Terraform locally make a practice that pull requests should include an attached copy of speculative plan output generated by the change author. Others arrange for their CI system to post speculative plan output to pull requests automatically.
In addition to reviewing the plan for the proper expression of its author's intent, the team can also make an evaluation whether they want this change to happen now. For example, if a team notices that a certain change could result in service disruption, they may decide to delay merging its pull request until they can schedule a maintenance window.
Once a pull request has been approved and merged, it's important for the team to review the final concrete plan that's run against the shared team branch and the latest version of the state file.
This plan has the potential to be different than the one reviewed on the pull request due to issues like merge order or recent infrastructural changes. For example, if a manual change was made to your infrastructure since the plan was reviewed, the plan might be different when you merge.
It is at this point that the team asks questions about the potential implications of applying the change. Do we expect any service disruption from this change? Is there any part of this change that is high risk? Is there anything in our system that we should be watching as we apply this? Is there anyone we need to notify that this change is happening?
Depending on the change, sometimes team members will want to watch the apply output as it is happening. For teams that are running Terraform locally, this may involve a screen share with the team. For teams running Terraform in CI, this may involve gathering around the build log.
Just like the workflow for individuals, the core workflow for teams is a loop that plays out for each change. For some teams this loop happens a few times a week, for others, many times a day.
While the above described workflows enable the safe, predictable, and reproducible creating or changing of infrastructure, there are multiple collaboration points that can be streamlined, especially as teams and organizations scale. We designed HCP Terraform to support and enhance the core Terraform workflow for anyone collaborating on infrastructure, from small teams to large organizations. Let's look at how HCP Terraform makes for a better experience at each step.
HCP Terraform provides a centralized and secure location for storing input variables and state while also bringing back a tight feedback loop for speculative plans for config authors. Terraform configuration can interact with HCP Terraform through the CLI integration.
terraform {
cloud {
organization = "my-org"
hostname = "app.terraform.io" # Optional; defaults to app.terraform.io
workspaces {
tags = ["networking", "source:cli"]
}
}
}
After you configure the integration, an HCP Terraform API key is all your team members need to edit config and run speculative plans against the latest version of the state file using all the remotely stored input variables.
$ terraform workspace select my-app-dev
Switched to workspace "my-app-dev".
$ terraform plan
Running plan remotely in Terraform Enterprise.
Output will stream here. To view this plan in a browser, visit:
https://app.terraform.io/my-org/my-app-dev/.../
Refreshing Terraform state in-memory prior to plan...
# ...
Plan: 1 to add, 0 to change, 0 to destroy.
With the assistance of this plan output, team members can each work on authoring config until it is ready to propose as a change via a pull request.
Once a pull request is ready for review, HCP Terraform makes the process of reviewing a speculative plan easier for team members. First, the plan is automatically run when the pull request is created. Status updates to the pull request indicate while the plan is in progress.
Once the plan is complete, the status update indicates whether there were any changes in the speculative plan, right from the pull request view.
For certain types of changes, this information is all that's needed for a team member to be able to approve the pull request. When a teammate needs to do a full review of the plan, clicking the link to HCP Terraform brings up a view that allows them to quickly analyze the full plan details.
This page allows the reviewer to quickly determine if the plan is matching the config author's intent and evaluate the risk of the change.
After merge, HCP Terraform presents the concrete plan to the team for review and approval.
The team can discuss any outstanding questions about the plan before the change is made.
Once the Apply is confirmed, HCP Terraform displays the progress live to anyone who'd like to watch.
There are many different ways to use Terraform: as an individual user, a single team, or an entire organization at scale. Choosing the best approach for the density of collaboration needed will provide the most return on your investment in the core Terraform workflow. For organizations using Terraform at scale, HCP Terraform introduces new layers that build on this core workflow to solve problems unique to teams and organizations.