Remote execution model in Terraform - Step-by-Step Execution

Process Flow - Remote execution model

User writes Terraform code

↓

Terraform CLI sends code to Remote Backend

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Remote Backend stores state securely

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Remote Backend runs Terraform plan/apply

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Remote Backend updates state

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User receives output and status

Terraform code is sent to a remote backend which securely stores state and runs the plan/apply commands, then updates state and returns results.

Execution Sample

Terraform

terraform {
  backend "remote" {
    organization = "my-org"
    workspaces { name = "my-workspace" }
  }
}

This config sets Terraform to use a remote backend with an organization and workspace for remote execution.

Process Table

Step	Action	Input/State	Output/State Change
1	User runs 'terraform init'	Local config only	Backend configured to remote with org and workspace
2	User runs 'terraform plan'	Code sent to remote backend	Remote backend creates execution plan, state locked
3	User reviews plan output	Plan generated remotely	Plan displayed locally
4	User runs 'terraform apply'	Apply command sent to remote backend	Remote backend applies changes, updates state
5	State updated remotely	State locked during apply	State unlocked and saved remotely
6	User receives apply output	Apply completed remotely	Output shown locally
7	User runs 'terraform destroy' (optional)	Destroy command sent remotely	Resources destroyed, state updated
8	Execution ends	State consistent remotely	User has updated infrastructure and state

💡 Execution stops after state is updated remotely and user receives output.

Status Tracker

Variable	Start	After Step 2	After Step 4	After Step 5	Final
Terraform Code	Local files	Sent to remote backend	Sent to remote backend	Sent to remote backend	Sent to remote backend
State	Local or none	Locked remotely	Locked remotely	Updated remotely	Unlocked remotely
Execution Plan	None	Created remotely	Created remotely	Used remotely	None
Apply Output	None	None	Generated remotely	Generated remotely	Received locally

Key Moments - 3 Insights

Why does the state get locked during remote execution?

State locking prevents multiple users from changing infrastructure at the same time, as shown in steps 2 and 4 of the execution_table.

Where does the Terraform plan get created in remote execution?

The plan is created on the remote backend, not locally, as seen in step 2 where the plan is generated remotely.

How does the user see the output if execution happens remotely?

The remote backend sends the output back to the user's local CLI, shown in step 6 where output is displayed locally.

Visual Quiz - 3 Questions

Look at the execution_table, at which step is the state first locked remotely?

A Step 1

B Step 4

C Step 2

D Step 5

💡 Hint

Check the 'Output/State Change' column for when state locking occurs.

According to variable_tracker, what is the state after step 5?

A Unlocked locally

B Updated and unlocked remotely

C Updated and locked remotely

D Locked locally

💡 Hint

Look at the 'State' row and the 'After Step 5' and 'Final' columns.

If the user skips 'terraform init', what impact would it have on the execution flow?

A Remote backend would not be configured, so execution fails early

B Plan and apply run locally instead

C State would be locked remotely anyway

D User still gets remote execution without init

💡 Hint

Refer to step 1 where 'terraform init' configures the backend.

Concept Snapshot

Terraform Remote Execution Model:
- Configure remote backend in terraform block
- 'terraform init' sets backend
- 'terraform plan' and 'apply' run remotely
- State is locked during execution
- Outputs returned to local CLI
- Ensures secure, shared state and execution

Full Transcript

In the Terraform remote execution model, the user writes Terraform code locally and configures a remote backend. When the user runs 'terraform init', the backend is set up. Then, 'terraform plan' sends the code to the remote backend, which locks the state and creates a plan. The user reviews the plan locally. When 'terraform apply' is run, the remote backend applies changes, updates and unlocks the state. Outputs are sent back to the user. This model ensures state is stored securely and execution is centralized, preventing conflicts.