Automating Terraform and Infrastructure as Code with env zero

You run [.code]terraform apply[.code], it fails partway through, and the next command you run refuses to move: [.code]Error acquiring the state lock[.code]. Nothing is broken yet, but nothing will proceed either until the lock is cleared.

This guide covers what [.code]force-unlock[.code] actually does, when it is safe to use, how to find the lock ID on every major backend, and what to do if the command itself does not fix things.

What does terraform force-unlock do?

Terraform locks state before any operation that could write to it. The lock stops two processes from writing to the same state file at once, which is the most common way a state file gets corrupted. Locking happens automatically and silently on every plan and apply where the backend supports it. You will not see a message unless acquiring the lock takes longer than expected.

[.code]force-unlock[.code] is the manual override for when that automatic process gets stuck. It removes the lock record so a new operation can proceed. According to HashiCorp, the command does not modify your infrastructure, and on most backends it does not touch your state data either. It just clears the record that says the state is currently held.

Usage:

terraform force-unlock [options] LOCK_ID

The only option is [.code]-force[.code], which skips the yes or no confirmation prompt. That is useful inside a script or CI job where nothing is available to type “yes” into. Otherwise leave it off, since the confirmation step is the last chance to catch a mistake before you unlock something someone else is actively using.

The lock ID is not optional and is not guessable. Terraform prints it in the error message when a lock is already held, and [.code]force-unlock[.code] requires an exact match. Per HashiCorp's own documentation, the ID works as a nonce, a one-time verification token that ensures a lock and an unlock target the same lock. That is deliberate: you can only release a lock you can identify, not just any lock on the state file.

One thing worth flagging up front: on the local backend, a stuck lock can only be cleared by the same machine and user that created it. There is no separate process to force it from elsewhere, which is one more reason most teams move to a remote backend, such as the ones covered in this backend configuration guide, before this becomes a live problem.

When should you use the force-unlock command?

Treat [.code]force-unlock[.code] as a last resort, not a first response. If two operations are genuinely running against the same state at the same time, forcing a lock open defeats the entire purpose of state locking and can leave you with a corrupted state file. Only run it when you are certain the process that created the lock is no longer active.

A stuck lock usually traces back to one of a few causes:

• A [.code]terraform apply[.code] or [.code]plan[.code] was cancelled or errored mid-run, for example because a CI job timed out or someone hit Ctrl+C, so Terraform never reached the step where it releases the lock.
• The machine or build agent running Terraform lost its network connection to the backend before the lock could be released.
• The backend storage itself changed mid-operation, for example a Terraform run modifying firewall rules, private endpoints, or access policies on the very storage account that holds the state file.

If none of those match your situation and you are not sure why the lock exists, treat that as a reason to investigate before clearing it, not a reason to assume it is safe to force.

Where to find the lock ID for every backend

In most cases you will not need to go looking. The lock ID appears directly in the [.code]Error acquiring the state lock[.code] message, under the [.code]ID:[.code] field, alongside who holds it and when it was created. The backend-specific detail below matters mainly when you are troubleshooting secondhand, for example clearing a lock a teammate reported without a fresh error message in front of you.

Local backend

Terraform writes a [.code].terraform.tfstate.lock.info[.code] file next to the state file while an operation is in progress. It is a small JSON object containing the lock [.code]ID[.code], the operation type, and who created it. On clean exit, Terraform deletes this file automatically. As noted above, a lock created by one machine cannot be released by [.code]force-unlock[.code] from a different one.

Amazon S3

As of Terraform 1.11, the S3 backend supports native state locking through the [.code]use_lockfile[.code] argument, and no longer requires a separate DynamoDB table. Setting it to [.code]true[.code] tells Terraform to create a lock object in the same S3 bucket as your state, using conditional writes so only one process can create it at a time.

terraform {
  backend "s3" {
    bucket       = "mybucket"
    key          = "path/to/my/key"
    region       = "us-east-1"
    use_lockfile = true
  }
}

With native locking, the lock ID is whatever the error message reports; there is no separate table to query. If your configuration still uses the older [.code]dynamodb_table[.code] argument, note that HashiCorp has deprecated it in favor of [.code]use_lockfile[.code]. On that legacy path, the lock lives as an item in the DynamoDB table, keyed by a partition key named [.code]LockID[.code], and you can inspect it directly:

aws dynamodb get-item \
  --table-name your-lock-table \
  --key '{"LockID": {"S": "your-bucket/path/to/terraform.tfstate"}}'

Azure Blob Storage

Azure Blob Storage implements locking through native blob leases, with no extra backend configuration required. If a run is interrupted mid-apply, the lease can be left in place. The lock ID appears in the error message, but you can also inspect the lease state directly:

az storage blob show \
  --account-name YOUR_STORAGE_ACCOUNT \
  --container-name YOUR_CONTAINER \
  --name path/to/terraform.tfstate \
  --query 'properties.lease'

If [.code]force-unlock[.code] is not an option, for example the lock ID is unavailable, you can break the lease directly through the Azure CLI, which achieves the same result at the storage layer:

az storage blob lease break \
  --account-name YOUR_STORAGE_ACCOUNT \
  --container-name YOUR_CONTAINER \
  --blob-name path/to/terraform.tfstate

Google Cloud Storage

The GCS backend also locks natively with zero extra configuration. Terraform writes a lock object at [.code]/.tflock[.code] in the same bucket as your state, and the lock ID is the object's generation number, which is included in the error message. Deleting that object directly is the manual equivalent of [.code]force-unlock[.code] if the CLI command fails for some reason.

HCP Terraform and Terraform Enterprise

This is a common point of confusion: [.code]terraform force-unlock[.code] is a CLI command that works against backends where Terraform itself manages the lock file. HCP Terraform and Terraform Enterprise instead lock and unlock workspaces through their own UI and API, not the CLI command. In the workspace's Actions menu, you can select Lock workspace or Unlock workspace directly, or call the workspaces API endpoint to do the same thing from automation.

Consul

With the Consul backend, lock information lives in the Consul key-value store rather than in a file. You can list it with the [.code]consul kv get [.code] command, or query the same data through Consul's HTTP API.

Using terraform force-unlock: a worked example

1. Identify the lock ID from the error message. For example: [.code]Lock Info: ID: b8814894-4a5f-217b-e97b-c4f5c02a1f88[.code].
2. Confirm nobody else is running an operation against this state. Check your CI/CD dashboard, ask your team, or check the environment's deployment history if you are running on a platform that centralizes this, before assuming the lock is actually stale.
3. Run the command with the ID from step one: [.code]terraform force-unlock b8814894-4a5f-217b-e97b-c4f5c02a1f88[.code]. Confirm the prompt with [.code]yes[.code], or add [.code]-force[.code] if you are running this non-interactively.
4. Verify the fix by re-running the command that originally failed, such as [.code]terraform plan[.code]. If it proceeds past the locking step without error, the lock is cleared.

Unlocking remote state: alternatives to force-unlock

Wait instead of forcing: -lock-timeout

If two operations occasionally overlap for a few seconds, for example two CI jobs kicking off close together, [.code]force-unlock[.code] is the wrong tool. The [.code]-lock-timeout[.code] flag tells Terraform to wait for the lock to clear on its own instead of failing immediately:

terraform plan -lock-timeout=5m

This is worth setting as a default in CI pipelines that run plan, apply, or destroy operations back to back, so a brief overlap resolves itself instead of surfacing as a lock error at all.

Manual removal as a last resort

Occasionally [.code]force-unlock[.code] itself fails, usually because the backend is unreachable or credentials cannot reach the lock record. HashiCorp's guide to recovering state from backup covers this scenario directly. In that situation, the remaining options are backend-specific: delete the lock object from S3 or GCS, edit or remove the DynamoDB item, or break the Azure blob lease as shown above. All of these bypass Terraform entirely, so treat them with the same caution as [.code]force-unlock[.code] itself.

Coordinate before you unlock

Whichever method you use, confirm no other process is mid-write before you touch the lock, and consider pulling a backup first with [.code]terraform state pull[.code]. Never use [.code]-lock=false[.code] as a standing workaround for frequent lock errors. It disables the protection entirely rather than resolving whatever is causing the contention.

Troubleshooting force-unlock errors

The lock ID does not match

[.code]force-unlock[.code] will refuse an ID that does not match the current lock. This almost always means you are using a stale ID from an old error message. Re-run the failing command to get the current lock's ID and try again.

Permission errors during force-unlock

Clearing a lock requires write or delete access to wherever the lock record lives, for example [.code]s3:DeleteObject[.code] on the lock object, or the equivalent DynamoDB, GCS, or Azure permission. A permissions error here usually points to the credentials Terraform is running with, not the lock itself.

The same lock error comes back immediately

If you clear a lock and it reappears right away, something is still actively writing to that state. Stop and investigate before unlocking again. This pattern usually means step two of the worked example above was skipped.

Managing state locking at scale with env zero

Clearing a stuck lock by hand does not scale once a platform team is managing hundreds of environments across multiple backends. Ad Hoc Tasks in env zero let you run a command, including [.code]terraform force-unlock -force LOCK_ID[.code], directly on the environment's deployment container from the UI. That means resolving a stuck lock does not require local CLI access, a checked-out copy of the Terraform configuration, or direct credentials to the backend that holds the state.

By default, ad hoc tasks are restricted to organization administrators, since they allow arbitrary commands against a live deployment container. Teams that want to delegate lock-clearing to platform engineers without granting full admin access can do that with a custom role scoped to just that permission.

It is worth distinguishing this from Environment Locking in env zero, which is a separate, deliberate governance control rather than Terraform's automatic state lock. Locking an environment in env zero blocks deploys, destroys, plans, and drift detection outright, with a reason attached for anyone else who looks at it, and it stays in effect until someone with permission unlocks it. A Terraform state lock, by contrast, is transient by design and normally clears itself within seconds. If you are troubleshooting a “locked” environment in env zero and [.code]force-unlock[.code] does not seem relevant, this distinction is usually why.

Key takeaways

• [.code]terraform force-unlock LOCK_ID[.code] manually clears a stuck state lock. It does not touch your infrastructure, and on most backends it does not touch your state data either.
• Only use it when you are certain the process that created the lock is no longer running. Unlocking an active operation risks a corrupted state file.
• The lock ID is usually sitting right in the error message. You only need to hunt through backend-specific tooling when troubleshooting without that message in hand.
• S3 no longer needs DynamoDB for locking. [.code]use_lockfile = true[.code] has been the supported path since Terraform 1.11.
• [.code]-lock-timeout[.code] prevents most stuck-lock situations in CI before they happen, by waiting instead of failing immediately.

Frequently asked questions

Q. How do I fix a Terraform state lock?

Run [.code]terraform force-unlock LOCK_ID[.code], using the ID from the [.code]Error acquiring the state lock[.code] message. Only do this once you are certain no other operation is currently running against the same state.

Q. What is Terraform state locking for?

State locking prevents two operations from writing to the same state file at the same time, which is one of the most common causes of state corruption. Terraform acquires the lock automatically before any operation that could write state and releases it when the operation finishes.

Q. Can force-unlock corrupt my Terraform state?

[.code]force-unlock[.code] itself does not modify your infrastructure or your state data; it only removes the lock record. The risk is indirect: if you unlock a state that another process is actively writing to, that process and yours can both write at once, which can corrupt the state file.

Q. Does the S3 backend still need DynamoDB for state locking?

No. Since Terraform 1.11, the S3 backend supports native locking through [.code]use_lockfile = true[.code], using S3 conditional writes instead of a separate DynamoDB table. The older [.code]dynamodb_table[.code] argument still works but is deprecated.

Q. How do I avoid stuck state locks in the first place?

Avoid cancelling Terraform runs mid-operation, set [.code]-lock-timeout[.code] in CI so brief overlaps wait instead of failing, and use a platform that centralizes deployment history so you can quickly confirm whether a lock is stale before clearing it.

Hello, env zero fans! As some of you know, we have almost unlimited extensibility with 3rd party tools, using our custom workflows. You can hook in pretty much any tool, in any phase of the deployment. Today, we’re going to talk about how to prevent cloud misconfigurations before they start. We’re going to do this by chaining a tool in the deployment after the terraform plan phase. This is where our friends at Bridgecrew come in. Just like we at env zero have open-sourced the Terratag module of our platform, Bridgecrew has open-sourced Checkov!

Checkov

Checkov is a static code analysis tool for infrastructure-as-code. It scans cloud infrastructure managed in Terraform, Cloudformation, Kubernetes, Arm templates, or Serverless Framework and detects misconfigurations.

Setup

For illustration purposes, we’re going to use Bridgecrew’s demo application called TerraGoat. TerraGoat is Bridgecrew’s “Vulnerable by Design” Terraform repository. TerraGoat is a learning and training project that demonstrates how common configuration errors can find their way into production cloud environments.

DISCLAIMER: DO NOT ACTUALLY DEPLOY THIS APPLICATION INTO YOUR CLOUD INFRASTRUCTURE. IT IS PURPOSELY COMPROMISED.

I have created a template of TerraGoat inside of env zero and linked it to our Bridgecrew Demo project.

The only other thing we have to do is to actually call Checkov to do the check during the deployment. We need to do this after the Terraform plan phase, so that we have a plan to check. Here is what the env0.yml file will look like:

This adds 3 commands that run after the Terraform Plan, and before Terraform Apply. We put it here so that the Apply doesn’t run in case of failures. We don’t want to see the errors after the resources are applied. We want the deployment to fail if there are errors.

This command installs Checkov into our runtime environment using the pip3 package installer so we can run it against our Terraform plan.

This command essentially formats our .tf-plan file into tf.json so that it can be parsed and run against Checkov.

This command has a lot going on and is in 2 parts. First, it quietly executes Checkov against our tf.json (the reformatted tf.plan file) and looks for a 0 exit code. The double pipe || tells bash to only execute the 2nd command if the exit code of the first command is not 0. So if your Checkov results are clear, your deployment gets the 0 exit code and continues on with the deployment.

If not, then the second part of the command runs. Knowing if this part runs, it is because of a failure, we’re just going to format our error message here. We run Checkov again so we can pipe the error with the echoed error notification text to the console. The 1>&2 routs stdout to stderror, and the exit 1 code tells env zero that the stage failed, and to end the deployment run.

The env zero platform will parse the error, and give you the clear error printed on the Environment deployment page. But, if you want the full logs from Checkov, you can find those in the After: Terraform Plan deployment logs.

And that’s it! A little bit of YAML, and you’ve implemented Checkov to protect yourself against the deployment of misconfigured cloud resources. That is instantly added value to your organization by shifting the security left in your deployment process with env0.

You can find more information on Checkov here. You can find the open-source repository on GitHub. And be sure to see how you can automate your infrastructure security from commit to cloud at Bridgecrew.io.

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"env zero cut our mean time to merge in half by helping us better manage our workflow and code conflicts.Their customer service and willingness to roll out features based on our needs was unprecedented."

Troy Knapp

Senior DevOps Engineery

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Background

Zip Co Limited (abbreviated as Zip Co) is a global 'buy now pay later' financial technology company with operations in Australia, New Zealand, and the USA used by millions of customers to handle billions of dollars in annual transactions. 

The Challenge

Before using env0, ZipCo utilized a monolithic Terraform repository and a rigid tool that functioned similarly to a conventional Git workflow, involving numerous pull requests from the master branch.

This resulted in a cumbersome process that ended up locking out any other developer from making changes. 

Moreover, for change, the propagation occurred linearly, where each environment would update one by one, further lengthening the time to deploy. 

As a result, it wasn’t uncommon for a simple change to take multiple hours to deploy, during which the codebase was locked, preventing anyone else from working on it.

The Solution

• Parallel Deployments: Before env0, ZipCo would have to deploy their code linearly. After moving to env0, multiple environments could now be deployed simultaneously.
• Robust UI: The interface env zero provides has given each developer a deeper insight in a much more organized fashion that doesn't rely on local code execution. The interface is also much easier to understand, well documented, and has fewer clicks than their previous solution.

The Impact

• Time to Deploy Cut by 50% - Simultaneous environment deployments have drastically reduced deployment times, thereby optimizing the development cycle and saving valuable time for the company.  
• Transparency and Accountability - By exposing "tribal knowledge" and eliminating hidden shortcuts and backdoors, all team members now have a clear understanding of the deployment environments, fostering a culture of openness and accountability.
• Streamlined Operations - The UI simplifies the deployment process, requires fewer steps compared to previous solutions, and is more intuitive. This improvement has enhanced productivity.
• Shortening Issue Resolution - Using env zero drift detection and logging capabilities, issues could be identified and resolved quicker, within hours rather than days or weeks.

What’s Next

There are still daily challenges ZipCo faces as they continue to integrate their worldwide Azure solution with env0. As each challenge presents itself, the flexibility of env zero coupled with the newfound agility gives ZipCo multiple paths to solve issues they traditionally saw as not reasonably achievable. 

In a recent blog post, I discussed expanding the idea of “Feature branches” to “Feature environments”. Using Infrastructure-as-Code, we can create an environment for every feature we are working on, thereby giving us a more flexible, isolated development environment, and allowing us to test our code early in the development process.

In this post I’d like to continue down that path, and see how we can automatically create an environment for every pull request, and gain a number of advantages over traditional static staging or qa environments.

Pull Requests & Moving Beyond Static Staging

Pull requests are a well known and common workflow step for many development teams. We usually think of them as a way you “tell others about changes you've pushed”, and where you “can discuss and review the potential changes with collaborators and add follow-up commits before your changes are merged”.

PR’s are more than just a code review - they’re a milestone in a feature’s lifecycle and a way of saying “I’m ready for this to be shared”. Beyond sharing it for feedback with the wider team, this milestone is a critical time to ensure it functions exactly as expected as part of the whole application, including any potential infrastructure or configuration changes. However - just as we wouldn’t want our data migration to run on the shared database at this point, we also want to use dedicated test infrastructure.

Static VS Dynamic PR Environments

At this point, you might ask yourself - I’m already testing my code and infrastructure changes in our dev/qa/staging environment, why complicate things?

Well, there are a number of advantages to moving from traditional, static environments, to dynamic, per-pull-request environments:

• They’re Isolated and Dedicated - having a dedicated environment for each PR means no more confusion of which version or branch is currently in staging, and no coordinating between people who want to test different versions.
• Easier To Share - Because each PR has its own fully functional environment, non technical stakeholders can provide feedback on new features very early in the process. Developers can then iterate over this feedback - without interfering with work being done by other team members.
• No Wasted Resources - Because you’re only provisioning an environment when you actually need it for testing, you’re not wasting (or paying for) resources when you don’t actually need them.
• Removes Bottlenecks In The Release Cycle - Shared development and staging environments are notorious bottlenecks for development teams, especially when they are the first place where new code meets infrastructure. It’s not uncommon to see a queue of who is using the environment for testing their features. Your developers time shouldn’t be spent on waiting.

How Do You Actually Do It?

Ok, so “per pull request environments” is an awesome idea. How are we going to actually get there? There are a number of tools out there that can help you accomplish this task but in this post, I’ll be using env0, a first of it’s kind environment-as-a-service platform - not just to deploy the environments, but to manage them as well.

Your default assumption might be to just use your CI/CD platform to set up your environment. This works, but most CI/CD platforms are built for running short lived tasks, whereas an environment’s lifecycle extends beyond deploying it once: It needs to be updated, monitored, and in the end destroyed. Besides easily automating resource provisioning using Terraform, env zero will help me keep track of which environments are up, which ones have had issues, and will provide me a top level view of how my whole team is using these environments.

Besides env0, I’ll be using Github to host my code and open pull requests, and Github Actions to trigger my environment creation. I’ll be using the same code example from the previous post, which will be deployed on AWS.

If you’d like to try this out yourself, the prerequisites for this tutorial will be

• An env zero account (it’s free, just login)
• A Github account 
• An AWS account

Getting Our Hands Dirty

Step one to fully automating anything is to make sure we can run it manually, so you’ll want to get your system set up. In my case, I’ve followed env0’s getting started guide, and taken the key steps of creating my own organization, connecting my AWS account, and creating a template for my Terraform code.

Custom workflows to the rescue

In the example code I’ve used, I also ran a bash script before deploying the environment. We can easily make sure this code runs before our Terraform is applied, using env0’s Custom Flows feature. I’ve already done this in advance and I’ve put my code in the env0.yml file, in our Github repo.

Let ‘er Rip!

We are ready to launch our first environment! Remember - this is just a manual test, to see things are ready for automation.

In the case of env0, just go to your Project Templates pages, and click “Run now” on the template we’ve created before. In the next screen, you can validate your settings, and when you’re ready - click “Run”.

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Great!

Integrating into CI/CD

Now that we know our environment management system will properly configure our environments, we need to make it run each time we open a pull request. For that, we’ll be using Github Actions to trigger env0’s CLI.

In order to create an environment on env zero from Github Actions, we need to create an API key for env0.

Next, we’ll need to save the API key and secret as Github Secrets, in the same manner we saved our AWS credentials to env0.

The final step of connecting everything, is telling Github how to trigger our environment deploy. We’ll add the following code to our codebase, in the file `.github/workflows/pr-environments.yml`.

name: "PR Environments"
on:
 pull_request:
   types: [opened, closed, reopened, synchronize]
jobs:
 env0_pr_environment:
   name: "PR Environment"
   runs-on: ubuntu-16.04
   env:
     ACTION: deploy
   steps:
     - name: Set Action
       if: github.event.action == 'closed'
       run: echo "::set-env name=ACTION::destroy"
     - uses: actions/setup-node@v1
       with:
         node-version: '12'
     - uses: actions/checkout@v2
       with:
         repository: env0/env0-client-integrations
     - name: install
       working-directory: node
       run: yarn
     - name: deploy
       working-directory: node
       run: >
         node env0-deploy-cli.js
         --apiKey ${{ secrets.ENV0_API_KEY_ID }}
         --apiSecret ${{ secrets.ENV0_API_KEY_SECRET }}
         --action $ACTION
         --organizationId ${{ secrets.ENV0_ORG_ID }}
         --projectId ${{ secrets.ENV0_PROJECT_ID }}
         --blueprintId ${{ secrets.ENV0_BLUEPRINT_ID }}
         --environmentName "${{ github.head_ref }}"
         --revision "${{ github.head_ref }}"

In the code above, you can see we

• Determine the action depending on the Github event data
• Fetch the env zero CLI, using the `checkout` action
• Run the env zero cli to deploy, update, or destroy the environment
• The name of the environment will be the branch name

That’s all folks!

We now have a fully functioning pipeline, and our setup will automatically create a new environment for every PR we open! When we deploy a new feature, even if that feature requires new or different infrastructure, the changes in our Terraform code will automatically be reflected in the resources provisioned for the PR environment!

In the case of env0, even though environments will be automatically created and destroyed by our CI/CD integration, we can also use the env zero UI as a control plane, for understanding which environments are up, and what they consist of. You can also use env0’s cost monitoring features, to understand how much each of these environments actually costs.

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Thank you for taking the time to read this post, I hope it helps you setting an environment-per-PR pipeline for your team. Once you’ve tried it yourself, I’d love to hear about it! Let me know in the comments below or on Twitter at @envzero.