Terraform Workspaces: Managing Multiple Environments

Your complete guide to using Terraform workspaces for environment isolation—when to use them, when to avoid them, and how to design multi-environment infrastructure that scales.

📅 Published: Feb 2026
⏱️ Estimated Reading Time: 22 minutes
🏷️ Tags: Terraform Workspaces, Environments, Multi-Environment, State Isolation, Terraform Best Practices

🎭 Introduction: The Environment Problem

Every Team Needs Multiple Environments

Every successful infrastructure project grows beyond a single environment. You start with development. Then you need staging to test before production. Then production itself. Then perhaps disaster recovery, performance testing, sandbox environments for new team members, and feature-specific preview environments.

This is the environment problem: How do you manage infrastructure that is mostly the same across environments, but different in critical ways?

The naive approach—copy-paste-modify—leads to disaster:

Dev, staging, and prod configurations drift apart
Security patches applied in prod but not dev
Production bugs that can't be reproduced in lower environments
Configuration that works in dev but fails in prod
Fear of changing infrastructure because "prod is different"

Terraform workspaces are one solution to this problem. But they're not the only solution—and often not the best solution.

What Are Workspaces?

Workspaces are named containers for multiple state files associated with a single configuration. Think of them as separate tracking files for the same Terraform code.

# Create and switch to a new workspace
terraform workspace new dev
terraform workspace new staging
terraform workspace new prod

# List workspaces
terraform workspace list
  default
  dev
  staging
* prod

# Switch between workspaces
terraform workspace select dev
terraform workspace select prod

Each workspace has its own state file:

terraform.tfstate.d/
├── dev/
│   └── terraform.tfstate
├── staging/
│   └── terraform.tfstate
└── prod/
    └── terraform.tfstate

The same configuration, the same variables, the same providers—different state files.

Workspaces vs. Directory Structure

This is the fundamental question every Terraform team must answer:

Approach	How It Works	Best For
Workspaces	Single configuration, multiple state files	Simple environments, small teams, early stages
Directory structure	Separate configurations per environment	Complex environments, large teams, strict isolation
Terragrunt	Tool overlay for DRY configurations	Enterprise, many environments, compliance requirements

There is no universally correct answer. There are tradeoffs, and understanding them is the difference between a scalable infrastructure and a tangled mess.

🔧 How Workspaces Work

Workspace State Storage

With local state, workspaces are stored in terraform.tfstate.d/:

project/
├── main.tf
├── variables.tf
├── outputs.tf
└── terraform.tfstate.d/
    ├── dev/
    │   └── terraform.tfstate
    └── staging/
        └── terraform.tfstate

With remote state, workspaces modify the backend path:

terraform {
  backend "s3" {
    bucket = "company-terraform-state"
    key    = "my-app/terraform.tfstate"  # Base path
    region = "us-west-2"
    
    # Workspace-enabled backend
    workspace_key_prefix = "env:"  # Default
  }
}

State files become:

s3://company-terraform-state/env:dev/my-app/terraform.tfstate
s3://company-terraform-state/env:staging/my-app/terraform.tfstate
s3://company-terraform-state/env:prod/my-app/terraform.tfstate

The Workspace Variable

Terraform provides terraform.workspace—a special variable that contains the current workspace name.

# Use workspace in resource names
resource "aws_s3_bucket" "data" {
  bucket = "my-app-data-${terraform.workspace}"
  
  tags = {
    Environment = terraform.workspace
    ManagedBy   = "Terraform"
  }
}

# Conditional logic based on workspace
resource "aws_instance" "web" {
  instance_type = terraform.workspace == "prod" ? "t3.large" : "t3.micro"
  
  count = terraform.workspace == "prod" ? 3 : 1
}

# Workspace-specific variable values
locals {
  instance_count = {
    default = 1
    prod    = 3
    staging = 2
  }
  
  actual_count = lookup(local.instance_count, terraform.workspace, local.instance_count.default)
}

This is the primary mechanism for environment-specific configuration when using workspaces.

Workspace Workflow

Typical workspace-based workflow:

# Initialize the configuration (once)
terraform init

# Create and switch to development workspace
terraform workspace new dev
terraform apply -var-file="dev.tfvars"

# Switch to staging
terraform workspace select staging
terraform apply -var-file="staging.tfvars"

# Switch to production
terraform workspace select prod
terraform apply -var-file="prod.tfvars"

Each apply operates on its own isolated state file. Resources in dev don't conflict with resources in prod because they're in different workspaces—but they're still defined by the same configuration.

✅ When Workspaces Work Well

Use Case 1: Simple, Parallel Environments

You have multiple identical environments that need to exist simultaneously. Feature branches, developer sandboxes, ephemeral test environments.

# Developer creates a feature branch environment
terraform workspace new "feature-user-auth-${USER}"
terraform apply -auto-approve

# Test the feature
# ...

# Destroy when done
terraform destroy -auto-approve
terraform workspace select default
terraform workspace delete "feature-user-auth-${USER}"

Why workspaces work here:

Environments are truly identical (no configuration differences)
Environments are short-lived (created and destroyed frequently)
Naming convention includes workspace name
No need for complex conditional logic

Use Case 2: Prototyping and Early Stages

Your infrastructure is simple and your team is small. You need dev, staging, and prod, but they're mostly the same with minor differences.

# Simple conditional logic is manageable
resource "aws_db_instance" "main" {
  instance_class = terraform.workspace == "prod" ? "db.r5.large" : "db.t3.micro"
  backup_retention_period = terraform.workspace == "prod" ? 30 : 7
  deletion_protection = terraform.workspace == "prod" ? true : false
}

Why workspaces work here:

Low complexity
Single team managing all environments
Easy to understand and implement
No need for separate state configurations

Use Case 3: Application-Tethered Infrastructure

Your infrastructure is tightly coupled to a specific application. Each instance of the application gets its own full infrastructure stack.

application-stack/
├── main.tf
├── variables.tf
├── outputs.tf
└── README.md

Each deployment is a workspace:

terraform workspace new customer-abc
terraform apply -var="customer_id=abc"

terraform workspace new customer-xyz
terraform apply -var="customer_id=xyz"

Why workspaces work here:

Each workspace represents a complete, independent stack
Workspaces map 1:1 to business entities
No shared infrastructure between workspaces

❌ When Workspaces Fail

Anti-Pattern 1: Complex Conditional Logic

Your configuration becomes littered with workspace checks:

# This is a code smell
resource "aws_vpc" "main" {
  cidr_block = terraform.workspace == "prod" ? "10.0.0.0/16" : (
                terraform.workspace == "staging" ? "10.1.0.0/16" : "10.2.0.0/16"
              )
  
  enable_dns_hostnames = terraform.workspace != "dev-old" ? true : false
  
  tags = {
    Environment = terraform.workspace
    # Wait, we need to map workspace names to display names...
    EnvironmentDisplay = terraform.workspace == "prod" ? "Production" : (
                           terraform.workspace == "staging" ? "Staging" : (
                             terraform.workspace == "qa" ? "QA" : "Development"
                           )
                         )
  }
}

Why this fails:

Configuration becomes unreadable
Adding a new environment requires updating every conditional
Testing becomes difficult (can't test prod changes without prod state)
Violates DRY—the same logic repeated everywhere

Better: Use directory structure with separate tfvars files.

Anti-Pattern 2: Workspaces as Environments in Shared Infrastructure

You have shared infrastructure (VPC, IAM, networking) that should exist once, not per workspace.

# This VPC will be created in EVERY workspace!
resource "aws_vpc" "main" {
  cidr_block = "10.0.0.0/16"
}

resource "aws_subnet" "public" {
  count = 2
  vpc_id = aws_vpc.main.id  # Different VPC per workspace!
}

Each workspace creates its own VPC, subnets, gateways. Workspaces were meant to be isolated, but here you want sharing.

Why this fails:

Resource duplication across workspaces
No central management of shared infrastructure
Inconsistent networking between environments
Higher costs (multiple VPCs)

Better: Separate "shared" infrastructure from "environment" infrastructure using different configurations/state files.

Anti-Pattern 3: Workspace Count Inflation

You have dozens of workspaces, but they're not truly independent:

terraform workspace list
  default
  dev-user-alice
  dev-user-bob
  dev-user-charlie
  feature-auth
  feature-payments
  feature-reporting
  qa-sprint-23
  qa-sprint-24
  prod
  prod-dr
  staging

Why this fails:

Workspace list becomes unmanageable
No clear naming convention enforced
Orphaned workspaces accumulate
No one knows what's still in use

Better: Implement a lifecycle policy or use separate configurations for truly independent stacks.

Anti-Pattern 4: Environment-Specific Backend Configuration

You can't easily use different backend configurations per workspace.

terraform {
  backend "s3" {
    # This is shared across ALL workspaces
    bucket = "company-terraform-state"
    key    = "my-app/terraform.tfstate"
    region = "us-west-2"
  }
}

But what if:

Prod state needs to be in a different AWS account?
Dev state should use local backend?
Staging needs KMS encryption with a specific key?

Workspaces share the backend configuration. You can't vary it per workspace without complex workarounds.

Better: Directory structure with separate backend configurations per environment.

🏛️ The Directory Structure Alternative

Environment-First Organization

Instead of workspaces, organize your code by environment:

infrastructure/
├── modules/
│   ├── networking/
│   ├── compute/
│   └── database/
├── environments/
│   ├── dev/
│   │   ├── main.tf
│   │   ├── variables.tf
│   │   ├── outputs.tf
│   │   ├── terraform.tfvars
│   │   └── backend.tf
│   ├── staging/
│   │   ├── main.tf
│   │   ├── variables.tf
│   │   ├── outputs.tf
│   │   ├── terraform.tfvars
│   │   └── backend.tf
│   └── prod/
│       ├── main.tf
│       ├── variables.tf
│       ├── outputs.tf
│       ├── terraform.tfvars
│       └── backend.tf

Each environment is a complete, independent Terraform configuration. They share modules but have separate state, separate variables, and separate backend configurations.

Benefits of Directory Structure

Aspect	Workspaces	Directory Structure
State isolation	✅ Separate state files	✅ Separate state files
Configuration sharing	✅ Same codebase	✅ Same modules
Environment-specific code	❌ Conditional logic required	✅ Can have different root modules
Backend configuration	❌ Shared across workspaces	✅ Independent per environment
Provider configuration	❌ Shared across workspaces	✅ Independent per environment
Variable files	⚠️ Manual selection	✅ Clear per-environment files
Plan/apply scope	✅ Workspace-specific	✅ Directory-specific
Access control	❌ Same state permissions	✅ Per-environment permissions
Team ownership	❌ Single team	✅ Different teams per env
Compliance separation	❌ All environments same controls	✅ Prod can have stricter controls

When Directory Structure Works Better

You need different provider configurations per environment:

# environments/dev/backend.tf
terraform {
  backend "s3" {
    bucket = "company-terraform-state-dev"
    key    = "my-app/terraform.tfstate"
    region = "us-west-2"
  }
}

# environments/prod/backend.tf
terraform {
  backend "s3" {
    bucket = "company-terraform-state-prod"  # Different bucket
    key    = "my-app/terraform.tfstate"
    region = "us-east-1"  # Different region
    
    assume_role = {
      role_arn = "arn:aws:iam::123456789012:role/TerraformStateAccess"
    }
  }
}

You need different provider configurations:

# environments/dev/providers.tf
provider "aws" {
  region = "us-west-2"
  # Dev uses shared credentials
}

# environments/prod/providers.tf
provider "aws" {
  region = "us-east-1"
  assume_role {
    role_arn = "arn:aws:iam::210987654321:role/TerraformExecution"
  }
}

You have complex environment-specific logic:

# environments/prod/main.tf
module "vpc" {
  source = "../../modules/networking"
  
  environment = "prod"
  vpc_cidr    = "10.0.0.0/16"
  
  # Production-specific settings
  enable_vpc_flow_logs = true
  flow_logs_destination = "arn:aws:s3:::company-flow-logs-prod"
  enable_nat_gateway = true
  nat_gateway_count = 3
}

# environments/dev/main.tf
module "vpc" {
  source = "../../modules/networking"
  
  environment = "dev"
  vpc_cidr    = "10.1.0.0/16"
  
  # Dev doesn't need expensive NAT gateways
  enable_nat_gateway = false
  enable_vpc_flow_logs = false
}

🔀 Hybrid Approaches

Workspaces Within Environments

Some teams use workspaces for temporary environments within a permanent environment:

environments/
├── dev/
│   ├── main.tf
│   ├── backend.tf
│   └── terraform.tfvars
├── staging/
│   └── ...
└── prod/
    └── ...

Within each environment, use workspaces for:

Feature branches
Developer sandboxes
Ephemeral test environments

cd environments/dev
terraform workspace new feature-123
terraform apply
# Test feature
terraform destroy
terraform workspace select default
terraform workspace delete feature-123

This gives you:

Permanent environments with clear, stable configuration
Ephemeral environments with workspace isolation
Shared infrastructure within the environment (VPC, etc.)
Isolated resources for the feature branch

Modules + Variable Files

The most scalable pattern:

Shared modules for all environments
Environment-specific root configurations
CI/CD pipelines that promote the same artifacts

terraform-repo/
├── modules/                  # Shared, versioned components
│   ├── networking/
│   ├── compute/
│   └── database/
├── global/                   # Cross-environment resources
│   ├── iam/
│   └── organizations/
└── stacks/                  # Reusable stack definitions
│   ├── web-service/
│   │   ├── main.tf
│   │   ├── variables.tf
│   │   └── outputs.tf
│   └── data-pipeline/
├── config/                  # Environment-specific values
│   ├── dev.yaml
│   ├── staging.yaml
│   └── prod.yaml
└── scripts/                 # Automation
    ├── deploy-stack.sh
    └── promote-stack.sh

Deployment script:

#!/bin/bash
# deploy-stack.sh

STACK=$1
ENVIRONMENT=$2

cd stacks/$STACK

# Select environment configuration
cp ../../config/$ENVIRONMENT.yaml terraform.tfvars.yaml

# Initialize with environment-specific backend
terraform init \
  -backend-config="bucket=company-terraform-state-$ENVIRONMENT" \
  -backend-config="key=$STACK/terraform.tfstate"

# Apply
terraform apply -auto-approve

🧠 Workspace Decision Framework

Use Workspaces When:

✅ You need ephemeral, parallel environments (feature branches, developer sandboxes)
✅ Your environments are truly identical with only scaling differences
✅ You're in early stages of a project and complexity is low
✅ Each workspace represents a fully independent stack
✅ You need to create/destroy environments frequently

Avoid Workspaces When:

❌ You have shared infrastructure that should exist once across environments
❌ Your environments require different provider configurations (different AWS accounts, regions)
❌ You need different backend configurations per environment
❌ You have complex conditional logic based on environment
❌ Different teams own different environments
❌ You need strict compliance separation between environments
❌ Your workspace list grows beyond 5-10 permanent workspaces

🎯 Real-World Scenarios

Scenario 1: Startup Growth

Phase 1: Single environment, monolith state

Just prod. No workspaces needed.

Phase 2: Dev, staging, prod with workspaces

terraform workspace new dev
terraform workspace new staging
terraform workspace new prod

Works well. Simple. One team manages everything.

Phase 3: Security team requires separate AWS accounts

❌ Workspaces can't use different provider configurations per workspace.
✅ Time to migrate to directory structure.

Migration path:

Create directory structure with separate backend configs
Use terraform state mv to move resources to new states
Update CI/CD pipelines
Archive workspace state

Scenario 2: Platform Team Serving Product Teams

Platform team provides reusable modules. Product teams deploy their own infrastructure instances.

Platform approach:

# Platform module (versioned, tested)
module "standard_service" {
  source = "git::https://github.com/platform/terraform-service-module?ref=v1.2.0"
  
  service_name = var.service_name
  environment  = var.environment
  team         = var.team
}

Product team deployment (using workspaces):

# Each service instance gets its own workspace
terraform workspace new payment-service-dev
terraform apply -var="service_name=payments" -var="environment=dev"

terraform workspace new payment-service-prod
terraform apply -var="service_name=payments" -var="environment=prod"

terraform workspace new notification-service-dev
terraform apply -var="service_name=notifications" -var="environment=dev"

This works because:

Each workspace is truly independent
No shared infrastructure between workspaces
Workspace names encode service + environment
Platform team controls module, product teams control instances

Scenario 3: Disaster Recovery

You need to deploy your infrastructure to a different region for DR testing.

With workspaces:

# Not ideal - workspaces don't change provider region
terraform workspace new dr-test
# Still deploying to us-west-2? Workspaces share provider config!

With directory structure:

cp -r environments/prod environments/dr-us-east
cd environments/dr-us-east
# Edit provider.tf to change region
# Edit backend.tf to change state location
terraform init
terraform apply

Better: Use Terragrunt or similar tooling for multi-region deployments.

📋 Workspace Commands Reference

# Workspace Management
terraform workspace new NAME          # Create and switch to new workspace
terraform workspace show              # Show current workspace
terraform workspace list              | List all workspaces
terraform workspace select NAME       # Switch to workspace
terraform workspace delete NAME       # Delete workspace (must be empty)

# Workspace Information
terraform workspace list | grep '*'   # Current workspace
echo $TF_WORKSPACE                  # Environment variable override

# Workspace-Aware Operations
terraform plan -out=plan.tfplan     # Plan for current workspace
terraform apply plan.tfplan         # Apply to current workspace
terraform destroy                   # Destroy current workspace resources

# Workspace Cleanup
terraform state list | xargs terraform state rm  # Remove all resources
terraform workspace delete NAME     # Now safe to delete

🧪 Practice Exercises

Exercise 1: Workspace Setup

Task: Create a simple configuration that uses workspaces to manage three environments.

# main.tf
terraform {
  required_version = ">= 1.5"
  
  backend "s3" {
    bucket = "workspace-practice-${random_string.suffix.result}"
    key    = "terraform.tfstate"
    region = "us-west-2"
  }
}

resource "random_string" "suffix" {
  length  = 8
  special = false
  upper   = false
}

resource "aws_s3_bucket" "state" {
  bucket = "workspace-practice-${random_string.suffix.result}"
  
  versioning {
    enabled = true
  }
}

resource "aws_s3_bucket" "app_data" {
  bucket = "app-data-${terraform.workspace}-${random_string.suffix.result}"
  
  tags = {
    Environment = terraform.workspace
  }
}

output "bucket_name" {
  value = aws_s3_bucket.app_data.bucket
}

Steps:

Initialize: terraform init
Create workspaces: terraform workspace new dev, staging, prod
Apply to each workspace
Verify separate buckets created
Clean up: terraform destroy in each workspace

Exercise 2: Workspace Conditional Logic

Task: Enhance the configuration with workspace-specific settings.

locals {
  # Workspace-specific configurations
  instance_count = {
    dev     = 1
    staging = 2
    prod    = 3
  }
  
  instance_type = {
    dev     = "t2.micro"
    staging = "t3.small"
    prod    = "t3.large"
  }
  
  enable_monitoring = {
    dev     = false
    staging = true
    prod    = true
  }
  
  # Current workspace settings with defaults
  current_instance_count = lookup(local.instance_count, terraform.workspace, 1)
  current_instance_type  = lookup(local.instance_type, terraform.workspace, "t2.micro")
  current_enable_monitoring = lookup(local.enable_monitoring, terraform.workspace, false)
}

resource "aws_instance" "web" {
  count = local.current_instance_count
  
  ami           = data.aws_ami.ubuntu.id
  instance_type = local.current_instance_type
  monitoring    = local.current_enable_monitoring
  
  tags = {
    Name        = "web-${terraform.workspace}-${count.index + 1}"
    Environment = terraform.workspace
  }
}

Question: What happens when you create a workspace named "qa" that's not in the lookup maps?

Answer: It uses the default values (1, "t2.micro", false). This is both a feature and a risk.

Exercise 3: Workspace to Directory Migration

Task: Migrate an existing workspace-based configuration to a directory structure.

Starting point:

project/
├── main.tf
├── variables.tf
├── outputs.tf
└── terraform.tfstate.d/
    ├── dev/
    ├── staging/
    └── prod/

Migration steps:

Step 1: Create directory structure

mkdir -p environments/{dev,staging,prod}

Step 2: Copy configuration to each environment

cp main.tf variables.tf outputs.tf environments/dev/
cp main.tf variables.tf outputs.tf environments/staging/
cp main.tf variables.tf outputs.tf environments/prod/

Step 3: Create environment-specific tfvars files

# environments/dev/terraform.tfvars
environment = "dev"
instance_type = "t2.micro"
instance_count = 1

# environments/staging/terraform.tfvars
environment = "staging"
instance_type = "t3.small"
instance_count = 2

# environments/prod/terraform.tfvars
environment = "prod"
instance_type = "t3.large"
instance_count = 3

Step 4: Create environment-specific backend configurations

# environments/dev/backend.tf
terraform {
  backend "s3" {
    bucket = "company-terraform-state-dev"
    key    = "my-app/terraform.tfstate"
    region = "us-west-2"
  }
}

# environments/prod/backend.tf
terraform {
  backend "s3" {
    bucket = "company-terraform-state-prod"
    key    = "my-app/terraform.tfstate"
    region = "us-east-1"
    assume_role = {
      role_arn = "arn:aws:iam::123456789012:role/TerraformStateAccess"
    }
  }
}

Step 5: Migrate state

# For dev
cd environments/dev
terraform init -reconfigure
terraform state mv -state=../../terraform.tfstate.d/dev/terraform.tfstate -state-out=terraform.tfstate aws_vpc.main aws_vpc.main
# ... move all resources

# For staging (similar)
# For prod (similar)

✅ Workspace Best Practices Checklist

When Using Workspaces

Use workspaces for parallel, identical environments — Not for environments with fundamental differences
Keep workspace-specific logic minimal — Extract to locals or variable lookups
Name workspaces consistently — dev, staging, prod, feature-123, user-abc
Document workspace naming convention — So everyone follows the same pattern
Clean up old workspaces — Implement lifecycle policy (delete after 30 days)
Use terraform.workspace in resource names — To avoid naming collisions
Test workspace changes in isolation — Create a test workspace before modifying production

When Not Using Workspaces

Use directory structure for permanent environments — Clear separation, independent configuration
Share modules, not root configurations — DRY code, separate state
Implement promotion pipelines — Promote the same artifacts, not reapply configuration
Use different AWS accounts for different environments — Strongest isolation
Consider Terragrunt — For complex, multi-environment, multi-team setups

🎓 Summary: Workspaces Are a Tool, Not a Strategy

Workspaces solve a specific problem: managing multiple state files for the same configuration. They are not a complete environment management strategy.

	Workspaces	Directory Structure
Configuration	Single root module	Multiple root modules
State isolation	✅ Different state files	✅ Different state files
Backend flexibility	❌ Shared backend config	✅ Per-environment backend
Provider flexibility	❌ Shared provider config	✅ Per-environment providers
Code duplication	❌ Minimal	⚠️ Some duplication
Complexity ceiling	Low (simple envs)	High (complex envs)
Team scale	1-5 environments, 1 team	5+ environments, multiple teams

The right tool depends on your situation:

Startup, early stage, simple infrastructure → Workspaces
Growing team, multiple permanent environments → Directory structure
Enterprise, multiple teams, compliance requirements → Terragrunt or custom solution
Platform team, product teams → Modules + Workspaces (per team/instance)

Remember: Workspaces don't eliminate environment differences—they just relocate them from separate directories to conditional logic. Choose the approach that makes your specific differences clearest and most maintainable.

🔗 Master Terraform Environments with Hands-on Labs

The best way to understand workspaces is to use them—and then migrate away from them when you outgrow them.

👉 Practice workspace management, environment isolation, and migration strategies in our interactive labs at:
https://devops.trainwithsky.com/

Our platform provides:

Workspace creation and management exercises
Multi-environment configuration challenges
Workspace → directory migration simulations
Terragrunt introduction labs
Real-world environment strategy design workshops

Frequently Asked Questions

Q: Can I use workspaces with different AWS accounts?

A: Not directly. Workspaces share the same provider configuration. You can use conditional logic to switch provider configs based on workspace, but this is messy and error-prone. Better to use directory structure with separate provider configurations.

Q: How do I manage secrets across workspaces?

A: Workspaces don't help with secrets. Use environment variables (TF_VAR_) or a secrets manager. For workspace-specific secrets, use different secret paths per workspace (e.g., secret/dev/db_password vs secret/prod/db_password).

Q: What happens to workspaces when I delete the .terraform directory?

A: Workspace definitions are stored in .terraform/workspace.json and terraform.tfstate.d/. If you delete these, Terraform forgets about your workspaces. You can recover by re-initializing and using terraform workspace select—the actual state files still exist in your backend.

Q: Can I rename a workspace?

A: No, there's no direct rename command. You must create a new workspace, move resources via terraform state mv, and delete the old workspace.

Q: How many workspaces should I have?

A: For permanent environments, keep it under 5-10. For ephemeral environments, any number is fine as long as you have a cleanup policy. Workspaces are cheap, but workspace list clutter is not.

Q: Should I use workspaces for disaster recovery?

A: Generally no. DR environments often require different regions, different provider configurations, and different state backends—all of which workspaces don't support well.

Q: What's the difference between Terraform workspaces and Terraform Cloud workspaces?

A: They're completely different concepts with the same name. Terraform Cloud workspaces are independent configurations with their own state, variables, and runs. Terraform CLI workspaces are multiple state files sharing one configuration. This naming collision causes endless confusion.

Still unsure whether workspaces are right for your team? Facing a specific environment management challenge? Share your scenario in the comments below—our community has navigated these tradeoffs before and can help! 💬

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