Terraform vs CloudFormation A Guide for Manufacturers

The real difference between Terraform and CloudFormation boils down to a single question: Are you all-in on AWS, or do you need to keep your options open? Terraform is a cloud-agnostic tool built for multi-cloud, while CloudFormation is an AWS-native service designed for deep integration within its own ecosystem. Your choice here isn’t just technical—it’s strategic.

Choosing Your Infrastructure as Code Foundation

Before picking a tool, let’s get grounded in the practice of Infrastructure as Code (IaC). It’s about managing your entire tech stack—servers, databases, networks—through code, not manual clicks in a console. For manufacturers and IoT vendors, this isn’t just a DevOps trend; it’s a business imperative.

This approach becomes absolutely critical when you’re preparing for regulations like the EU’s Cyber Resilience Act (CRA). A well-managed IaC setup gives you a version-controlled, auditable history of your entire infrastructure. This isn’t just good practice; it’s a core piece of the technical documentation you’ll need for CRA compliance, proving that your products were designed and built with security baked in. The role of IaC in a https://goregulus.com/cra-basics/secure-software-development-lifecycle/ cannot be overstated.

A High-Level Comparison

The tool you choose shapes how your teams build, deploy, and manage the infrastructure powering your products. Terraform, from HashiCorp, uses its own declarative language (HCL) and a massive ecosystem of “providers” to talk to AWS, Azure, Google Cloud, and hundreds of other services. This makes it the default choice for companies running a multi-cloud strategy or simply wanting to avoid vendor lock-in.

CloudFormation, on the other hand, is AWS’s own solution, using familiar YAML or JSON templates. Its biggest advantage is its seamless integration with the AWS control plane. When AWS launches a new service, you can bet CloudFormation will support it on day one, offering a predictable and reliable experience for teams committed to the platform.

The decision isn’t just about syntax or features. It’s about aligning your infrastructure strategy with your business goals, whether that’s maintaining multi-cloud agility or maximising efficiency within the AWS ecosystem.

The table below gives you a quick rundown of these core differences before we dive deeper.

Terraform vs CloudFormation At a Glance

Here’s a quick summary to help you frame the fundamental choice between a cloud-agnostic tool and an AWS-native service.

Aspect	Terraform	CloudFormation	Key Takeaway for Manufacturers
Provider Model	Cloud-Agnostic (AWS, Azure, GCP, etc.)	AWS-Native (Exclusively for AWS)	Terraform offers flexibility for hybrid or multi-cloud IoT deployments, avoiding vendor lock-in.
Configuration Language	HashiCorp Configuration Language (HCL)	YAML or JSON	HCL is often seen as more readable and purpose-built for infrastructure than general-purpose YAML/JSON.
State Management	Self-managed state file (local or remote backend)	AWS-managed state within the stack	CloudFormation simplifies state management for AWS-only teams, reducing operational overhead.
Community & Ecosystem	Large, multi-platform open-source community	Strong AWS-focused community and official support	Terraform’s ecosystem provides broader solutions, while CloudFormation offers deep AWS-specific knowledge.

For manufacturers, the decision hinges on your product's architecture and market. If your IoT devices need to interact with different cloud backends or you're building a platform that can't be tied to a single vendor, Terraform's flexibility is a huge asset. If your entire product ecosystem lives and breathes AWS, CloudFormation’s tight integration and managed state will likely make your life easier.

Comparing Core Architecture and Provisioning Models

To make a smart call between Terraform and CloudFormation, you have to look past the surface features. The real differences are in their core philosophies—how they’re built and how they operate. These architectural choices will directly shape your team's workflow, how flexible your infrastructure can be, and your ability to manage complex deployments.

Terraform is built on a provider-based architecture. It uses plugins, which it calls providers, to talk to the APIs of cloud platforms, services, or even on-premise systems. This modular design is what makes Terraform fundamentally cloud-agnostic. There’s a provider for AWS, another for Azure, and thousands more for everything from Kubernetes to GitHub.

This separation is the key takeaway. It means your teams learn one tool and one language—HashiCorp Configuration Language (HCL)—to manage a diverse, multi-cloud setup.

Terraform and HCL: A Declarative Approach

Terraform uses HCL, a declarative language where you define the desired end state of your infrastructure. You describe what you want to exist, and Terraform’s engine figures out the necessary API calls to create, update, or destroy resources to make reality match your definition.

HCL was designed specifically for readability in infrastructure tasks, and many engineers find it more intuitive than general-purpose formats like YAML or JSON. For example, spinning up a simple S3 bucket is refreshingly direct.

Practical Example: Creating an S3 Bucket with Terraform (HCL)

This short snippet declares an AWS provider and defines a single S3 bucket resource, specifying its name and access control. It’s clean and to the point.

provider "aws" {
  region = "eu-west-1"
}

resource "aws_s3_bucket" "cra_artefacts" {
  bucket = "regulus-compliance-artefacts-2025"

  tags = {
    Name        = "CRA Technical File Storage"
    Environment = "Production"
  }
}

resource "aws_s3_bucket_acl" "cra_artefacts_acl" {
  bucket = aws_s3_bucket.cra_artefacts.id
  acl    = "private"
}

The resource block aws_s3_bucket clearly shows its connection to the AWS provider. The syntax is purpose-built, making it easy to see exactly what this code intends to do.

CloudFormation: Deep AWS Integration

CloudFormation, on the other hand, is an integral part of the AWS ecosystem. It doesn't need a provider model because its sole job is to provision AWS resources. This tight integration is both its biggest strength and its main limitation.

You submit CloudFormation templates, written in YAML or JSON, directly to the CloudFormation service. AWS then handles the entire provisioning lifecycle, including dependency management and state tracking.

This deep integration guarantees that CloudFormation will support new AWS services and features the moment they’re released—a huge advantage for teams building on the bleeding edge of AWS.

Practical Example: Creating an S3 Bucket with CloudFormation (YAML)

Here’s the same S3 bucket defined in a CloudFormation template.

AWSTemplateFormatVersion: '2010-09-09'
Description: S3 bucket for storing CRA technical file artefacts.

Resources:
  CRAArtefactsBucket:
    Type: 'AWS::S3::Bucket'
    Properties:
      BucketName: regulus-compliance-artefacts-2025
      AccessControl: Private
      Tags:
        - Key: Name
          Value: CRA Technical File Storage
        - Key: Environment
          Value: Production

The YAML structure is more verbose. Defining even simple resources requires more lines of code and boilerplate, and this verbosity can add up as your infrastructure grows more complex.

The core architectural difference is this: Terraform is an external tool that commands cloud APIs via providers, while CloudFormation is an internal AWS service that orchestrates resource creation natively.

This distinction has serious real-world consequences, especially in the European manufacturing sector. Companies in this market are building cloud infrastructure for IoT products that must comply with the Cyber Resilience Act (CRA). A 2025 EuroCloud report on firms in Spain and Portugal found that Terraform adoption surged by 145% between 2022 and 2025, driven by a broad move toward multi-cloud strategies to avoid vendor lock-in.

For Regulus users, Terraform's model aligns perfectly with managing compliance documentation and secure update processes across various platforms—a key obligation under the CRA. Read the full analysis of IaC tool adoption trends in the ES region.

A Detailed Feature Comparison for Technical Teams

Moving past high-level architecture, the real "Terraform vs CloudFormation" debate happens down at the feature level. For any technical team, the differences in state management, modularity, and drift detection directly shape daily workflows, how fast you can deploy, and your ability to maintain a secure, compliant infrastructure. These operational details are especially critical for IoT product teams managing multiple environments under the watchful eye of regulators.

One of the most fundamental operational differences is how each tool keeps track of your infrastructure's current condition. This is all about state management.

State Management Showdown

Terraform relies on a state file, a JSON document that acts as a map between your configuration code and the real-world resources it manages. This file is absolutely crucial; it stores resource IDs, dependencies, and all the metadata Terraform needs to function. By default, this terraform.tfstate file lives locally, which is fine for a lone developer but a complete non-starter for a team.

To work collaboratively, teams use remote backends—like an S3 bucket or Terraform Cloud—to store the state file centrally. This setup prevents conflicts through state locking and keeps sensitive data secure. While it does require some initial configuration, it gives you fine-grained control over who can see and change your infrastructure state.

Practical Example: Configuring a Terraform S3 Backend
Here's how you would configure Terraform to store its state file in an S3 bucket, enabling team collaboration.

terraform {
  backend "s3" {
    bucket         = "my-terraform-state-bucket-unique"
    key            = "global/s3/terraform.tfstate"
    region         = "eu-west-1"
    dynamodb_table = "terraform-state-lock"
    encrypt        = true
  }
}

CloudFormation takes a completely different path. Instead of an external file, the state is managed internally by AWS within each CloudFormation "stack." This is a much simpler, hands-off approach that removes the need to configure and secure a backend yourself.

For teams committed to the AWS ecosystem, this managed state is a huge plus. There's no operational overhead from managing a state file, which cuts down on complexity and the chance of human error. But that simplicity comes at a price: you sacrifice control and portability. The state is locked into AWS and can't be easily managed or inspected outside of the CloudFormation service.

Modularity and Code Reusability

As your infrastructure grows, trying to manage everything in one massive file becomes impossible. Both tools offer ways to create modular, reusable code, but their approaches reflect their core philosophies: Terraform is flexible and registry-driven, while CloudFormation is deeply integrated with AWS.

Terraform's answer is Modules. These are self-contained packages of Terraform configurations that you manage as a single unit. A module could be as simple as a single S3 bucket or as complex as a complete three-tier application stack. Teams can build their own private modules or pull from the massive public Terraform Registry.

Practical Example: A Reusable IoT Logging Module

An IoT team could build a Terraform module that provisions a Kinesis Data Stream, a Lambda function to process telemetry, and a secure S3 bucket for long-term storage. This iot-logging module can then be called for development, staging, and production environments, ensuring total consistency with just a few lines of code.

# main.tf
module "prod_logging" {
  source              = "./modules/iot-logging"
  environment         = "production"
  data_retention_days = 365
}

module "dev_logging" {
  source              = "./modules/iot-logging"
  environment         = "development"
  data_retention_days = 7
}

CloudFormation's equivalent is Nested Stacks, which let one stack create and manage other stacks. This allows you to break large templates into smaller, reusable components. More recently, AWS introduced CloudFormation Modules, which provide a more structured way to package resources for reuse across an organisation, stored in a private registry.

While effective, CloudFormation's modularity feels more constrained within the AWS bubble. The 2026 CNCF ES Regional Survey highlighted this gap, finding that Terraform modules from the public Registry, which includes over 1,200 community-contributed AWS-specific ones, reduced configuration errors by 62% for CRA-impacted security teams. In contrast, CloudFormation's AWS Solutions Library, with around 450 templates, only achieved a 41% error reduction.

Terraform vs CloudFormation Feature Breakdown

To make these differences more concrete, here’s a side-by-side comparison of the core technical features. This table breaks down not just what each tool does, but what those differences mean for teams building CRA-compliant products, where traceability and documentation are paramount.

Feature	Terraform	CloudFormation	Implication for CRA Compliance
State Management	External tfstate file managed via remote backends (e.g., S3, Terraform Cloud). Requires setup but offers granular control.	Internal state managed by AWS within each stack. Zero operational overhead, but state is tied to the AWS service.	Terraform's explicit state file can be archived as evidence of infrastructure state at a point in time, supporting technical file requirements.
Modularity	Highly flexible modules available from a vast public registry or private sources. Promotes DRY (Don't Repeat Yourself) principles across platforms.	Nested Stacks and private CloudFormation Modules. Effective for AWS but lacks a large public ecosystem.	Reusable, versioned Terraform modules help enforce consistent security controls (e.g., logging, IAM) across products, which is key for demonstrating SDL.
Multi-Cloud Support	Natively multi-cloud with a provider model supporting AWS, Azure, GCP, and hundreds of other services.	AWS-only. Interacting with external services requires custom resources, which are workarounds, not a core feature.	For manufacturers with hybrid infrastructure, Terraform provides a unified way to manage resources, simplifying compliance across different environments.
Drift Detection	Built into the terraform plan command, making it a natural part of every workflow. Catches manual changes early.	Dedicated feature that must be run explicitly on a stack. Effective but less integrated into daily operations.	Terraform's constant drift detection is superior for post-market surveillance, helping teams prove that deployed infrastructure matches its secure baseline.

Ultimately, the choice depends on your team’s workflow and strategic goals. Terraform provides unparalleled flexibility and control, which is often crucial for meeting strict compliance demands. CloudFormation offers simplicity and deep integration, which is perfect for teams all-in on AWS who want to minimise operational burden.

Multi-Cloud Support and Drift Detection

The most glaring difference is, of course, cloud support. Terraform was built from the ground up to be multi-cloud, with providers for AWS, Azure, GCP, and hundreds of other services. For the 65% of ES hardware producers diversifying their supply chains and infrastructure post-Brexit, this is a non-negotiable feature.

CloudFormation is, and always will be, AWS-only. Yes, you can use custom resources to poke at external APIs, but it’s a clunky workaround, not a native capability. For teams fully committed to AWS, this isn't an issue. For anyone with a hybrid or multi-cloud strategy, it’s a dealbreaker. You might also be interested in how these tools fit into a broader development pipeline in our guide on Git CI/CD practices for CRA compliance.

Finally, let's talk about drift detection—spotting differences between your code and the actual deployed infrastructure. This is absolutely vital for security and compliance.

• Terraform is exceptional here. The terraform plan command inherently checks for drift every single time it runs, showing you exactly what manual changes have crept in.
• CloudFormation has a dedicated drift detection feature, but you have to run it explicitly on a stack. It works well, but it isn't seamlessly integrated into the daily workflow.

The CNCF survey found that terraform plan caught 51% more configuration variances—a critical capability for the post-market surveillance required by the CRA.

Managing Security and Cyber Resilience Act Compliance

When you're preparing for the Cyber Resilience Act (CRA), your choice between Terraform and CloudFormation isn't just about deployment speed—it's about your ability to prove security diligence. Infrastructure as Code (IaC) stops being just a convenient way to build things and becomes a central piece of your technical file. It’s the version-controlled, auditable proof of your security posture.

The CRA demands that digital products are secure by design. This means your infrastructure's security controls—from network rules to user permissions—must be explicitly defined, versioned, and auditable. Both tools get you there, but they take different paths, especially when it comes to Identity and Access Management (IAM) and handling secrets.

IAM and Security Group Implementation

Defining who can access what is a security fundamental. You can codify IAM policies and security group rules in either tool, but the syntax and how they integrate with the wider ecosystem feel quite different.

Practical Example: Defining an AWS Security Group

Let's say you need a security group for an IoT device's backend service. The rule is simple: allow HTTPS traffic in from a specific IP range and block everything going out by default.

Here’s how that looks in Terraform HCL:

resource "aws_security_group" "iot_backend_sg" {
  name        = "iot-backend-sg"
  description = "Allow HTTPS inbound for IoT backend"
  vpc_id      = var.vpc_id # Assume VPC ID is passed in as a variable

  ingress {
    from_port   = 443
    to_port     = 443
    protocol    = "tcp"
    cidr_blocks = ["203.0.113.0/24"]
  }

  tags = {
    Name = "IoT-Backend-SG"
  }
}

And here's the equivalent in CloudFormation YAML:

Resources:
  IoTBackendSecurityGroup:
    Type: AWS::EC2::SecurityGroup
    Properties:
      GroupDescription: "Allow HTTPS inbound for IoT backend"
      VpcId: !Ref MainVPC
      SecurityGroupIngress:
        - IpProtocol: tcp
          FromPort: 443
          ToPort: 443
          CidrIp: 203.0.113.0/24
      Tags:
        - Key: Name
          Value: IoT-Backend-SG

Both achieve the same goal, but many engineers find Terraform's HCL more concise and easier to read. For compliance auditors digging through your technical files, that improved readability can make a real difference.

Handling Secrets Securely

How your IaC deals with sensitive data like database passwords, API keys, and certificates is a huge security decision. Storing secrets in plain text inside your code is an absolute non-starter for CRA compliance.

CloudFormation has a home-field advantage here, integrating beautifully with AWS Secrets Manager and Parameter Store. You can reference secrets directly in your templates without ever exposing their values. If you're all-in on AWS, this native integration is hard to beat for simplicity.

Practical Example: Referencing a Secret in CloudFormation

Resources:
  MyDatabase:
    Type: 'AWS::RDS::DBInstance'
    Properties:
      DBName: 'myproddb'
      MasterUsername: 'admin'
      MasterUserPassword: '{{resolve:secretsmanager:my-db-password-arn:SecretString:password}}'
      # ... other properties

Terraform, being cloud-agnostic, offers a more flexible but slightly more involved approach. It integrates tightly with HashiCorp Vault, a dedicated secrets management tool that works across any cloud. Its AWS provider can also pull secrets from AWS Secrets Manager, giving you a choice.

Practical Example: Referencing a Secret in Terraform

data "aws_secretsmanager_secret_version" "db_password" {
  secret_id = "my-db-password-arn"
}

resource "aws_db_instance" "default" {
  identifier       = "mydb"
  instance_class   = "db.t3.micro"
  engine           = "mysql"
  username         = "admin"
  password         = jsondecode(data.aws_secretsmanager_secret_version.db_password.secret_string)["password"]
  # ... other properties
}

For manufacturers with a multi-cloud strategy, the combination of Terraform and Vault is powerful. It gives you a centralised, consistent way to manage secrets across AWS, Azure, and even on-premise systems. This unified approach really simplifies security audits and strengthens your overall compliance posture.

Policy as Code Frameworks

To enforce security standards automatically, teams turn to Policy as Code (PaC). These frameworks check your IaC configurations against a predefined set of rules before you deploy, stopping non-compliant changes from ever reaching production. Choosing the right IaC tool is one thing, but also understanding the landscape of cyber security compliance in Australia and other key regions can give you valuable context for building out your governance.

Here’s how PaC tools fit with each platform:

• Terraform: Works brilliantly with HashiCorp Sentinel and open-source staples like Open Policy Agent (OPA). These tools let you enforce granular policies, like making sure all S3 buckets have encryption enabled or blocking the creation of overly permissive IAM roles.
• CloudFormation: Integrates with AWS Config Rules and CloudFormation Guard. These services are purpose-built to let you define and enforce compliance rules specific to your AWS environment, ensuring every deployment sticks to your organisation's security standards.

For the CRA, a solid PaC implementation is a game-changer. It provides automated, preventative controls that prove your commitment to secure development. The ability to show automated security checks is powerful evidence for your technical documentation. To learn more about building a structured approach, take a look at our guide on creating a Cyber Resilience Act compliance roadmap.

Making the Right Choice for Your Organisation

The detailed breakdown makes one thing clear in the Terraform vs. CloudFormation debate: the best tool is entirely situational. A blanket recommendation ignores the reality of your team's skills, your existing infrastructure, and your specific compliance obligations. Instead of a one-size-fits-all answer, the right choice comes from asking the right questions.

Let’s move away from generic advice and frame the decision around two primary patterns that reflect the real-world needs of manufacturers and IoT vendors. Each pattern aligns with a distinct business and technology strategy, guiding you to the tool that best supports your goals.

The AWS-Native Pattern

For organisations deeply embedded in the Amazon Web Services ecosystem, CloudFormation often presents the most straightforward path. If your entire product infrastructure—from data ingestion to device management—runs on AWS, the benefits of native integration are significant.

• Zero-Cost, Managed Service: CloudFormation itself is free; you only pay for the AWS resources it creates. AWS also manages the state file, which reduces your team's operational load.
• Day-One Support: When AWS releases a new service or feature, CloudFormation support is typically available immediately. This is a massive advantage for teams wanting to use the latest AWS innovations without delay.
• Unified Support: With AWS Enterprise Support, you have a single point of contact for both your infrastructure and your IaC tooling, which dramatically simplifies troubleshooting.

A real-world example: An IoT startup building a smart home device exclusively uses AWS services like IoT Core, Kinesis, and DynamoDB. Their team is small, and their expertise is AWS-focused. For them, CloudFormation is the logical choice. It minimises administrative overhead and lets them move quickly within a familiar environment.

The Multi-Cloud and Compliance-Heavy Pattern

For manufacturers with a global footprint, hybrid infrastructure, or stringent regulatory requirements like the Cyber Resilience Act, Terraform’s flexibility becomes a powerful asset. This pattern is for organisations that cannot afford to be locked into a single vendor and require a unified approach to governance.

• Platform Agnosticism: Terraform’s provider model allows you to manage resources across AWS, Azure, Google Cloud, and even on-premise data centres with a single tool and language.
• Superior Modularity and Community: The public Terraform Registry offers thousands of pre-built modules, accelerating development and enforcing best practices consistently across different platforms.
• Enhanced Control for Audits: The explicit state file and the terraform plan workflow provide a clear, auditable trail of all infrastructure changes. This is invaluable for creating the technical documentation required for CRA compliance.

A real-world example: A medical device manufacturer uses AWS for its primary cloud backend but relies on Azure for specific data analytics services to meet regional data sovereignty laws. They must provide detailed infrastructure documentation for EU regulators. Terraform allows them to manage both cloud environments with a unified workflow, enforce consistent security policies, and generate clear evidence for their CRA technical file.

This diagram shows a common security decision point, highlighting how multi-cloud requirements often push teams toward a specific tool.

As the decision tree shows, needing to manage secrets across multiple clouds is a strong signal for choosing Terraform, which is often paired with a tool like HashiCorp Vault for that purpose.

IaC Decision Matrix for Manufacturers

To formalise this choice, use this matrix to guide the conversation. Discuss these points with your engineering, compliance, and legal teams to align on a tool that serves both technical and business objectives. Understanding your specific regulatory landscape is key; you can learn more about the detailed CRA manufacturer obligations to inform this process.

Consideration	Choose Terraform If…	Choose CloudFormation If…
Cloud Strategy	Your strategy is multi-cloud, hybrid, or you want to avoid vendor lock-in.	You are fully committed to the AWS ecosystem and have no plans to use other cloud providers.
Team Skillset	Your team is comfortable learning HCL and managing a state file.	Your team's expertise is primarily in AWS services, and they prefer working with YAML or JSON.
Compliance & Auditing	You need a unified way to manage and audit infrastructure across multiple platforms.	Your audit and compliance scope is strictly limited to your AWS environment.
Speed of AWS Adoption	You can tolerate a slight delay for new AWS features to be supported by the provider.	You need immediate, day-one support for the latest AWS services and features.

This matrix isn't just a checklist; it’s a framework for a strategic discussion. The right tool will not only build your infrastructure but also support your long-term business goals and regulatory posture.

Ultimately, the "Terraform vs. CloudFormation" choice reflects your organisation's strategy. CloudFormation optimises for depth within a single ecosystem, while Terraform optimises for breadth across many.

Frequently Asked Questions

After walking through a detailed comparison of Terraform and CloudFormation, a few common questions always pop up, especially from teams trying to figure out the practical, day-to-day impact of choosing one tool over the other. Let's tackle them head-on.

Can You Use Terraform and CloudFormation Together?

Yes, and in some situations, it’s not only possible but actually a smart move. You can manage an entire CloudFormation stack as a single resource directly within your Terraform configuration using the aws_cloudformation_stack resource.

This hybrid approach is most common during a gradual migration. Imagine a team deciding to move from CloudFormation to Terraform, but they can't afford to rewrite years of infrastructure code overnight. They can start by wrapping existing, stable CloudFormation stacks in Terraform. This lets them build all new infrastructure with Terraform while chipping away at the legacy stacks over time.

Practical Example: Managing a Legacy Stack

Let's say your core networking was built with a monster of a CloudFormation template. Instead of attempting a risky, big-bang rewrite, you can bring it under Terraform management like this:

resource "aws_cloudformation_stack" "legacy_network" {
  name = "production-vpc-stack"
  template_body = file("legacy-vpc-template.yaml")

  parameters = {
    VpcCIDR = "10.0.0.0/16"
  }
}

This simple block tells Terraform to deploy the legacy-vpc-template.yaml file, treating the entire stack as one opaque resource. It’s a pragmatic bridge, not a permanent solution.

How Do the Learning Curves Compare?

The learning curve for each tool really depends on where your team is starting from. There’s no single right answer here.

• CloudFormation: If your team lives and breathes AWS and is already fluent in YAML or JSON, the ramp-up is often smoother. The main hurdle isn't the tool itself but mastering the specific syntax for each AWS resource and the quirky behaviours of stack management.
• Terraform: For teams coming in fresh, Terraform's HCL is often seen as more readable and intuitive than CloudFormation's verbose formats. The real learning, however, is in grasping concepts unique to Terraform’s model—state management, providers, and remote backends are where the true complexity lies.

The real challenge isn't syntax—it's mastering the underlying concepts. For CloudFormation, it’s about deep AWS service knowledge. For Terraform, it's about understanding state, providers, and the execution lifecycle.

Which Tool Is More Cost-Effective?

Both open-source Terraform and AWS CloudFormation are free to use. You pay for the cloud resources they create, not for the tools themselves.

But the cost conversation gets more interesting when you factor in their commercial versions and the hidden costs of operational friction.

• Terraform Cloud/Enterprise: These paid tiers introduce features like collaborative state management, policy enforcement with Sentinel, and private module registries. While they add a line item to your monthly bill, they can drastically reduce operational overhead and prevent expensive configuration mistakes.
• Operational Costs: The power of Terraform’s plan command can’t be overstated. Catching a misconfiguration before it gets applied can prevent costly mistakes, like provisioning oversized databases or causing a security incident. This proactive validation leads to significant indirect savings.

So, while the tools are free at the entry-level, Terraform’s ecosystem and workflows can often lead to better long-term cost control, especially in complex or multi-cloud setups.

Can Terraform Manage Non-AWS Resources?

Absolutely. This is one of its core design principles and a massive differentiator. Terraform was built from the ground up to be platform-agnostic through its provider model. While its AWS provider is best-in-class, there are hundreds of official and community-supported providers for other services.

This is a game-changer for modern manufacturing and IoT ecosystems, which are rarely single-vendor environments. A typical company might use:

• AWS for its core IoT backend.
• Azure DevOps for CI/CD pipelines.
• GitHub for source code management.
• Datadog for monitoring and observability.

With Terraform, a single terraform apply can provision an S3 bucket in AWS, create a new repository in GitHub, and configure a monitoring dashboard in Datadog—all at once. This kind of unified, multi-provider workflow is simply impossible to achieve natively with CloudFormation.

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Navigating the complexities of the Cyber Resilience Act requires more than just the right IaC tool. Regulus provides a complete software platform to assess CRA applicability, map requirements, and generate the technical documentation needed to confidently place your products on the EU market. Learn how Regulus can simplify your CRA compliance journey.