What you'll learn. In this Pulumi vs. Terraform comparison, you'll see how Terraform's domain-specific language (HashiCorp Configuration Language, i.e., HashiCorp Configuration Language HCL) differs from Pulumi's use of general-purpose programming languages, and where Pulumi and Terraform shine or struggle in real use cases, from simple stacks to complex deployments.

infrastructure-as-code (IaC) has changed how you manage infrastructure, moving you away from clicking around cloud consoles and copy-pasting shell scripts and toward repeatable infrastructure definitions that encode everything from networks to Kubernetes resources as versioned code.

When you look at modern infrastructure management today, most roads converge on two names that come up in conversations about managing cloud infrastructure across multiple cloud providers: Terraform and Pulumi.

Both tools help you write infrastructure code, model the desired infrastructure state of your cloud resources, and keep that desired state in sync with reality. Terraform and Pulumi both work across major cloud providers, integrate with DevOps tools, and promise multi-cloud infrastructure management at scale. They just make very different bets on configuration language, programming model, and how tightly infrastructure should be coupled to your application code.

If you're choosing between Pulumi and Terraform, you're really choosing a way of thinking about infrastructure: about where software engineering practices stop and infrastructure management begins, and about how much power you want to unlock versus how much complexity you are willing to carry.

Read on for hands-on examples that provision resources on AWS:

Learn which key differences actually matter when you manage infrastructure every day
How each IaC tool models infrastructure-as-code and state management
How their provider ecosystems and cloud provider support compare
How Terrateam helps you secure and govern your Terraform workflows without bolting on yet another SaaS.

What is Terraform?

Terraform is an open-source tool used to manage cloud infrastructure. According to Stack Overflow's 2025 Developer Survey, 17.8% of developers use it for cloud development.

Its primary purpose is to define and provision infrastructure using code, which allows you to automate the creation, modification, and management of cloud resources. Whether you're working with AWS, Azure, Google Cloud, or other major cloud providers now, Terraform makes it possible to control all aspects of your infrastructure in a consistent and repeatable way.

One of the key features of Terraform is its declarative syntax. Instead of writing scripts that tell the system exactly what steps to take, you simply define what you want your desired infrastructure state to look like, what resources you need, and the configurations for those resources. Terraform then takes care of figuring out the necessary steps to make your current infrastructure match the desired state. For example, if you need to set up a web server on AWS, you describe that server in a configuration file, and Terraform will automatically create and configure it for you.

Terraform interacts with cloud providers through providers. Providers are plugins that allow Terraform to manage resources for specific platforms. For example, the AWS provider allows you to manage AWS services like EC2 instances, S3 buckets, and Lambda functions. Similarly, providers exist for other cloud platforms like Azure and Google Cloud, making it easy to manage infrastructure across multiple cloud services and environments with a single IaC tool.

Terraform in practice

Terraform started by standardizing how you describe cloud infrastructure. Instead of wiring together cloud provider consoles, custom scripts, and third-party tools, you describe infrastructure resources in declarative code using HashiCorp Configuration Language, then let Terraform calculate the plan to move from current infrastructure state to desired state.

The configuration language is intentionally constrained, so you focus on outcomes, not the exact steps to get there.

Terraform uses providers as the bridge to real cloud services. Terraform providers are plugins that understand how to manage resources for a specific cloud provider or platform. The AWS provider can manage EC2, S3, IAM, and hundreds of other AWS services; the Google Cloud provider manages GCP services; the Azure provider manages Azure resources; there are providers for Kubernetes resources, Datadog, GitHub, and thousands of other systems.

This provider ecosystem, and the way Terraform supports both cloud providers and SaaS APIs, is a big part of why Terraform became the default choice for many teams.

At its core, Terraform is a declarative language around a graph of infrastructure resources. You describe the desired state, Terraform computes a change set, runs terraform plan to show you what it intends to do, and then applies that plan to manage resources and keep your infrastructure definitions aligned with reality.

Terraform's advantages in everyday infrastructure work

Declarative language and predictability

When people talk about Terraform's strengths, they are often talking about predictability.

You get declarative code that cleanly separates desired state from the imperative work of calling cloud APIs, state management that keeps track of what already exists, and multi-cloud support from the same configuration language. For teams that aren't primarily software engineers but need to manage cloud infrastructure, this combination is powerful.

Because Terraform uses a dedicated domain-specific language instead of a general-purpose programming language, the mental model stays focused on infrastructure definitions rather than application logic.

HashiCorp Configuration Language is close enough to JSON and YAML that it feels familiar, but expressive enough to capture relationships between infrastructure resources. For many teams, this means a shorter learning curve for infrastructure-as-code when compared to jumping straight into TypeScript or Python.

Widespread adoption

Terraform also benefits from widespread adoption.

Terraform supports a huge catalog of existing Terraform providers, community modules, and reference architectures. There's extensive documentation, examples for almost every cloud service, and community support in forums and chat.

If you want to manage infrastructure across multiple cloud providers, build standardized modules, or integrate with Terraform Enterprise or Terraform Cloud for centralized state and policy control, you can do that with patterns that are already battle-tested.

Straightforward management

Teams also appreciate that Terraform's multi-cloud infrastructure management story is straightforward. You write infrastructure code once, swap providers or add additional providers, and Terraform takes care of orchestrating calls to each cloud provider.

If you need to manage infrastructure that spans AWS, Azure, and Google Cloud, and you want one tool and one workflow, Terraform gives you that without forcing your team to learn multiple languages.

Terraform challenges you'll actually feel

Learning a new programming language

The same choices that make Terraform approachable also introduce friction when your infrastructure and your software development practices start to converge.

HCL is powerful as a configuration language, but compared to general-purpose programming languages, its support for complex logic is limited. You do have conditionals, for_each, and some expressions, but once you start encoding real software engineering practices into your Terraform modules, you feel where the language resists you.

Teams also have to accept that Terraform is a new configuration language layered on top of their existing stack. If your developers are comfortable in Python, Go, or TypeScript, adopting Terraform means teaching them HashiCorp Configuration Language rather than letting them use the same language for infrastructure and app code. That's fine when you are primarily a platform or infrastructure team, but not ideal when application developers are expected to manage resources directly.

State becomes a point of friction

Terraform's state file is a critical piece of how it tracks infrastructure state, so you need to treat it as a first-class asset. That means you have to think about state storage, locking, permissions, and backup. Terraform supports backends like S3, GCS, and Terraform Cloud, but you still own the complexity of access control, sensitive data protection inside state, and the workflows around long-lived state in big repos.

There are ecosystem considerations as well. Since the licensing change to BSL, some organizations worry about how Terraform support and Terraform Enterprise evolve over time and have started to look at alternatives like OpenTofu. Terraform remains a strong IaC tool, but the licensing shift changed how some teams think about long-term risk in their cloud infrastructure tooling.

We're building Stategraph: A tool that will help us to reduce Terraform state friction. Learn more about Stategraph.

Where Terraform fits best

Terraform is a strong fit when you want a predictable, declarative IaC tool that centers on infrastructure management rather than application logic. If your team consists of DevOps engineers or platform engineers who prefer a purpose-built domain-specific language, if you need multi-cloud support across different cloud providers, and if you care about a mature provider ecosystem and community support, Terraform will usually be the safer default.

Teams use Terraform to:

Define base cloud infrastructure across AWS, Azure, and Google Cloud projects
Encode network topology, VPCs, policies, and Kubernetes resources
Manage integration with third-party tools like monitoring, security scanning, and identity providers.

It's also a good fit when you want to separate app code and infrastructure code and manage resources from a central platform team.

A hands-on example with Terraform and EC2

To make the Terraform side of this Pulumi vs. Terraform comparison concrete, you can look at how Terraform provisions a simple EC2 instance. The configuration below uses the AWS provider to define an instance and tags, then lets Terraform compute the plan.

provider "aws" {
  region = "us-east-1"
}

resource "aws_instance" "infra_instance" {
  ami           = "ami-0c55b159cbfafe1f0"
  instance_type = "t2.micro"

  tags = {
    Name = "terrateam-ec2"
  }
}

You initialize the working directory with terraform init, which pulls the required Terraform providers for AWS and configures the backend.

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Then you run terraform plan to see the desired infrastructure state as a set of actions.

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Next, you run terraform apply to actually manage resources in your AWS account. Read more in our articles on customizing Terraform plan and apply workflows.

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Terraform records the infrastructure state in a backend so that future plans can detect drift, manage resources consistently, and avoid accidentally recreating existing resources.

This is the basic Terraform experience. You write declarative code, rely on Terraform support for providers and state management, and let the engine translate configuration into calls to real cloud services.

What is Pulumi?

Pulumi is another popular IaC tool, but it takes a different approach than Terraform.

While Terraform uses its own declarative language, Pulumi allows you to define your infrastructure using programming languages like Python, TypeScript, JavaScript, Go, and C#. This means that if you're already familiar with one of these languages, you don't have to learn a new language specifically designed for infrastructure, like HCL in Terraform. Instead, you can use the full power of familiar language and programming logic to define your infrastructure.

With Pulumi, you write infrastructure code the same way you would write regular application code. For example, you can use loops, conditionals, and other programming constructs to create your infrastructure. This gives you greater flexibility to manage complex infrastructures.

Pulumi allows you to create reusable abstractions using classes, functions, or modules to define common infrastructure components. This can include more complex configurations like virtual machines, networking setups, or managed storage systems.

By using objects and classes, you can define these components at a higher level of abstraction, making your infrastructure code cleaner, more flexible, and easier to maintain. This advanced feature helps teams write less repetitive code and ensures consistency across different projects. Pulumi integrates seamlessly with development tools you're already using, like IDEs, version control systems, and CI/CD pipelines, allowing you to manage both your application and infrastructure in a unified workflow.

Pulumi in practice

Pulumi starts from a different assumption. Instead of asking you to learn a new configuration language, Pulumi supports multiple languages and invites you to describe your cloud infrastructure using general-purpose programming languages like TypeScript, JavaScript, Python, Go, C#, and Java.

The idea is that if you are already comfortable writing application code, you should be able to write infrastructure code the same way, in the same language, and often in the same repository.

While Terraform centers on a declarative language, Pulumi centers on software development practices. You use classes, functions, modules, and common programming patterns to model infrastructure resources. You can use real loops and conditionals, share logic between application code and infrastructure code, hook into IDE support and code tools, and write integration testing and automated tests using the same frameworks you already run for your app code.

Pulumi's provider ecosystem mirrors Terraform's in spirit. Pulumi supports major cloud providers, Kubernetes, and a wide variety of cloud services through native providers and bridges to existing Terraform providers, which means you can often reuse knowledge of resource models even when the infrastructure code is written in a different way.

Pulumi Cloud, the Pulumi SaaS offering sometimes called Pulumi Service, provides hosted state management, policy, and collaboration workflows, similar in spirit to Terraform Cloud.

Pulumi advantages when you live in code

Language Flexibility

Pulumi's biggest strength is that it treats infrastructure as just another facet of software.

If your team is full of developers familiar with TypeScript or Python, you do not force them into a new configuration language. You let them use the same language, the same IDE support, the same code review practices, and the same automated tests for both application code and infrastructure code.

That alignment alone removes a huge amount of cognitive overhead.

Because you are using full programming languages, complex logic is no longer something you awkwardly express through expressions in a declarative language.

You can write helper functions to generate infrastructure resources from configuration, use loops to build out clusters, perform integration testing against a deployed stack, and use third-party tools and SDKs inside your infrastructure code. This makes Pulumi especially attractive for complex deployments that need rich orchestration or that deeply integrate with application behavior.

Good for multi-cloud infrastructure management

Pulumi's model also fits multi-cloud infrastructure management well. Since you can create abstractions in code, you can hide cloud provider differences behind your own APIs, so that calling code does not care whether a resource is in AWS or Google Cloud.

When you combine that with Pulumi's language support and native providers, you get a powerful way to manage cloud infrastructure across multiple cloud providers without giving up control over the underlying resource graph.

Pulumi challenges and constraints

Complex logic could be a barrier

The same power that makes Pulumi appealing also introduces risk. If your team is not made up of software engineers, giving them the full power of general-purpose programming languages inside infrastructure code can backfire.

It's easy to over-engineer abstractions, build complex logic that only a few people understand, or mix app code and infrastructure definitions in a way that blurs boundaries and makes onboarding harder.

Less mature than Terraform

Pulumi's community is vibrant but smaller than Terraform's. While Pulumi supports a large set of infrastructure resources, Terraform still has the edge in sheer breadth and maturity of modules. If you rely heavily on existing infrastructure patterns shared across organizations, the smaller ecosystem may be a factor. Pulumi bridges many existing Terraform providers, but you have to be comfortable with that extra layer.

State management and sensitive data

You also need to think carefully about state management and sensitive data. Pulumi Cloud gives you a managed service for state storage, secrets, and policy, but that means adopting another SaaS in your stack. You can run Pulumi without the SaaS, but then you have to design your own approach to infrastructure state and secrets, similar to how you handle Terraform remote backends.

Potential for a steep learning curve

Finally, the learning curve cuts in the opposite direction compared to Terraform. If you have a team of developers familiar with programming languages and software engineering practices, Pulumi feels natural; but if your team is primarily infrastructure engineers who are used to declarative code and cloud consoles, Pulumi's programming model can feel like a heavy lift.

Where Pulumi fits best

Pulumi fits well when you want infrastructure definitions to live alongside application code, when teams already have strong software engineering practices, and when they are comfortable with the idea that infrastructure is just another codebase.

It's particularly attractive if:

You want to use the same language across app code and infrastructure code
Your developers are already using code tools, IDE support, and test frameworks they love
You're willing to lean into programmable infrastructure.

Teams often reach for Pulumi when application developers need to manage resources themselves without waiting on a platform team, when they want to encapsulate complex infrastructure patterns as libraries, or when they want tight integration testing of infrastructure behavior as part of their CI pipelines.

In those settings, being able to use familiar programming languages and general-purpose constructs becomes a decisive advantage.

Hands-on example with Pulumi and an S3 bucket.

To mirror the Terraform example, you can define an S3 bucket using Pulumi with TypeScript. This is what it looks like to provision resources in code while still working within your usual development workflow.

Firstly, make sure that you have Pulumi installed. You can install it via npm:

npm install -g pulumi

Now, in your terminal, create a new Pulumi project using the following commands:

mkdir pulumi-s3-demo
cd pulumi-s3-demo
pulumi new typescript

Next, we need the AWS SDK to interact with AWS services. You can install it with npm:

npm install @pulumi/aws

In your index.ts file, write the following code to create an S3 bucket:

import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";

const bucket = new aws.s3.Bucket("terrateam-bucket", {
  acl: "private",
});

export const bucketName = bucket.id;

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You scaffold a new project using pulumi new typescript, install the AWS native providers (@pulumi/aws), then run pulumi preview to see the desired state and pulumi up to provision resources.

Pulumi tracks infrastructure state either in Pulumi Cloud or in a self-managed backend, and it lets you consume outputs like bucketName directly in your application code or CI pipelines.

For many developers, this is the real Pullumi vs. Terraform key difference. You didn't have to learn a new configuration language. You used familiar programming languages, the same language you already use for your app, and your IDE and tests understood everything without any extra work.

Key differences between Terraform and Pulumi.

From a distance, you can treat Terraform vs. Pulumi as a generic IaC comparison, but when you look more closely, the key differences are about how you think, not just how you write syntax.

Here's a Pulumi vs. Terraform comparison table that captures the main trade-offs.

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Both Terraform and Pulumi can manage resources across cloud providers, enforce a desired state, and help you manage cloud infrastructure at scale. The choice is less about raw capability and more about how you want your teams to think about infrastructure, which IaC tools fit your culture, and how you connect infrastructure management to the rest of your software development practices.

Terraform vs. Pulumi: Choosing the right tool

When you decide between Pulumi and Terraform, you're not choosing a winner in an abstract tools war. You're choosing something that has to fit your existing infrastructure, your team capabilities, and your tolerance for coupling infrastructure to application code.

If you already have a significant Terraform codebase, a set of existing resources managed through HCL, and workflows built around terraform plan and terraform apply, the default move is usually to double down on that investment.

You benefit from Terraform support in your organization, from training that already happened, from existing infrastructure definitions, and from a shared understanding of how to manage resources across accounts and cloud providers.

You might choose Pulumi when your bottleneck is that application teams are blocked on infrastructure changes, and they are already comfortable in general-purpose programming languages.

In that setting, letting developers familiar with TypeScript or Python define and manage cloud infrastructure in the same language, in the same monorepo, and under the same automated tests can be transformative. You get to use integration testing for infrastructure, reuse business logic libraries for provisioning, and encode complex logic in ways that feel natural instead of fighting a limited expression language.

You also have a middle ground.

Some organizations run both Terraform and Pulumi. They use Terraform for baseline multi-cloud infrastructure management, where the declarative model and Terraform providers ecosystem shine, and they use Pulumi for application-specific stacks or edge cases where using the same language as the app is critical. In those environments, Pulumi vs. Terraform isn't a zero-sum choice but a set of well-understood trade-offs.

Whatever you choose, keep an eye on:

How you manage sensitive data
How you model infrastructure state
How you provision resources across regions and accounts
How you align your IaC tool with your broader set of DevOps tools.

The right choice is the one that minimizes accidental complexity while letting you move quickly without losing control.

Security and compliance considerations for IaC

Once you have chosen a primary IaC tool, you still need to think about security, compliance, and governance. Writing infrastructure-as-code in Terraform or Pulumi does not automatically solve access control, secrets hygiene, or auditability. It just makes it possible to encode those concerns as part of your workflow.

Permssions

You need to control who can change infrastructure definitions and who can execute plans and applies.

That usually means aligning cloud IAM roles with source control permissions, and for Terraform it often means layering in pull-request-driven workflows so that terraform plan and terraform apply are not run directly from laptops.

Pulumi has a similar story, using Pulumi Cloud permissions to manage who can manage resources in which projects.

Sensitive data

You also need a clear strategy for sensitive data.

Both Terraform and Pulumi integrate with secret managers such as HashiCorp Vault, AWS Secrets Manager, and other cloud provider tools. You still have to make sure secrets never leak into plain text logs, state files, or version control.

For Terraform, this means marking values as sensitive and being careful with state management
For Pulumi, this means using its Secret type and Pulumi Cloud features to encrypt secrets at rest

In both cases, managing cloud infrastructure safely depends on more than the IaC tool. It depends on how you wire those tools into your workflows.

Policy enforcement

Policy enforcement is another layer.

Terraform can integrate with Sentinel and Open Policy Agent, Pulumi can integrate with OPA as well, and both can sit behind external policy engines and third-party tools that validate plans before they reach production.

Whether you write policies in Rego or another language, the point is that you encode compliance and security requirements as code so that they apply consistently to every change.

Audit trails

Finally, you have to think about audit trails. You want to see who changed what, when, and why. You want drift detection that tells you when the real world no longer matches your desired state. You want logs that tie together Git commits, CI runs, and cloud provider events like CloudTrail. Neither Terraform nor Pulumi alone gives you turnkey governance. You always need glue around them.

That is the gap Terrateam is designed to fill.

Terrateam amplifies Terraform

Terrateam exists on the Terraform side of the Pulumi vs. Terraform landscape. It assumes you have chosen Terraform for infrastructure-as-code and focuses on turning that choice into a robust, auditable, and secure workflow instead of a loose collection of scripts.

Where Terraform gives you an IaC engine, Terrateam gives you an orchestration layer around that engine so you can manage infrastructure with confidence at the team and organization scale.

Terrateam integrates with GitHub so that managing infrastructure looks like managing application code. Every change to your Terraform configuration runs through pull requests, plans, reviews, and applies that are controlled through policy.

Instead of wiring this together manually in a CI system, you get a focused GitOps control plane for Terraform that bakes in state management, policy enforcement, and drift detection.

Role-based access control for Terraform workflows

Terrateam ships with role-based access control so you can express who is allowed to plan and who is allowed to apply changes across your repositories. You can give application developers the ability to trigger terrateam plan on their stacks while reserving terrateam apply for a smaller set of operators or SREs. You encode that separation in configuration rather than tribal knowledge.

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This separation means you can safely let more teams contribute infrastructure code without granting them broad permissions against your cloud provider directly. Access is mediated through Terrateam, which respects repository boundaries and environment rules and keeps the blast radius small.

For more details, visit Role-Based Access Control

Policy enforcement that keeps you compliant by default.

Terrateam treats policy as a central primitive rather than an afterthought. You can integrate Open Policy Agent or other policy engines so that every terrateam plan is evaluated against your rules before anyone applies it.

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That's where you enforce requirements such as encryption on storage, tagging standards, network boundaries, and controls around which repositories are allowed to manage which infrastructure resources.

Because policies run as part of the workflow, not as a late-stage audit, teams get fast feedback when they violate standards. Actionable failures during plan time are much easier to correct than surprises after a manual review.

For more details, visit Policy enforcement with OPA.

Secrets management that fits Git-driven workflows

Terrateam treats secrets as first-class objects without asking you to redesign your entire secrets strategy. It integrates with GitHub secrets, environment variables, and tfvars files, and it makes sure sensitive values flow into Terraform at runtime without ever landing in plain text in your repos.

By pulling secrets from systems of record and injecting them only when plans and applies run, you get to keep your Terraform configurations clean while still satisfying compliance requirements around how sensitive data moves through your systems.

For more details, visit Secrets and Variables

Audit logging and drift detection that you can trust

Terrateam keeps a complete audit trail of every infrastructure change. Every pull request, every plan, every apply, and every drift detection run is recorded with who triggered it, what changed, and whether it succeeded. This gives you a single place to answer questions that usually require stitching together Git logs, CI logs, and cloud provider logs.

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Drift detection runs on a schedule and tells you when your real infrastructure diverges from your Terraform configuration. That is essential when you want to trust that your desired state really is the truth, and not just an aspirational document that no longer matches what is actually running.

For more, visit Terrateam Audit Trail.

Terrateam's focus is not on replacing Terraform, but on giving you the governance, safety, and observability that you wish Terraform Cloud provided out of the box, with a flexible engine that fits how you already work.

When you need help, same day support from people who live and breathe Terraform workflows is part of the offering rather than an afterthought.

Conclusion

The Terraform vs. Pulumi debate is not about which tool is objectively better.

Terraform and Pulumi are serious IaC tools, both:

Manage cloud infrastructure across multiple cloud providers
Integrate with modern DevOps tools
Support policy and secrets in some form
Let you declare a desired state and rely on an engine to manage resources accordingly

The real question is how you want your teams to think. If you want a clear separation between app code and infra, a dedicated configuration language, and a massive provider ecosystem,

Terraform is the natural starting point. If you want infrastructure to follow the same software engineering practices as your services, to live in the same repositories, and to use the same tests, Pulumi makes a coherent argument for programmable infrastructure.

Whichever side of the Pulumi vs. Terraform conversation you land on, the critical piece is the workflow around the tool. You still need guardrails, policy, and auditability.

If you choose Terraform, Terrateam gives you that control plane. If you choose Pulumi, you need to build similar guardrails around the Pulumi CLI and Pulumi Cloud.

In other words, picking an IaC tool is just the beginning. The real work is in turning that tool into a safe, repeatable way to manage your infrastructure so that teams can move quickly without losing track of what actually runs in production.

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