Pulumi vs Terraform

12 minute read     Updated:

Alexander Yu %
Alexander Yu

This article compares infrastructure as code (IaC) tools. Earthly’s declarative syntax streamlines complex build steps. Learn more about Earthly.

There once was a time when technicians manually provisioned application infrastructure. In recent years, as companies began rapidly expanding their infrastructure stacks, they began to realize the shortcomings of manual provisioning:

  • It’s costly, since hiring a technician is expensive, and manual processes are time-consuming.
  • It’s inconsistent, since human errors are inevitable, and can cause unwanted discrepancies between stacks.
  • It’s not scalable since, as stacks grow, companies have to continually devote resources towards infrastructure management.

To address these shortcomings, the Infrastructure as Code (IaC) paradigm was created. The central idea of IaC is that developers can now use code to define their infrastructure stacks, rather than rely on manual provisioning. This dramatically reduced costs, led to more consistency across infrastructure stacks, and was highly scalable, all because infrastructure provisioning could now be largely automated.

There are many solutions out there that embody IaC, but this article will focus on two particular IaC tools that stand out: Pulumi and Terraform. In this article, these tools will be compared in terms of overall functionality, expected learning curve, community support, and other important considerations. This is crucial in helping you decide which IaC tool is better for you.

Comparing Pulumi and Terraform

A vs B

Terraform is one of the most well-established IaC tools today. It’s a declarative tool, which means you define what you want the final state of your infrastructure to look like, and Terraform will handle how to achieve that state. Terraform is often considered the default IaC tool of choice, especially among larger companies and organizations that have the resources to support the learning curve of HashiCorp Configuration Language (HCL), a Domain Specific Language (DSL) unique to Terraform.

Pulumi is a newer IaC tool that has been quickly gaining in popularity. Unlike Terraform, you don’t have to learn a DSL in order to use it. Instead, Pulumi supports creating, deploying, and managing all your cloud infrastructure using common programming languages. Note that while you use an imperative language such as Python to create Pulumi files, Pulumi is still considered a declarative tool. However, due to this increased flexibility, Pulumi is often preferred by developers who are already very comfortable with one or more of the supported languages.

Terraform and Pulumi are open source tools that are very widely used in the industry. To help you determine which one best suits your needs, let’s now look into specific factors that you’ll want to consider.



Both tools have the same base functionality: enabling you to easily define and deploy your infrastructure as code. However, because Terraform uses HCL, it naturally comes with more guidelines and restrictions. In contrast, Pulumi allows you to leverage existing concepts in languages, such as loops, classes, and data structures. It’s also easier for developers to create built-in testing suites and use other extensions and libraries in their Pulumi programs. While Terraform has no built-in testing functionality, the Terraform CLI contains better tools for troubleshooting a corrupt state.

The open source nature of these tools gives the developer community the opportunity to influence which features get prioritized and delivered. In a clear illustration of this, due to high demand, Terraform launched the Cloud Development Kit for Terraform, which allows developers to use familiar languages, though it should be noted that the Terraform CDK is a newer tool in active development that, as of this writing, may not be production stable. Similarly, Pulumi launched tf2pulumi, a tool that converts HCL into a language of your choice.

Learning Curve

Learning Curve

If you’re looking to quickly learn and use one of these tools, you’ll probably find that Pulumi is easier to pick up. This is because Pulumi allows you to use your preferred programming language to define your infrastructure stacks—there’s no need to learn a specific DSL. If you already know Python, Java, Node.js, Go, or .NET Core, you can get started with Pulumi right away. If you’re familiar with Python, you can easily create an AWS DynamoDB table using Pulumi with the following code:

import pulumi
import pulumi_aws as aws

ddb_table = aws.dynamodb.Table("ddb-table",
 attributes = [
 billing_mode = "PAY_PER_REQUEST",
 hash_key = "Id",
 read_capacity = 5,
 write_capacity = 5)

Note that this is all regular Python syntax. Pulumi has a plethora of code samples in every supported language in their documentation (for example, it is the dynamodb.Table documentation). To actually deploy your infrastructure, you’ll need to become familiar with various Pulumi CLI commands.

To get started with Terraform, you’ll first have to become familiar with HCL syntax. Some developers consider this a significant extra hump to get over, but HCL is so widely adopted that it’s always a useful skill to have. In addition, while HCL is like learning a new language, much of the syntax is relatively intuitive and simple. For example, to create the same DynamoDB table from the Pulumi example, you can use the following Terraform code:

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

resource "aws_dynamodb_table" "ddb_table" {
 name = "ddb_table"
 attribute {
  name = "Id"
  type = "S"
 billing_mode = "PAY_PER_REQUEST"
 hash_key = "Id"
 read_capacity = "5"
 write_capacity = "5"

As you can see, this isn’t too bad! As with Pulumi, Terraform documents all resource properties and provides multiple code examples in their official documentation (for example, it is the aws_dynamodb_table documentation). To actually deploy your infrastructure, you’ll also have to become familiar with various Terraform CLI commands.

At first glance, it’s certainly true that Pulumi has a much easier learning curve because you can simply draw on your existing knowledge of a language. However, this doesn’t mean that it’s necessarily “better” than having to learn HCL. Because all Terraform files are written in HCL, any Terraform developer can automatically understand any Terraform file. A Pulumi developer who’s unfamiliar with Go may not be able to understand a Pulumi file written in Go. While the learning curve for Terraform may be higher at the onset, it may be worth having everyone in your organization stick to a single DSL.


Both tools are compatible with most operating systems (Windows, macOS, and Linux), and work well with all common cloud providers (AWS, Azure, Google Cloud, Kubernetes, OpenStack). Both tools are also compatible with most IDEs, although Terraform is at a slight disadvantage here because you’ll need to download an external plugin. With Pulumi, you’ll get all the inherent benefits of using an IDE, such as code completion and automatic syntax correction.


Infrastructure stacks can get big and complex. As such, it’s always best practice to break them up into small, reusable chunks. Terraform natively supports this through the concept of modules, which is simply a set of Terraform files that you can reference in other areas of your HCL code. Pulumi supports this as well, since you can reuse any class, function, or package that you define in your Pulumi files.

Community Support

raised hands with hearts

Both Terraform and Pulumi are updated frequently and have great support from their respective developer communities. However, Terraform is a more mature tool, and it has a significantly larger community. You’ll likely have an easier time finding help for issues that you come across for Terraform compared to Pulumi. One data point that stands out at the time of this writing is the number of Stack Overflow questions tagged with terraform (12,983) versus pulumi (317).


This article compared Terraform and Pulumi, two prominent Infrastructure as Code (IaC) tools. Key points to note are:

  • Functionality: Terraform uses HCL with strong troubleshooting features; Pulumi leverages familiar programming languages, allowing ease of adding libraries and testing.
  • Learning Curve: Terraform requires learning HCL, while Pulumi might require learning a new language other developers may not be familiar with.
  • Compatibility: Both are compatible with all major operating systems, cloud providers, and IDEs. Terraform requires a plugin for IDE use.
  • Modularity: Both tools support modularity.
  • Community Support: Terraform has larger community support, but both tools have comprehensive documentation and code examples.

In summary, Terraform, as the industry leader, is ideal if you seek robust community support and are willing to learn HCL. Pulumi is an emerging player preferred for efficiency and the use of familiar languages. Both tools serve the same purpose - pick one that aligns best with your needs.

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Alexander Yu %
Alexander Yu
Alexander Yu is a technical writer at AWS by day and a freelance writer by night. After completing his BS in electrical engineering and computer science from UC Berkeley, he became a software developer at AWS for almost three years before transitioning into technical writing. He lives in Seattle with his dog Yuna.



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