Pulumi or Terraform?

Pulumi and Terraform are both popular infrastructure-as-code (IaC) tools used for provisioning and managing cloud resources. While they share similarities, they have distinct differences in their approaches and capabilities. Which one should you pick for your next project? let's compare!.

What makes terraform so special?

1. Broad provider support: Terraform has a vast ecosystem of providers, which allows you to manage resources across various cloud providers, including AWS, Azure, Google Cloud, and more.

2. Declarative configuration: Terraform uses a declarative language called HashiCorp Configuration Language (HCL) or JSON. It allows you to define the desired state of your infrastructure without worrying about the implementation details.

3. Maturity and community support: Terraform has been around for a longer time and has a large and active community. This means there are extensive resources, modules, and community-driven contributions available.

4. Plan and apply workflow: Terraform's plan feature allows you to preview changes before applying them, ensuring you have visibility into the potential impact of your infrastructure modifications.

As with every other tool there are also some bad sides of terraform, let's look at some of them and how pulumi is handling them

While Terraform supports some degree of abstraction with modules and interpolations, it primarily focuses on infrastructure provisioning and lacks extensive programming capabilities. For example, let's say you have a requirement to conditionally provision resources based on certain conditions or perform complex calculations during resource creation. With Terraform's declarative approach, achieving such dynamic behavior can be challenging. While there are workarounds using Terraform's data sources and interpolations, it can lead to more complex and less intuitive code.

In contrast, with a tool like Pulumi that supports full programming languages, you have the flexibility to incorporate loops, conditionals, functions, and other programming constructs directly into your infrastructure code. This enables you to handle complex logic and dynamic resource provisioning more easily and intuitively. A good use case is provisioning VMs with Terraform.

In this scenario, you have an application that requires different types of VMs based on the workload and environment. Let's say you need to provision small VMs for development and testing purposes and larger VMs for production.

Using Terraform's declarative approach, you would define your infrastructure configuration in HCL (HashiCorp Configuration Language).

Here's an example of how the Terraform code might look

1.  variable "environment" {
      description = "Environment type (dev, prod)"
      type        = string
    }
   
    resource "aws_instance" "example" {
      count         = var.environment == "prod" ? 3 : 1
      ami           = "ami-0c94855ba95c71c99"
      instance_type = var.environment == "prod" ? "t3.large" : "t3.micro"
    }
   

   In this example, we define a variable called "environment" that represents the type of environment (dev, prod). Based on the value of the "environment" variable, the count and instance type of the AWS EC2 instances will be determined. If the environment is set to "prod", it provisions three instances of type "t3.large"; otherwise, it provisions a single instance of type "t3.micro".

   This simple use case demonstrates how you can conditionally provision resources in Terraform based on certain variables or conditions. However, as the complexity of the conditions or dynamic behavior increases, Terraform's limited programming capabilities may make it more challenging to express the desired logic.

   In contrast, with Pulumi's programming language support, you could write similar logic using familiar programming constructs like if-else statements, loops, and functions. This can make the code more expressive, easier to manage, and enable more complex scenarios

   Terraform also uses a state file to track the state of the deployed resources. Managing the state can sometimes become challenging, especially in a team or collaborative environment and it is primarily designed to be declarative, meaning it's focused on describing the desired state rather than allowing imperative control over resource management.

Pulumi to the rescue. Here are some general advatages of using Pulumi

1. Full programming language support: Pulumi allows you to use popular programming languages like Python, JavaScript/TypeScript, Go, and .NET/C# to define and manage your infrastructure. This provides more flexibility and control over your infrastructure code.

   Let's consider a scenario where you have an application that requires the creation of multiple instances of a resource based on a dynamic list of inputs. For instance, you need to provision a set of AWS S3 buckets based on a list of bucket names provided by an external source.

   Using Pulumi's full language support, you can write infrastructure code using a programming language such as Python. Here's an example using Python and Pulumi's AWS provider:

    import pulumi
    from pulumi_aws import s3
   
    bucket_names = ["bucket1", "bucket2", "bucket3"]
   
    for name in bucket_names:
        bucket = s3.Bucket(name)
        pulumi.export(name, bucket.id)
   

   In this example, we define a list of bucket names. With a simple loop, we iterate over the list and create an AWS S3 bucket for each name. The bucket resources are dynamically provisioned based on the contents of the list. This dynamic behavior is made possible by the full programming language support provided by Pulumi.

   Additionally, with Pulumi's language support, you can incorporate other programming constructs like conditionals, functions, libraries, and modules. This enables you to implement sophisticated logic and customize your infrastructure provisioning based on the unique requirements of your application.

2. Bi-directional provisioning and updates: Pulumi allows you to provision and update resources both in a forward and backward direction, making it easier to evolve and manage existing infrastructure.

   Imagine you have an application that experiences varying levels of traffic throughout the day. To handle the fluctuating workload efficiently, you want to implement an autoscaling mechanism that automatically adjusts the number of instances in your cloud environment based on the current demand.

   With Pulumi's bi-directional provisioning and updates, you can achieve this dynamic autoscaling behavior more effectively. Here's an example using Python and Pulumi's AWS provider:

    import pulumi
    from pulumi_aws import autoscaling
   
    group = autoscaling.Group(
        "autoscaling-group",
        min_size=1,
        max_size=10,
        desired_capacity=2,
        launch_template=autoscaling.GroupLaunchTemplateArgs(
            id="lt-0123456789abcdef0",
            version="$Latest",
        ),
    )
   
    pulumi.export("group_name", group.name)
    pulumi.export("group_arn", group.arn)
   

3. Fine-grained control: With Pulumi, you have fine-grained control over resource provisioning, allowing you to make changes to individual resources and react to events during provisioning.

Pulumi is not perfect. Yes. Some possible challenges we might need to face with using this tool are listed thus.

1. Smaller ecosystem: Pulumi has a growing ecosystem but is still relatively smaller compared to Terraform. It may have fewer providers and community-contributed modules available.

2. Learning curve: Pulumi's programming language approach means you need to have some programming knowledge to work effectively with it. This can introduce a learning curve for users who are not familiar with programming concepts.

3. Resource support gaps: While Pulumi covers many popular cloud providers, some niche providers or specific services might have limited support or require custom implementation.

Ultimately, the choice between Pulumi and Terraform depends on your specific use case, infrastructure requirements, and personal preferences. If you prioritize a declarative approach, broad provider support, and a large community, Terraform might be a better fit. On the other hand, if you prefer a full programming language experience, fine-grained control, and bi-directional updates, Pulumi could be a suitable choice.

Add: Pulumi has a declarative language now https://www.pulumi.com/docs/intro/languages/yaml/