Fabric vs Terraform: What are the differences?

Introduction

This markdown provides a comparison between Fabric and Terraform, highlighting their key differences.

1. Programming Language: Fabric is implemented using Python, which allows for more flexibility and customization in creating infrastructure automation scripts. On the other hand, Terraform uses its own Domain Specific Language (DSL), called HashiCorp Configuration Language (HCL), which is more declarative and easier to read.

2. Cloud Provider Support: Fabric supports a wide range of cloud providers, including AWS, Azure, and Google Cloud Platform, while Terraform supports an even larger number of providers, including some less common ones, making it a more comprehensive solution for multi-cloud or hybrid cloud environments.

3. Ecosystem and Community: Terraform has a larger and more mature ecosystem and community compared to Fabric. Terraform has a vast collection of official and community-contributed modules, which can be reused to provision various resources, reducing the amount of custom scripting required. Fabric, although also benefiting from a community, may have fewer resources and modules available.

4. Maturity and Stability: Terraform is a more established and widely adopted infrastructure provisioning tool, with a longer history and larger user base. It has been battle-tested and continuously improved over the years, which contributes to its stability and reliability. Fabric, being relatively newer, may have a smaller user base, and its maturity and stability may not be on par with Terraform.

5. State Management: Terraform manages the state of the provisioned infrastructure using a state file, which keeps track of the current state and helps with resource management and updates. Fabric, on the other hand, does not have built-in state management. This means that state management needs to be handled separately, which may introduce additional complexity and require custom solutions.

6. Architecture and Extensibility: Fabric follows a modular architecture and provides a customizable framework that allows fine-grained control over infrastructure automation. It provides a set of primitives that can be used to build flexible and complex automation workflows. Conversely, Terraform is designed to be more opinionated and follows a declarative approach, abstracting away lower-level details. While this makes Terraform easier to use for general infrastructure automation, it may limit the extensibility and customization options compared to Fabric.

In summary, Fabric and Terraform differ in their programming language, cloud provider support, ecosystem and community, maturity and stability, state management, and architecture/extensibility.