Fabric vs Terraform

Overview

Fabric

Stacks494

Followers307

Votes75

GitHub Stars15.3K

Forks2.0K

Terraform

Stacks22.9K

Followers14.7K

Votes344

GitHub Stars47.0K

Forks10.1K

Fabric vs Terraform: What are the differences?

Introduction

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

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.
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.
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.
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.
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.
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.

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Advice on Fabric, Terraform

Sung Won

Nov 4, 2019

Decidedon

Google Cloud IoT Core

Terraform

Python

Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

Check Out My Architecture: CLICK ME

Check out the GitHub repo attached

2.25M views2.25M

Comments

Timothy

SRE

Mar 20, 2020

Decided

I personally am not a huge fan of vendor lock in for multiple reasons:

I've seen cost saving moves to the cloud end up costing a fortune and trapping companies due to over utilization of cloud specific features.
I've seen S3 failures nearly take down half the internet.
I've seen companies get stuck in the cloud because they aren't built cloud agnostic.

I choose to use terraform for my cloud provisioning for these reasons:

It's cloud agnostic so I can use it no matter where I am.
It isn't difficult to use and uses a relatively easy to read language.
It tests infrastructure before running it, and enables me to see and keep changes up to date.
It runs from the same CLI I do most of my CM work from.

385k views385k

Comments

Daniel

May 4, 2020

Decided

Because Pulumi uses real programming languages, you can actually write abstractions for your infrastructure code, which is incredibly empowering. You still 'describe' your desired state, but by having a programming language at your fingers, you can factor out patterns, and package it up for easier consumption.

426k views426k

Comments

Detailed Comparison

Fabric	Terraform
Fabric is a Python (2.5-2.7) library and command-line tool for streamlining the use of SSH for application deployment or systems administration tasks. It provides a basic suite of operations for executing local or remote shell commands (normally or via sudo) and uploading/downloading files, as well as auxiliary functionality such as prompting the running user for input, or aborting execution.	With Terraform, you describe your complete infrastructure as code, even as it spans multiple service providers. Your servers may come from AWS, your DNS may come from CloudFlare, and your database may come from Heroku. Terraform will build all these resources across all these providers in parallel.
Lets you execute arbitrary Python functions via the command line;Library of subroutines (built on top of a lower-level library) to make executing shell commands over SSH easy and Pythonic	Infrastructure as Code: Infrastructure is described using a high-level configuration syntax. This allows a blueprint of your datacenter to be versioned and treated as you would any other code. Additionally, infrastructure can be shared and re-used.;Execution Plans: Terraform has a "planning" step where it generates an execution plan. The execution plan shows what Terraform will do when you call apply. This lets you avoid any surprises when Terraform manipulates infrastructure.;Resource Graph: Terraform builds a graph of all your resources, and parallelizes the creation and modification of any non-dependent resources. Because of this, Terraform builds infrastructure as efficiently as possible, and operators get insight into dependencies in their infrastructure.;Change Automation: Complex changesets can be applied to your infrastructure with minimal human interaction. With the previously mentioned execution plan and resource graph, you know exactly what Terraform will change and in what order, avoiding many possible human errors
Statistics
GitHub Stars 15.3K	GitHub Stars 47.0K
GitHub Forks 2.0K	GitHub Forks 10.1K
Stacks 494	Stacks 22.9K
Followers 307	Followers 14.7K
Votes 75	Votes 344
Pros & Cons
Pros 23 Python 21 Simple 5 Low learning curve, from bash script to Python power 5 Installation feedback for Twitter App Cards 3 Single config file	Pros 121 Infrastructure as code 73 Declarative syntax 45 Planning 28 Simple 24 Parallelism Cons 1 Doesn't have full support to GKE
Integrations
No integrations available	Heroku Amazon EC2 CloudFlare DNSimple Microsoft Azure Consul Equinix Metal DigitalOcean OpenStack Google Compute Engine

What are some alternatives to Fabric, Terraform?

Ansible

Ansible is an IT automation tool. It can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments or zero downtime rolling updates. Ansible’s goals are foremost those of simplicity and maximum ease of use.

Chef

Chef enables you to manage and scale cloud infrastructure with no downtime or interruptions. Freely move applications and configurations from one cloud to another. Chef is integrated with all major cloud providers including Amazon EC2, VMWare, IBM Smartcloud, Rackspace, OpenStack, Windows Azure, HP Cloud, Google Compute Engine, Joyent Cloud and others.

Capistrano

Capistrano is a remote server automation tool. It supports the scripting and execution of arbitrary tasks, and includes a set of sane-default deployment workflows.

Puppet Labs

Puppet is an automated administrative engine for your Linux, Unix, and Windows systems and performs administrative tasks (such as adding users, installing packages, and updating server configurations) based on a centralized specification.

Salt

Salt is a new approach to infrastructure management. Easy enough to get running in minutes, scalable enough to manage tens of thousands of servers, and fast enough to communicate with them in seconds. Salt delivers a dynamic communication bus for infrastructures that can be used for orchestration, remote execution, configuration management and much more.

AWS OpsWorks

Start from templates for common technologies like Ruby, Node.JS, PHP, and Java, or build your own using Chef recipes to install software packages and perform any task that you can script. AWS OpsWorks can scale your application using automatic load-based or time-based scaling and maintain the health of your application by detecting failed instances and replacing them. You have full control of deployments and automation of each component

cPanel

It is an industry leading hosting platform with world-class support. It is globally empowering hosting providers through fully-automated point-and-click hosting platform by hosting-centric professionals

Webmin

It is a web-based interface for system administration for Unix. Using any modern web browser, you can setup user accounts, Apache, DNS, file sharing and much more. It removes the need to manually edit Unix configuration files.

Mina

Mina works really fast because it's a deploy Bash script generator. It generates an entire procedure as a Bash script and runs it remotely in the server. Compare this to the likes of Vlad or Capistrano, where each command is run separately on their own SSH sessions. Mina only creates one SSH session per deploy, minimizing the SSH connection overhead.

Puppet Bolt

It is an open source orchestration tool that automates the manual work it takes to maintain your infrastructure. Use it to automate tasks that you perform on an as-needed basis or as part of a greater orchestration workflow.

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Fabric vs Terraform: What are the differences?

Introduction

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

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.
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.
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.
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.
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.
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.