Docker vs Fabric

Overview

Docker

Stacks194.2K

Followers143.8K

Votes3.9K

Fabric

Stacks494

Followers307

Votes75

GitHub Stars15.3K

Forks2.0K

Docker vs Fabric: What are the differences?

Introduction

Docker and Fabric are two popular tools used in the software development industry. While they have some similarities, they also have key differences that set them apart. In this article, we will explore these differences and provide a clear understanding of when to use Docker and when to use Fabric.

Deployment Methodology: Docker is a containerization platform that allows developers to package their applications, along with all the dependencies, into a single unit called a container. It provides an isolated and consistent environment for running applications. On the other hand, Fabric is a Python library that simplifies the deployment and management of applications on remote servers. It focuses on automation and scripting tasks related to deploying applications.
Level of Abstraction: Docker operates at a higher level of abstraction compared to Fabric. Docker allows developers to define the entire application stack, including the operating system, libraries, and dependencies, in a Dockerfile. It abstracts away the underlying infrastructure and provides a consistent runtime environment. Conversely, Fabric is more focused on providing a flexible and easy-to-use platform for deploying applications, without the need for defining the entire infrastructure stack.
Portability: Docker containers are highly portable and can be run on any system that supports Docker, regardless of the underlying operating system or architecture. This makes Docker suitable for deploying applications across different environments with ease. On the other hand, Fabric is more geared towards specific server configurations and may require more manual setup and configuration to work on different systems.
Scalability: Docker provides built-in features for scaling applications, allowing developers to easily scale containers up or down based on the demand. It also supports orchestration tools like Docker Swarm and Kubernetes, which simplify the management of large-scale container deployments. Meanwhile, Fabric focuses more on the deployment and configuration aspects and may require additional tools or scripts to handle scaling.
Development vs. Operations: Docker is commonly used during development and testing stages to ensure consistent and reproducible environments. It helps developers build and test applications with their dependencies, making it easier to identify and fix potential issues. Fabric, on the other hand, is more focused on the operational aspects of deploying and managing applications in production environments.
Ecosystem and Community: Docker has a large and active community, with an extensive ecosystem of tools, libraries, and images available. Developers can leverage these resources to simplify their workflow and address common challenges. Fabric, while not as widely adopted as Docker, still has a supportive community and offers its own set of plugins and extensions for various deployment scenarios.

In summary, Docker is a containerization platform that provides a higher level of abstraction and focuses on packaging and running applications in isolated environments. Fabric, on the other hand, is a Python library that simplifies deployment and management tasks, with a focus on automation and scripting. Docker is more suitable for development and testing stages, while Fabric is more aligned with operational deployment in production environments.

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Advice on Docker, Fabric

Florian

IT DevOp at Agitos GmbH

Oct 22, 2019

Decided

lxd/lxc and Docker aren't congruent so this comparison needs a more detailed look; but in short I can say: the lxd-integrated administration of storage including zfs with its snapshot capabilities as well as the system container (multi-process) approach of lxc vs. the limited single-process container approach of Docker is the main reason I chose lxd over Docker.

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Detailed Comparison

Docker	Fabric
The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere	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.
Integrated developer tools; open, portable images; shareable, reusable apps; framework-aware builds; standardized templates; multi-environment support; remote registry management; simple setup for Docker and Kubernetes; certified Kubernetes; application templates; enterprise controls; secure software supply chain; industry-leading container runtime; image scanning; access controls; image signing; caching and mirroring; image lifecycle; policy-based image promotion	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
Statistics
GitHub Stars -	GitHub Stars 15.3K
GitHub Forks -	GitHub Forks 2.0K
Stacks 194.2K	Stacks 494
Followers 143.8K	Followers 307
Votes 3.9K	Votes 75
Pros & Cons
Pros 823 Rapid integration and build up 692 Isolation 521 Open source 505 Testability and reproducibility 460 Lightweight Cons 8 New versions == broken features 6 Unreliable networking 6 Documentation not always in sync 4 Moves quickly 3 Not Secure	Pros 23 Python 21 Simple 5 Low learning curve, from bash script to Python power 5 Installation feedback for Twitter App Cards 3 Easy to add any type of job
Integrations
Java Docker Compose VirtualBox Linux Amazon EC2 Container Service Docker Swarm boot2docker Kubernetes Docker Machine Vagrant	No integrations available

What are some alternatives to Docker, Fabric?

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.

Terraform

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.

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.

LXD

LXD isn't a rewrite of LXC, in fact it's building on top of LXC to provide a new, better user experience. Under the hood, LXD uses LXC through liblxc and its Go binding to create and manage the containers. It's basically an alternative to LXC's tools and distribution template system with the added features that come from being controllable over the network.

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

LXC

LXC is a userspace interface for the Linux kernel containment features. Through a powerful API and simple tools, it lets Linux users easily create and manage system or application containers.

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

Related Comparisons

Docker vs Fabric: What are the differences?

Introduction

Deployment Methodology: Docker is a containerization platform that allows developers to package their applications, along with all the dependencies, into a single unit called a container. It provides an isolated and consistent environment for running applications. On the other hand, Fabric is a Python library that simplifies the deployment and management of applications on remote servers. It focuses on automation and scripting tasks related to deploying applications.
Level of Abstraction: Docker operates at a higher level of abstraction compared to Fabric. Docker allows developers to define the entire application stack, including the operating system, libraries, and dependencies, in a Dockerfile. It abstracts away the underlying infrastructure and provides a consistent runtime environment. Conversely, Fabric is more focused on providing a flexible and easy-to-use platform for deploying applications, without the need for defining the entire infrastructure stack.
Portability: Docker containers are highly portable and can be run on any system that supports Docker, regardless of the underlying operating system or architecture. This makes Docker suitable for deploying applications across different environments with ease. On the other hand, Fabric is more geared towards specific server configurations and may require more manual setup and configuration to work on different systems.
Scalability: Docker provides built-in features for scaling applications, allowing developers to easily scale containers up or down based on the demand. It also supports orchestration tools like Docker Swarm and Kubernetes, which simplify the management of large-scale container deployments. Meanwhile, Fabric focuses more on the deployment and configuration aspects and may require additional tools or scripts to handle scaling.
Development vs. Operations: Docker is commonly used during development and testing stages to ensure consistent and reproducible environments. It helps developers build and test applications with their dependencies, making it easier to identify and fix potential issues. Fabric, on the other hand, is more focused on the operational aspects of deploying and managing applications in production environments.
Ecosystem and Community: Docker has a large and active community, with an extensive ecosystem of tools, libraries, and images available. Developers can leverage these resources to simplify their workflow and address common challenges. Fabric, while not as widely adopted as Docker, still has a supportive community and offers its own set of plugins and extensions for various deployment scenarios.

Docker vs Fabric

Overview

Docker vs Fabric: What are the differences?