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  1. Stackups
  2. DevOps
  3. Continuous Deployment
  4. Server Configuration And Automation
  5. Habitat vs Metamon vs Terraform

Habitat vs Metamon vs Terraform

OverviewComparisonAlternatives

Overview

Terraform
Terraform
Stacks22.9K
Followers14.7K
Votes344
GitHub Stars47.0K
Forks10.1K
Metamon
Metamon
Stacks0
Followers3
Votes0
GitHub Stars337
Forks15
Habitat
Habitat
Stacks34
Followers60
Votes5
GitHub Stars2.7K
Forks319

Habitat vs Metamon vs Terraform: What are the differences?

Introduction: In the realm of infrastructure automation, Habitat, Metamon, and Terraform stand out as key players. Each tool offers distinct capabilities and approaches to managing infrastructure, deployment, and configuration. Understanding the differences between these tools is crucial for choosing the most suitable solution for various automation needs.

  1. Approach to Infrastructure Management: Habitat focuses on packaging applications with their dependencies to ensure consistency across different environments. Metamon, on the other hand, specializes in simplifying the management of metadata and configurations across multiple systems. Terraform excels in defining and provisioning infrastructure as code, enabling users to manage resources across various cloud providers in a declarative manner.

  2. Focus on Cross-Environment Consistency: Habitat emphasizes application portability and reproducibility by creating packages that can be easily transferred between different environments. Metamon streamlines the synchronization of metadata and configurations to maintain consistency across systems. In contrast, Terraform's infrastructure as code approach ensures consistent resource provisioning across various environments by defining configurations in code.

  3. Dependency Management: Habitat excels in managing application dependencies within packages, ensuring that all necessary components are included for seamless deployment. Metamon focuses on metadata and configuration management to simplify the tracking and synchronization of settings across distributed systems. Terraform leverages modules and provider plugins to manage dependencies and interact with external resources for infrastructure automation.

  4. Complexity of Configuration: Habitat simplifies the configuration process by encapsulating applications and their dependencies within packages, reducing the complexity of deployment. Metamon simplifies configuration management by centralizing metadata and settings for efficient distribution across systems. Terraform streamlines infrastructure configuration by defining resources in code, facilitating automated provisioning and updates with minimal manual intervention.

  5. Scope of Automation: Habitat primarily focuses on packaging applications for consistent deployment and management, ensuring that dependencies are included for seamless operation. Metamon centralizes metadata and configuration management to streamline settings synchronization across environments. Terraform extends automation capabilities to infrastructure provisioning, enabling the definition of resources, dependencies, and configurations as code for efficient deployment and management.

  6. Integration with Cloud Providers: Habitat offers integration with various cloud platforms to facilitate application deployment and scalability in cloud environments. Metamon focuses on metadata and configuration synchronization across distributed systems, offering flexibility in managing settings. Terraform shines in its seamless integration with multiple cloud providers, enabling users to provision and manage resources across platforms with ease.

In Summary, understanding the key differences between Habitat, Metamon, and Terraform is essential for selecting the most suitable automation tool based on specific infrastructure management needs and requirements.

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Detailed Comparison

Terraform
Terraform
Metamon
Metamon
Habitat
Habitat

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.

Metamon is a Vagrantfile combined with a set of Ansible Playbooks which can be used to quickly start a new Django project. Although Metamon is easily extensible by adding new Ansible roles, it is a better fit for people who use Django + Gunicorn + Nginx + PostgreSQL.

Habitat is a new approach to automation that focuses on the application instead of the infrastructure it runs on. With Habitat, the apps you build, deploy, and manage behave consistently in any runtime — metal, VMs, containers, and PaaS. You'll spend less time on the environment and more time building features.

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
Create an Ubuntu 14.04 machine.;Set-up basic Operating system dependencies.;Set-up a Virtualenv and automatically install dependencies.;Set-up Supervisor, PostgreSQL 9.3, Gunicorn and Nginx.;Start a new Django project if it's needed.;Automatically activate a virtualenv and cd to the project's directory when logging in during development.;Use separate requirements files for faster deploys.;Separate settings file for unit testing with coverage and customized settings to make testing faster.
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Statistics
GitHub Stars
47.0K
GitHub Stars
337
GitHub Stars
2.7K
GitHub Forks
10.1K
GitHub Forks
15
GitHub Forks
319
Stacks
22.9K
Stacks
0
Stacks
34
Followers
14.7K
Followers
3
Followers
60
Votes
344
Votes
0
Votes
5
Pros & Cons
Pros
  • 121
    Infrastructure as code
  • 73
    Declarative syntax
  • 45
    Planning
  • 28
    Simple
  • 24
    Parallelism
Cons
  • 1
    Doesn't have full support to GKE
No community feedback yet
Pros
  • 2
    Easy to use
  • 1
    Lightweight
  • 1
    Supervisor is great concept
  • 1
    Cross platform builds
Integrations
Heroku
Heroku
Amazon EC2
Amazon EC2
CloudFlare
CloudFlare
DNSimple
DNSimple
Microsoft Azure
Microsoft Azure
Consul
Consul
Equinix Metal
Equinix Metal
DigitalOcean
DigitalOcean
OpenStack
OpenStack
Google Compute Engine
Google Compute Engine
Ansible
Ansible
Django
Django
Vagrant
Vagrant
VirtualBox
VirtualBox
Microsoft Azure
Microsoft Azure
Chef
Chef
rkt
rkt
Nomad
Nomad
Google App Engine
Google App Engine
Docker
Docker
Mesosphere
Mesosphere
Kubernetes
Kubernetes
Google Compute Engine
Google Compute Engine
VMware vSphere
VMware vSphere

What are some alternatives to Terraform, Metamon, Habitat?

Ansible

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

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

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 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

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 CloudFormation

AWS CloudFormation

You can use AWS CloudFormation’s sample templates or create your own templates to describe the AWS resources, and any associated dependencies or runtime parameters, required to run your application. You don’t need to figure out the order in which AWS services need to be provisioned or the subtleties of how to make those dependencies work.

Fabric

Fabric

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.

AWS OpsWorks

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

Packer

Packer

Packer automates the creation of any type of machine image. It embraces modern configuration management by encouraging you to use automated scripts to install and configure the software within your Packer-made images.

Scalr

Scalr

Scalr is a remote state & operations backend for Terraform with access controls, policy as code, and many quality of life features.

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