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

Docker Machine vs Terraform

OverviewDecisionsComparisonAlternatives

Overview

Terraform
Terraform
Stacks22.9K
Followers14.7K
Votes344
GitHub Stars47.0K
Forks10.1K
Docker Machine
Docker Machine
Stacks430
Followers518
Votes12

Docker Machine vs Terraform: What are the differences?

Introduction

This Markdown document provides a comparison between Docker Machine and Terraform, outlining the key differences between these two tools. Docker Machine is a command-line tool used for provisioning and managing Docker hosts, while Terraform is an infrastructure as code tool designed for deploying and managing infrastructure across multiple service providers.

  1. Docker Machine: Docker Machine is specifically focused on managing Docker hosts. It allows the user to create, provision, and manage Docker hosts on a variety of platforms, including local machines, cloud providers, and virtual machines. The primary advantage of Docker Machine is its ability to quickly and easily create and manage Docker hosts without having to manually install and configure Docker on each individual host. This makes it a convenient option for developers who want to quickly spin up Docker hosts for testing and development purposes.

  2. Terraform: Terraform, on the other hand, is a more comprehensive infrastructure as code tool that allows users to define, provision, and manage infrastructure resources across a wide range of service providers. Unlike Docker Machine, which focuses solely on Docker hosts, Terraform supports a vast array of resources, including virtual machines, containers, storage, networks, and more. Terraform uses a declarative syntax to define the desired state of the infrastructure, which it then provisions and manages. This makes Terraform a powerful tool for managing infrastructure across multiple platforms and providers in a consistent and reproducible manner.

  3. Resource Provisioning: When it comes to provisioning resources, Docker Machine primarily focuses on creating and managing Docker hosts. It provisions minimum necessary resources required to run Docker and sets up the Docker daemon. On the other hand, Terraform provides a more extensive set of resource provisioning capabilities. It supports creating and managing a wide range of resources, such as virtual machines, containers, storage, networks, load balancers, and more. This makes Terraform well-suited for managing complex infrastructure setups that go beyond just Docker hosts.

  4. Provider Support: Docker Machine offers a variety of supported drivers, which are responsible for creating and managing Docker hosts on different platforms. These drivers include native drivers for platforms like VirtualBox and VMware, as well as cloud-specific drivers for platforms like AWS and Azure. In contrast, Terraform provides a vast ecosystem of providers that allow users to create and manage resources across different service providers, cloud platforms, and infrastructure technologies. This gives users more flexibility and choice when it comes to provisioning infrastructure resources.

  5. Configuration Language: Docker Machine uses a command-line interface with specific flags and options to provision Docker hosts. While it does support some level of automation through scripts, the process of creating and managing Docker hosts is mainly done through command-line commands. On the other hand, Terraform uses its own configuration language called HashiCorp Configuration Language (HCL), which is a declarative language for describing infrastructure resources and their configurations. With HCL, users can define complex infrastructure setups, dependencies, and variables in a human-readable and version-controlled manner.

  6. Scope and Use Cases: Due to its focused nature, Docker Machine is primarily used for managing Docker hosts on different platforms, making it ideal for developers and teams who primarily work with Docker containers. It simplifies the process of creating and managing Docker hosts, allowing developers to focus more on containerization. On the other hand, Terraform's broader scope and capabilities make it suitable for managing complex infrastructure setups that include various resources and service providers. It is often used by DevOps teams looking to manage infrastructure as code across multiple environments and platforms.

In summary, Docker Machine is a tool focused on quickly provisioning and managing Docker hosts on different platforms, while Terraform is an infrastructure as code tool that provides a wider range of resource provisioning capabilities and supports multiple service providers. Docker Machine simplifies the management of Docker hosts, while Terraform enables the management of complex infrastructure setups in a consistent and reproducible manner.

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Advice on Terraform, Docker Machine

Sung Won
Sung Won

Nov 4, 2019

DecidedonGoogle Cloud IoT CoreGoogle Cloud IoT CoreTerraformTerraformPythonPython

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
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
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

Terraform
Terraform
Docker Machine
Docker Machine

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.

Machine lets you create Docker hosts on your computer, on cloud providers, and inside your own data center. It creates servers, installs Docker on them, then configures the Docker client to talk to them.

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
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Statistics
GitHub Stars
47.0K
GitHub Stars
-
GitHub Forks
10.1K
GitHub Forks
-
Stacks
22.9K
Stacks
430
Followers
14.7K
Followers
518
Votes
344
Votes
12
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
Pros
  • 12
    Easy docker hosts management
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
Docker
Docker

What are some alternatives to Terraform, Docker Machine?

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.

Kubernetes

Kubernetes

Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.

Rancher

Rancher

Rancher is an open source container management platform that includes full distributions of Kubernetes, Apache Mesos and Docker Swarm, and makes it simple to operate container clusters on any cloud or infrastructure platform.

Docker Compose

Docker Compose

With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.

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.

Docker Swarm

Docker Swarm

Swarm serves the standard Docker API, so any tool which already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts: Dokku, Compose, Krane, Deis, DockerUI, Shipyard, Drone, Jenkins... and, of course, the Docker client itself.

Tutum

Tutum

Tutum lets developers easily manage and run lightweight, portable, self-sufficient containers from any application. AWS-like control, Heroku-like ease. The same container that a developer builds and tests on a laptop can run at scale in Tutum.

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.

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