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  1. Stackups
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  4. Virtual Machine Platforms And Containers
  5. Docker vs Terraform

Docker vs Terraform

OverviewDecisionsComparisonAlternatives

Overview

Docker
Docker
Stacks194.2K
Followers143.8K
Votes3.9K
Terraform
Terraform
Stacks22.9K
Followers14.7K
Votes344
GitHub Stars47.0K
Forks10.1K

Docker vs Terraform: What are the differences?

Docker is a containerization platform that simplifies the process of packaging and deploying applications, while Terraform is an infrastructure as code tool used for provisioning and managing cloud resources in a declarative manner. Let's explore the key differences between them.

  1. Container Orchestration vs Infrastructure Provisioning: Docker is primarily used for containerization and container orchestration. It allows developers to package their applications and their dependencies into containers, making it easy to deploy and manage them across different environments. Terraform, on the other hand, is an infrastructure provisioning tool. It enables users to define and provision infrastructure resources, such as servers, networks, and storage, in a way that can be easily managed and automated.

  2. Scope: Docker focuses on the deployment and management of applications within containers. It provides a lightweight runtime environment that is isolated from the underlying operating system, making it easier to develop and deploy applications. Terraform, on the other hand, focuses on the provisioning and management of infrastructure resources. It allows users to define and provision infrastructure as code, enabling consistent and repeatable deployments.

  3. Technology Stack: Docker is built on containerization technology, using containers to package and distribute applications and their dependencies. It relies on a container runtime engine, such as Docker Engine, to run these containers. Terraform, on the other hand, is a cloud-agnostic technology. It can be used to provision infrastructure resources on a wide range of cloud providers, including AWS, Azure, Google Cloud, and more.

  4. State Management: Docker does not have a built-in state management system. Each container is isolated and runs independently. Docker containers can be managed and orchestrated using tools like Docker Compose and Kubernetes. Terraform, on the other hand, has built-in state management. It maintains a state file that keeps track of the current state of the infrastructure. This allows Terraform to understand the changes that need to be made to the infrastructure and apply them accordingly.

  5. Use Case: Docker is commonly used for building, packaging, and deploying applications, especially in microservices architectures. It provides a lightweight and efficient way to package applications and their dependencies, making it easier to deploy and scale them. Terraform, on the other hand, is used for infrastructure provisioning and management. It enables users to define and manage infrastructure resources, making it easier to automate infrastructure deployments and ensure consistency across environments.

  6. Community Support and Ecosystem: Docker has a large and active community with a wide range of tools and libraries built around it. This includes popular tools like Docker Compose, Docker Swarm, and Kubernetes, which provide additional functionality for managing and orchestrating Docker containers. Terraform also has a strong community and ecosystem, with support for a wide range of cloud providers and resources. It integrates well with other infrastructure tools and frameworks, making it easy to use alongside existing workflows and technologies.

In summary, Docker focuses on container orchestration and application deployment, while Terraform focuses on infrastructure provisioning and management. Docker uses containers to package and distribute applications, while Terraform provides infrastructure as code for provisioning and managing resources. Docker is commonly used for building and deploying applications, while Terraform is used for automating and managing infrastructure deployments.

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Advice on Docker, Terraform

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
Praveen
Praveen

Engineering Manager at Taylor and Francis

Jul 29, 2019

Needs adviceonMongoDB AtlasMongoDB AtlasJavaJavaSpring BootSpring Boot

We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

To build our #Backend capabilities we decided to use the following:

  1. @{#Microservices}|topic:513| - @{Java}|tool:995| with @{Spring Boot}|tool:2927| , @{Node.js}|tool:1011| with @{ExpressJS}|tool:1163| and @{Python}|tool:993| with @{Flask}|tool:1001|
  2. @{#Eventsourcingframework}|topic:890| - @{Amazon Kinesis}|tool:433| , @{Amazon Kinesis Firehose}|tool:3770| , @{Amazon SNS}|tool:396| , @{Amazon SQS}|tool:395|, @{AWS Lambda}|tool:1909|
  3. @{#Data}|topic:1360| - @{Amazon RDS}|tool:232| , @{Amazon DynamoDB}|tool:389| , @{Amazon S3}|tool:25| , @{MongoDB Atlas}|tool:5739|

To build #Webapps we decided to use Angular with RxJS

#Devops - GitHub , Travis CI , Terraform , Docker , Serverless

4.12M views4.12M
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

Detailed Comparison

Docker
Docker
Terraform
Terraform

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

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.

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
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
-
GitHub Stars
47.0K
GitHub Forks
-
GitHub Forks
10.1K
Stacks
194.2K
Stacks
22.9K
Followers
143.8K
Followers
14.7K
Votes
3.9K
Votes
344
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
    Documentation not always in sync
  • 6
    Unreliable networking
  • 4
    Moves quickly
  • 3
    Not Secure
Pros
  • 121
    Infrastructure as code
  • 73
    Declarative syntax
  • 45
    Planning
  • 28
    Simple
  • 24
    Parallelism
Cons
  • 1
    Doesn't have full support to GKE
Integrations
Java
Java
Docker Compose
Docker Compose
VirtualBox
VirtualBox
Linux
Linux
Amazon EC2 Container Service
Amazon EC2 Container Service
Docker Swarm
Docker Swarm
boot2docker
boot2docker
Kubernetes
Kubernetes
Docker Machine
Docker Machine
Vagrant
Vagrant
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

What are some alternatives to Docker, Terraform?

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.

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.

LXD

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

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

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

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

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