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  1. Stackups
  2. DevOps
  3. Build Automation
  4. Infrastructure Build Tools
  5. AWS CloudFormation vs Docker Compose

AWS CloudFormation vs Docker Compose

OverviewDecisionsComparisonAlternatives

Overview

AWS CloudFormation
AWS CloudFormation
Stacks1.6K
Followers1.3K
Votes88
Docker Compose
Docker Compose
Stacks22.3K
Followers16.5K
Votes501
GitHub Stars36.4K
Forks5.5K

AWS CloudFormation vs Docker Compose: What are the differences?

Introduction

AWS CloudFormation and Docker Compose are both powerful tools used in the field of cloud computing, but they serve different purposes and have distinct features that set them apart. Understanding the key differences between these two tools is crucial in determining which one to use for specific scenarios.

  1. Orchestration vs. Containerization: The main difference between AWS CloudFormation and Docker Compose lies in their primary function. AWS CloudFormation is an orchestration tool used for managing and provisioning cloud resources, while Docker Compose is a containerization tool that focuses on managing and running containerized applications.

  2. Infrastructure as Code vs. Service Definition: AWS CloudFormation operates on the concept of infrastructure as code, allowing users to define and manage their cloud resources in a declarative manner using a template. On the other hand, Docker Compose focuses on defining the services, networks, and volumes required for running Docker containers, providing a clear and concise service definition.

  3. Multi-Cloud vs. Single-Platform: AWS CloudFormation is specifically built for managing resources within the AWS ecosystem, meaning it primarily supports the provisioning of AWS-specific services. Docker Compose, on the other hand, is cloud-agnostic and can be used to manage containers on various platforms, including AWS, Azure, Google Cloud, and even local environments.

  4. Scalability and High Availability: AWS CloudFormation offers built-in features for managing scalability and high availability of resources. It supports the creation of auto-scaling groups, load balancers, and other features that ensure the availability and performance of the infrastructure. Docker Compose, however, does not provide native support for these features and relies on external tools or manual configuration to achieve scalability and high availability.

  5. Centralized Management vs. Local Development: AWS CloudFormation allows users to centrally manage and provision resources using templates, making it ideal for large-scale deployments across multiple environments. Docker Compose, on the other hand, is primarily used in local development environments for running and testing containerized applications, providing a lightweight and flexible toolset.

  6. Complexity vs. Simplicity: AWS CloudFormation can be more complex to set up and use due to its comprehensive feature set and the need to understand AWS-specific services. Docker Compose, on the other hand, provides a simplified and straightforward approach to container management, making it easier to get started with for developers and small-scale deployments.

In summary, AWS CloudFormation focuses on the orchestration and provisioning of cloud resources within the AWS ecosystem, while Docker Compose is primarily used for managing containerized applications across various platforms. AWS CloudFormation offers scalability, high availability, and centralized management, whereas Docker Compose provides simplicity and flexibility for local development and testing.

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Advice on AWS CloudFormation, Docker Compose

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
Sergey
Sergey

Contractor at Adaptive

Apr 17, 2020

Decided

Overview

We use Terraform to manage AWS cloud environment for the project. It is pretty complex, largely static, security-focused, and constantly evolving.

Terraform provides descriptive (declarative) way of defining the target configuration, where it can work out the dependencies between configuration elements and apply differences without re-provisioning the entire cloud stack.

Advantages

Terraform is vendor-neutral in a way that it is using a common configuration language (HCL) with plugins (providers) for multiple cloud and service providers.

Terraform keeps track of the previous state of the deployment and applies incremental changes, resulting in faster deployment times.

Terraform allows us to share reusable modules between projects. We have built an impressive library of modules internally, which makes it very easy to assemble a new project from pre-fabricated building blocks.

Disadvantages

Software is imperfect, and Terraform is no exception. Occasionally we hit annoying bugs that we have to work around. The interaction with any underlying APIs is encapsulated inside 3rd party Terraform providers, and any bug fixes or new features require a provider release. Some providers have very poor coverage of the underlying APIs.

Terraform is not great for managing highly dynamic parts of cloud environments. That part is better delegated to other tools or scripts.

Terraform state may go out of sync with the target environment or with the source configuration, which often results in painful reconciliation.

426k views426k
Comments

Detailed Comparison

AWS CloudFormation
AWS CloudFormation
Docker Compose
Docker Compose

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.

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.

AWS CloudFormation comes with the following ready-to-run sample templates: WordPress (blog),Tracks (project tracking), Gollum (wiki used by GitHub), Drupal (content management), Joomla (content management), Insoshi (social apps), Redmine (project mgmt);No Need to Reinvent the Wheel – A template can be used repeatedly to create identical copies of the same stack (or to use as a foundation to start a new stack);Transparent and Open – Templates are simple JSON formatted text files that can be placed under your normal source control mechanisms, stored in private or public locations such as Amazon S3 and exchanged via email.;Declarative and Flexible – To create the infrastructure you want, you enumerate what AWS resources, configuration values and interconnections you need in a template and then let AWS CloudFormation do the rest with a few simple clicks in the AWS Management Console, via the command line tools or by calling the APIs.
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Statistics
GitHub Stars
-
GitHub Stars
36.4K
GitHub Forks
-
GitHub Forks
5.5K
Stacks
1.6K
Stacks
22.3K
Followers
1.3K
Followers
16.5K
Votes
88
Votes
501
Pros & Cons
Pros
  • 43
    Automates infrastructure deployments
  • 21
    Declarative infrastructure and deployment
  • 13
    No more clicking around
  • 3
    Atomic
  • 3
    Infrastructure as code
Cons
  • 4
    Brittle
  • 2
    No RBAC and policies in templates
Pros
  • 123
    Multi-container descriptor
  • 110
    Fast development environment setup
  • 79
    Easy linking of containers
  • 68
    Simple yaml configuration
  • 60
    Easy setup
Cons
  • 9
    Tied to single machine
  • 5
    Still very volatile, changing syntax often
Integrations
No integrations available
Docker
Docker

What are some alternatives to AWS CloudFormation, Docker Compose?

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 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.

Portainer

Portainer

It is a universal container management tool. It works with Kubernetes, Docker, Docker Swarm and Azure ACI. It allows you to manage containers without needing to know platform-specific code.

Codefresh

Codefresh

Automate and parallelize testing. Codefresh allows teams to spin up on-demand compositions to run unit and integration tests as part of the continuous integration process. Jenkins integration allows more complex pipelines.

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.

Pulumi

Pulumi

Pulumi is a cloud development platform that makes creating cloud programs easy and productive. Skip the YAML and just write code. Pulumi is multi-language, multi-cloud and fully extensible in both its engine and ecosystem of packages.

CAST.AI

CAST.AI

It is an AI-driven cloud optimization platform for Kubernetes. Instantly cut your cloud bill, prevent downtime, and 10X the power of DevOps.

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