StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. Platform as a Service
  4. Platform As A Service
  5. Cloudify vs Terraform

Cloudify vs Terraform

OverviewDecisionsComparisonAlternatives

Overview

Cloudify
Cloudify
Stacks15
Followers19
Votes0
Terraform
Terraform
Stacks22.9K
Followers14.7K
Votes344
GitHub Stars47.0K
Forks10.1K

Cloudify vs Terraform: What are the differences?

Introduction

Cloudify and Terraform are both powerful tools that are commonly used for infrastructure as code. While they serve similar purposes, there are key differences between the two that set them apart. In this article, we will explore the main differences between Cloudify and Terraform.

  1. Provider Support: One of the notable differences between Cloudify and Terraform is the range of supported providers. Cloudify has a broader range of built-in provider support, allowing users to work with a variety of clouds, platforms, and tools. On the other hand, Terraform has a narrower focus on infrastructure provisioning and primarily supports industry-leading cloud providers like AWS, Azure, and Google Cloud.

  2. Language and Syntax: Another key difference lies in the language and syntax used by Cloudify and Terraform. Cloudify uses a declarative programming language called YAML, which is simple to understand and allows users to define the desired state of their infrastructure. Terraform, on the other hand, uses a domain-specific language (DSL) called HashiCorp Configuration Language (HCL), which is designed specifically for infrastructure provisioning.

  3. Maturity and Ecosystem: Cloudify has been in the market for a longer period of time, making it a more mature and established tool. It has a larger ecosystem with a wide range of plugins and extensions developed by the community. Terraform, on the other hand, has gained significant popularity in recent years, but it is considered to be a younger tool compared to Cloudify. However, Terraform benefits from being developed by HashiCorp, a well-known company in the DevOps and infrastructure automation space.

  4. Orchestration Capabilities: Cloudify stands out with its advanced orchestration capabilities. It provides a rich set of features for orchestrating complex workflows, managing dependencies, and handling the coordination of different components in a distributed environment. While Terraform does support basic dependency management, it is primarily focused on provisioning infrastructure resources rather than orchestration.

  5. Community and Support: Cloudify has a dedicated and active community that contributes to its development, provides support, and shares knowledge through forums, blogs, and other resources. Terraform also has a strong and vibrant community, benefiting from HashiCorp's reputation and the popularity of other tools in its ecosystem, such as Vagrant and Consul.

  6. Integration with Other Tools: Both Cloudify and Terraform can integrate with other tools and frameworks to enhance their capabilities. However, Cloudify offers more out-of-the-box integrations with popular tools like Ansible, Puppet, and Kubernetes, allowing users to leverage existing investments and build comprehensive automation workflows. While Terraform does have some integrations, it is more focused on its core provisioning functionality.

In Summary, Cloudify offers broader provider support, advanced orchestration capabilities, and a more mature ecosystem. Terraform, on the other hand, has a narrower focus, a simpler language syntax, and benefits from being developed by HashiCorp. The choice between the two largely depends on the specific requirements, preferences, and existing infrastructure stack of the user.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Advice on Cloudify, 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
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

Cloudify
Cloudify
Terraform
Terraform

Orchestrate real apps on the cloud with Cloudify, an open source application management framework that allows users to manage even the most complex apps by automating their DevOps processes.

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.

Deployment Automation; Post-Deployment Automation; Application Monitoring; Scaling; Multi-Cloud Interoperability; Deployment Monitoring; Elastic Caching
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
15
Stacks
22.9K
Followers
19
Followers
14.7K
Votes
0
Votes
344
Pros & Cons
No community feedback yet
Pros
  • 121
    Infrastructure as code
  • 73
    Declarative syntax
  • 45
    Planning
  • 28
    Simple
  • 24
    Parallelism
Cons
  • 1
    Doesn't have full support to GKE
Integrations
Jenkins
Jenkins
Kubernetes
Kubernetes
AWS CloudFormation
AWS CloudFormation
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 Cloudify, Terraform?

Heroku

Heroku

Heroku is a cloud application platform – a new way of building and deploying web apps. Heroku lets app developers spend 100% of their time on their application code, not managing servers, deployment, ongoing operations, or scaling.

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.

Clever Cloud

Clever Cloud

Clever Cloud is a polyglot cloud application platform. The service helps developers to build applications with many languages and services, with auto-scaling features and a true pay-as-you-go pricing model.

Google App Engine

Google App Engine

Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.

Red Hat OpenShift

Red Hat OpenShift

OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.

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.

AWS Elastic Beanstalk

AWS Elastic Beanstalk

Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring.

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.

Related Comparisons

GitHub
Bitbucket

Bitbucket vs GitHub vs GitLab

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot