Google Cloud Deployment Manager vs Pulumi vs Terraform

Overview

Terraform

Stacks22.9K

Followers14.7K

Votes344

GitHub Stars47.0K

Forks10.1K

Google Cloud Deployment Manager

Stacks24

Followers113

Votes5

Pulumi

Stacks306

Followers293

Votes25

GitHub Stars24.1K

Forks1.3K

Google Cloud Deployment Manager vs Pulumi vs Terraform: What are the differences?

Language Support: Google Cloud Deployment Manager uses configuration files written in YAML or Jinja to deploy resources on Google Cloud Platform. In contrast, Pulumi allows users to write infrastructure code using familiar programming languages such as Python, TypeScript, and Go, providing more flexibility and ease of use. Terraform, on the other hand, uses its own declarative language called HashiCorp Configuration Language (HCL), which is tailored specifically for infrastructure as code tasks.
State Management: Google Cloud Deployment Manager relies on Google Cloud Storage to store the deployment state, which can lead to potential issues when managing state files in large-scale deployments. Pulumi provides a centralized architecture for state management, allowing users to store state securely in their preferred backend like VCS or cloud storage. Similarly, Terraform also offers built-in features for state management, supporting state locking and remote state storage to prevent conflicts and ensure consistency in infrastructure changes.
Provider Ecosystem: Google Cloud Deployment Manager is specific to Google Cloud Platform, offering native support for GCP resources and services. In comparison, Pulumi supports multiple cloud providers, enabling users to manage resources across different cloud environments with a unified workflow. Terraform boasts an extensive provider ecosystem with support for various cloud providers, infrastructure technologies, and third-party services, making it a versatile choice for multi-cloud and hybrid cloud deployments.
Execution Model: Google Cloud Deployment Manager follows a declarative model where users define the desired state of the infrastructure, and the tool handles the provisioning and configuration automatically. Pulumi embraces a modern imperative model, allowing for more dynamic and fine-grained control over resource creation and management through imperative coding techniques. Terraform combines both imperative and declarative paradigms in its execution model, offering a compromise between simplicity and flexibility in defining infrastructure workflows.
Community and Support: Google Cloud Deployment Manager, being a Google-owned tool, has a limited community compared to Pulumi and Terraform, which have active and supportive communities of users and contributors. Pulumi's community-driven approach fosters rapid development, updates, and community modules, enhancing the tool's usability and extensibility. Terraform's vibrant community offers a wide range of resources, modules, and best practices for infrastructure automation, making it a dependable choice for diverse infrastructure requirements.

In Summary, the key differences between Google Cloud Deployment Manager, Pulumi, and Terraform lie in their language support, state management capabilities, provider ecosystems, execution models, and community support, catering to different preferences and requirements in managing cloud infrastructure efficiently.

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Advice on Terraform, Google Cloud Deployment Manager, Pulumi

Sung Won

Nov 4, 2019

Decidedon

Google Cloud IoT Core

Terraform

Python

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

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

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	Google Cloud Deployment Manager	Pulumi
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.	Google Cloud Deployment Manager allows you to specify all the resources needed for your application in a declarative format using yaml.	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.
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	-	Containers - Deploy a Docker container to production in 5 minutes using your favorite orchestrator.; Serverless - Stand up a serverless API or event handler in 5 minutes using a real lambda in code.; Infrastructure - Manage cloud infrastructure or hosted services using infrastructure as code.; CoLaDa - Embrace containers, lambdas, and data, using a modern, multi-cloud framework.
Statistics
GitHub Stars 47.0K	GitHub Stars -	GitHub Stars 24.1K
GitHub Forks 10.1K	GitHub Forks -	GitHub Forks 1.3K
Stacks 22.9K	Stacks 24	Stacks 306
Followers 14.7K	Followers 113	Followers 293
Votes 344	Votes 5	Votes 25
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 2 Automates infrastructure deployments 1 Fast deploy and update 1 Infrastracture as a code 1 Easy to deploy for GCP Cons 1 Only using in GCP	Pros 8 Infrastructure as code with less pain 4 Best-in-class kubernetes support 3 Simple 3 Can use many languages 2 Can be self-hosted
Integrations
Heroku Amazon EC2 CloudFlare DNSimple Microsoft Azure Consul Equinix Metal DigitalOcean OpenStack Google Compute Engine	Jinja Python Google Cloud Storage Google Compute Engine Google Cloud SQL	No integrations available

What are some alternatives to Terraform, Google Cloud Deployment Manager, Pulumi?

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 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 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 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 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

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 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

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

Related Comparisons

Google Cloud Deployment Manager vs Pulumi vs Terraform: What are the differences?

Language Support: Google Cloud Deployment Manager uses configuration files written in YAML or Jinja to deploy resources on Google Cloud Platform. In contrast, Pulumi allows users to write infrastructure code using familiar programming languages such as Python, TypeScript, and Go, providing more flexibility and ease of use. Terraform, on the other hand, uses its own declarative language called HashiCorp Configuration Language (HCL), which is tailored specifically for infrastructure as code tasks.
State Management: Google Cloud Deployment Manager relies on Google Cloud Storage to store the deployment state, which can lead to potential issues when managing state files in large-scale deployments. Pulumi provides a centralized architecture for state management, allowing users to store state securely in their preferred backend like VCS or cloud storage. Similarly, Terraform also offers built-in features for state management, supporting state locking and remote state storage to prevent conflicts and ensure consistency in infrastructure changes.
Provider Ecosystem: Google Cloud Deployment Manager is specific to Google Cloud Platform, offering native support for GCP resources and services. In comparison, Pulumi supports multiple cloud providers, enabling users to manage resources across different cloud environments with a unified workflow. Terraform boasts an extensive provider ecosystem with support for various cloud providers, infrastructure technologies, and third-party services, making it a versatile choice for multi-cloud and hybrid cloud deployments.
Execution Model: Google Cloud Deployment Manager follows a declarative model where users define the desired state of the infrastructure, and the tool handles the provisioning and configuration automatically. Pulumi embraces a modern imperative model, allowing for more dynamic and fine-grained control over resource creation and management through imperative coding techniques. Terraform combines both imperative and declarative paradigms in its execution model, offering a compromise between simplicity and flexibility in defining infrastructure workflows.
Community and Support: Google Cloud Deployment Manager, being a Google-owned tool, has a limited community compared to Pulumi and Terraform, which have active and supportive communities of users and contributors. Pulumi's community-driven approach fosters rapid development, updates, and community modules, enhancing the tool's usability and extensibility. Terraform's vibrant community offers a wide range of resources, modules, and best practices for infrastructure automation, making it a dependable choice for diverse infrastructure requirements.

Google Cloud Deployment Manager vs Pulumi vs Terraform

Overview