Chef vs Google Cloud Deployment Manager

Overview

Chef

Stacks1.3K

Followers1.1K

Votes345

Google Cloud Deployment Manager

Stacks24

Followers113

Votes5

Chef vs Google Cloud Deployment Manager: What are the differences?

Introduction:

Chef and Google Cloud Deployment Manager are both tools used for automating infrastructure provisioning and management. While they share some similarities, there are also key differences that set them apart.

Configuration Language: One of the main differences between Chef and Google Cloud Deployment Manager is the configuration language they use. Chef utilizes Ruby-based DSL (Domain-Specific Language), allowing for greater flexibility and customization in defining infrastructure as code. On the other hand, Google Cloud Deployment Manager uses YAML or Jinja templates, which may be simpler for those already familiar with these languages.
Hosted Solution: Chef is primarily self-hosted, meaning users are responsible for setting up and maintaining the infrastructure for Chef server and related components. In contrast, Google Cloud Deployment Manager is a hosted solution provided by Google Cloud Platform, requiring minimal setup and maintenance on the user's end.
Integration with Google Cloud Platform Services: Google Cloud Deployment Manager seamlessly integrates with various Google Cloud Platform services, allowing for easy provisioning and management of resources within the Google Cloud ecosystem. While Chef can also be used for managing Google Cloud resources, it may require more manual configuration and integration work.
Community Support: Chef benefits from a large and active community of users and contributors, providing a wealth of resources, cookbooks, and plugins to aid in automation tasks. Google Cloud Deployment Manager, while backed by Google's resources, may have a smaller community footprint, potentially leading to fewer pre-built templates or resources for users to leverage.
Scalability: When it comes to scalability, Google Cloud Deployment Manager is designed to handle large-scale deployments and provide efficient resource management at scale. Chef, while capable of scaling to a certain extent, may require more manual intervention and optimization to handle large and complex infrastructures effectively.
Pricing Model: Chef follows a subscription-based pricing model for its enterprise edition, with pricing based on the number of nodes being managed. In contrast, Google Cloud Deployment Manager is included in Google Cloud Platform's pricing structure, with charges based on the resources provisioned using the deployment manager.

In Summary, Chef and Google Cloud Deployment Manager differ in configuration language, hosting, integration with Google Cloud Platform, community support, scalability, and pricing model, offering users a choice between flexibility, ease of use, ecosystem integration, community support, scalability, and cost implications based on their specific requirements.

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CLI (Node.js)

Manual

Advice on Chef, Google Cloud Deployment Manager

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

Anonymous

Sep 17, 2019

Needs advice

I'm just getting started using Vagrant to help automate setting up local VMs to set up a Kubernetes cluster (development and experimentation only). (Yes, I do know about minikube)

I'm looking for a tool to help install software packages, setup users, etc..., on these VMs. I'm also fairly new to Ansible, Chef, and Puppet. What's a good one to start with to learn? I might decide to try all 3 at some point for my own curiosity.

The most important factors for me are simplicity, ease of use, shortest learning curve.

329k views329k

Comments

Detailed Comparison

Chef	Google Cloud Deployment Manager
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.	Google Cloud Deployment Manager allows you to specify all the resources needed for your application in a declarative format using yaml.
Access to 800+ Reusable Cookbooks;Integration with Leading Cloud Providers;Enterprise Platform Support including Windows and Solaris;Create, Bootstrap and Manage OpenStack Clouds;Easy Installation with 'one-click' Omnibus Installer;Automatic System Discovery with Ohai;Text-Based Search Capabilities;Multiple Environment Support;"Knife" Command Line Interface;"Dry Run" Mode for Testing Potential Changes;Manage 10,000+ Nodes on a Single Chef Server;Available as a Hosted Service;Centralized Activity and Resource Reporting;"Push" Command and Control Client Runs;Multi-Tenancy;Role-Based Access Control [RBAC];High Availability Installation Support and Verification;Centralized Authentication Using LDAP or Active Directory	-
Statistics
Stacks 1.3K	Stacks 24
Followers 1.1K	Followers 113
Votes 345	Votes 5
Pros & Cons
Pros 110 Dynamic and idempotent server configuration 76 Reusable components 47 Integration testing with Vagrant 43 Repeatable 30 Mock testing with Chefspec	Pros 2 Automates infrastructure deployments 1 Infrastracture as a code 1 Easy to deploy for GCP 1 Fast deploy and update Cons 1 Only using in GCP
Integrations
Amazon EC2 Rackspace Cloud Servers Microsoft Azure HP Cloud Compute Joyent Cloud	Jinja Python Google Cloud Storage Google Compute Engine Google Cloud SQL

What are some alternatives to Chef, Google Cloud Deployment Manager?

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.

Terraform

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.

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

Chef vs Google Cloud Deployment Manager: What are the differences?

Introduction:

Configuration Language: One of the main differences between Chef and Google Cloud Deployment Manager is the configuration language they use. Chef utilizes Ruby-based DSL (Domain-Specific Language), allowing for greater flexibility and customization in defining infrastructure as code. On the other hand, Google Cloud Deployment Manager uses YAML or Jinja templates, which may be simpler for those already familiar with these languages.
Hosted Solution: Chef is primarily self-hosted, meaning users are responsible for setting up and maintaining the infrastructure for Chef server and related components. In contrast, Google Cloud Deployment Manager is a hosted solution provided by Google Cloud Platform, requiring minimal setup and maintenance on the user's end.
Integration with Google Cloud Platform Services: Google Cloud Deployment Manager seamlessly integrates with various Google Cloud Platform services, allowing for easy provisioning and management of resources within the Google Cloud ecosystem. While Chef can also be used for managing Google Cloud resources, it may require more manual configuration and integration work.
Community Support: Chef benefits from a large and active community of users and contributors, providing a wealth of resources, cookbooks, and plugins to aid in automation tasks. Google Cloud Deployment Manager, while backed by Google's resources, may have a smaller community footprint, potentially leading to fewer pre-built templates or resources for users to leverage.
Scalability: When it comes to scalability, Google Cloud Deployment Manager is designed to handle large-scale deployments and provide efficient resource management at scale. Chef, while capable of scaling to a certain extent, may require more manual intervention and optimization to handle large and complex infrastructures effectively.
Pricing Model: Chef follows a subscription-based pricing model for its enterprise edition, with pricing based on the number of nodes being managed. In contrast, Google Cloud Deployment Manager is included in Google Cloud Platform's pricing structure, with charges based on the resources provisioned using the deployment manager.

Chef vs Google Cloud Deployment Manager

Overview