Chef vs Packer

Overview

Chef

Stacks1.3K

Followers1.1K

Votes345

Packer

Stacks573

Followers566

Votes41

Chef vs Packer: What are the differences?

Introduction

Chef and Packer are both tools used in DevOps and infrastructure automation. While they share some similarities, there are key differences between the two.

Configuration Management vs. Image Building: Chef is a configuration management tool that allows you to define and manage the desired state of your infrastructure. It focuses on maintaining and configuring servers by writing recipes and cookbooks. On the other hand, Packer is an image building tool that creates machine images for multiple platforms, such as virtual machines or containers. It focuses on creating reusable and consistent images that can be deployed to various environments.
Procedural vs. Declarative: Chef follows a procedural approach, meaning you define step-by-step instructions on how to achieve a desired state. It provides flexibility but can be more complex to manage and maintain. In contrast, Packer follows a declarative approach, where you define the desired end result without specifying the exact steps to get there. This makes Packer easier to use and maintain, especially for image building processes.
Continuous Configuration Enforcement vs. Image Caching: Chef enforces the desired configuration continuously by converging the current state to the desired state. It actively manages and applies changes to the infrastructure, ensuring it remains in the desired state. Packer, on the other hand, focuses on image caching and reuse. It builds images based on defined configurations and caches them for future builds, reducing build times and ensuring consistency across deployments.
Platform Independence vs. Platform-specific: Chef is a platform-independent tool, meaning it can be used to manage configurations across various operating systems and cloud providers. It provides a unified approach to managing infrastructure. In contrast, Packer supports multiple platforms but requires separate configuration files for each platform. It allows for fine-tuning image builds specific to the target platforms.
Real-time Configuration vs. Pre-built Images: Chef makes real-time configuration changes to existing infrastructure by applying recipes and cookbooks on target nodes. It allows for dynamic adjustments and updates to server configurations. Packer, on the other hand, builds pre-configured images that are ready to be deployed. These pre-built images contain the desired configuration and can be used to spin up new instances quickly without requiring real-time configuration changes.
Applicability Scope vs. Image Granularity: Chef is suitable for managing various aspects of the infrastructure, including package installations, service configurations, and server provisioning. It provides a broad range of configuration management capabilities. Packer, however, focuses on building images and is less concerned with the ongoing management and configuration of running instances. It provides granular control over the image creation process, allowing you to define specific components and configurations within the image.

In summary, Chef is a configuration management tool that focuses on maintaining and configuring servers in real-time across different platforms, while Packer is primarily used for building pre-configured images that can be deployed quickly and consistently across multiple platforms.

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CLI (Node.js)

Manual

Advice on Chef, Packer

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.

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Comments

Detailed Comparison

Chef	Packer
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.	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.
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	Super fast infrastructure deployment. Packer images allow you to launch completely provisioned and configured machines in seconds, rather than several minutes or hours.;Multi-provider portability. Because Packer creates identical images for multiple platforms, you can run production in AWS, staging/QA in a private cloud like OpenStack, and development in desktop virtualization solutions such as VMware or VirtualBox.;Improved stability. Packer installs and configures all the software for a machine at the time the image is built. If there are bugs in these scripts, they'll be caught early, rather than several minutes after a machine is launched.;Greater testability. After a machine image is built, that machine image can be quickly launched and smoke tested to verify that things appear to be working. If they are, you can be confident that any other machines launched from that image will function properly.
Statistics
Stacks 1.3K	Stacks 573
Followers 1.1K	Followers 566
Votes 345	Votes 41
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 27 Cross platform builds 8 Vm creation automation 4 Bake in security 1 Easy to use 1 Good documentation
Integrations
Amazon EC2 Rackspace Cloud Servers Microsoft Azure HP Cloud Compute Joyent Cloud	Amazon EC2 DigitalOcean Docker Google Compute Engine OpenStack VirtualBox

What are some alternatives to Chef, Packer?

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

Scalr

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

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.

Related Comparisons

Chef vs Packer: What are the differences?

Introduction

Chef and Packer are both tools used in DevOps and infrastructure automation. While they share some similarities, there are key differences between the two.

Configuration Management vs. Image Building: Chef is a configuration management tool that allows you to define and manage the desired state of your infrastructure. It focuses on maintaining and configuring servers by writing recipes and cookbooks. On the other hand, Packer is an image building tool that creates machine images for multiple platforms, such as virtual machines or containers. It focuses on creating reusable and consistent images that can be deployed to various environments.
Procedural vs. Declarative: Chef follows a procedural approach, meaning you define step-by-step instructions on how to achieve a desired state. It provides flexibility but can be more complex to manage and maintain. In contrast, Packer follows a declarative approach, where you define the desired end result without specifying the exact steps to get there. This makes Packer easier to use and maintain, especially for image building processes.
Continuous Configuration Enforcement vs. Image Caching: Chef enforces the desired configuration continuously by converging the current state to the desired state. It actively manages and applies changes to the infrastructure, ensuring it remains in the desired state. Packer, on the other hand, focuses on image caching and reuse. It builds images based on defined configurations and caches them for future builds, reducing build times and ensuring consistency across deployments.
Platform Independence vs. Platform-specific: Chef is a platform-independent tool, meaning it can be used to manage configurations across various operating systems and cloud providers. It provides a unified approach to managing infrastructure. In contrast, Packer supports multiple platforms but requires separate configuration files for each platform. It allows for fine-tuning image builds specific to the target platforms.
Real-time Configuration vs. Pre-built Images: Chef makes real-time configuration changes to existing infrastructure by applying recipes and cookbooks on target nodes. It allows for dynamic adjustments and updates to server configurations. Packer, on the other hand, builds pre-configured images that are ready to be deployed. These pre-built images contain the desired configuration and can be used to spin up new instances quickly without requiring real-time configuration changes.
Applicability Scope vs. Image Granularity: Chef is suitable for managing various aspects of the infrastructure, including package installations, service configurations, and server provisioning. It provides a broad range of configuration management capabilities. Packer, however, focuses on building images and is less concerned with the ongoing management and configuration of running instances. It provides granular control over the image creation process, allowing you to define specific components and configurations within the image.

Chef vs Packer

Overview

Chef vs Packer: What are the differences?