Chef vs Packer: What are the differences?
What is Chef? Build, destroy and rebuild servers on any public or private cloud. 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.
What is Packer? Create identical machine images for multiple platforms from a single source configuration. 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.
Chef can be classified as a tool in the "Server Configuration and Automation" category, while Packer is grouped under "Infrastructure Build Tools".
Some of the features offered by Chef are:
- Access to 800+ Reusable Cookbooks
- Integration with Leading Cloud Providers
- Enterprise Platform Support including Windows and Solaris
On the other hand, Packer provides the following key features:
- 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.
"Dynamic and idempotent server configuration" is the primary reason why developers consider Chef over the competitors, whereas "Cross platform builds" was stated as the key factor in picking Packer.
Chef and Packer are both open source tools. Packer with 9.1K GitHub stars and 2.47K forks on GitHub appears to be more popular than Chef with 5.86K GitHub stars and 2.36K GitHub forks.
Airbnb, Facebook, and Slack are some of the popular companies that use Chef, whereas Packer is used by Instacart, Oscar Health, and Razorpay. Chef has a broader approval, being mentioned in 360 company stacks & 80 developers stacks; compared to Packer, which is listed in 115 company stacks and 21 developer stacks.
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What is Packer?
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LaunchDarkly is almost a five year old company, and our methodology for deploying was state of the art... for 2014. We recently undertook a project to modernize the way we #deploy our software, moving from Ansible-based deploy scripts that executed on our local machines, to using Spinnaker (along with Terraform and Packer) as the basis of our deployment system. We've been using Armory's enterprise Spinnaker offering to make this project a reality.
Since #ATComputing is a vendor independent Linux and open source specialist, we do not have a favorite Linux distribution. We mainly use Ubuntu , Centos Debian , Red Hat Enterprise Linux and Fedora during our daily work. These are also the distributions we see most often used in our customers environments.
For our #ci/cd training, we use an open source pipeline that is build around Visual Studio Code , Jenkins , VirtualBox , GitHub , Docker Kubernetes and Google Compute Engine.
For #ServerConfigurationAndAutomation, we have embraced and contributed to Ansible mainly because it is not only flexible and powerful, but also straightforward and easier to learn than some other (open source) solutions. On the other hand: we are not affraid of Puppet Labs and Chef either.
Currently, our most popular #programming #Language course is Python . The reason Python is so popular has to do with it's versatility, but also with its low complexity. This helps sysadmins to write scripts or simple programs to make their job less repetitive and automating things more fun. Python is also widely used to communicate with (REST) API's and for data analysis.
Our base infrastructure is composed of Debian based servers running in Amazon EC2 , asset storage with Amazon S3 , and Amazon RDS for Aurora and Redis under Amazon ElastiCache for data storage.
We are starting to work in automated provisioning and management with Terraform , Packer , and Ansible .
Out custom recipes makes it simple for developers bootstrap process (using vagrant) and that same recipe is also the one that is used to prep instances