---
page_title: Packer use cases
description: |-
  Learn about use cases for Packer, such as continuous delivery, dev/prod parity, and appliance and demo creation.
---

# Packer use cases

In this topic describes some of the use cases for Packer. This is a partial list of use cases intended to give you an idea of how Packer may improve your processes.

## Continuous delivery

Packer is lightweight, portable, and command-line driven. This makes it the
perfect tool to put in the middle of your continuous delivery pipeline. Packer
can be used to generate new machine images for multiple platforms on every
change to Chef/Puppet.

As part of this pipeline, the newly created images can then be launched and
tested, verifying the infrastructure changes work. If the tests pass, you can be
confident that the image will work when deployed. This brings a new level of
stability and testability to infrastructure changes.

## Environment parity

Packer helps keep development, staging, and production as similar as
possible. Refer to the following external article to learn more about parity between environments: ["X. Dev/prod parity"](http://www.12factor.net/dev-prod-parity). 

You can use Packer to generate images for multiple platforms at the same time. So if you use AWS for production and VMware, perhaps with [Vagrant](https://www.vagrantup.com/), for
development, you can generate both an AMI and a VMware machine using Packer at
the same time from the same template.

Mix this in with the continuous delivery use case above, and you have a pretty
slick system for consistent work environments from development all the way
through to production.

## Appliance and demo creation

Because Packer creates consistent images for multiple platforms in parallel, it is
perfect for creating
[appliances](https://en.wikipedia.org/wiki/Software_appliance) and disposable
product demos. As your software changes, you can automatically create appliances
with the software pre-installed. Potential users can then get started with your
software by deploying it to the environment of their choice.

Packaging up software with complex requirements has never been so easy. Or
enjoyable, if you ask me.
