github.com/aclaygray/packer@v1.3.2/website/source/intro/use-cases.html.md (about) 1 --- 2 layout: intro 3 sidebar_current: intro-use-cases 4 page_title: Use Cases - Introduction 5 description: |- 6 By now you should know what Packer does and what the benefits of image 7 creation are. In this section, we'll enumerate *some* of the use cases for 8 Packer. Note that this is not an exhaustive list by any means. There are 9 definitely use cases for Packer not listed here. This list is just meant to 10 give you an idea of how Packer may improve your processes. 11 --- 12 13 # Use Cases 14 15 By now you should know what Packer does and what the benefits of image creation 16 are. In this section, we'll enumerate *some* of the use cases for Packer. Note 17 that this is not an exhaustive list by any means. There are definitely use cases 18 for Packer not listed here. This list is just meant to give you an idea of how 19 Packer may improve your processes. 20 21 ### Continuous Delivery 22 23 Packer is lightweight, portable, and command-line driven. This makes it the 24 perfect tool to put in the middle of your continuous delivery pipeline. Packer 25 can be used to generate new machine images for multiple platforms on every 26 change to Chef/Puppet. 27 28 As part of this pipeline, the newly created images can then be launched and 29 tested, verifying the infrastructure changes work. If the tests pass, you can be 30 confident that the image will work when deployed. This brings a new level of 31 stability and testability to infrastructure changes. 32 33 ### Dev/Prod Parity 34 35 Packer helps [keep development, staging, and production as similar as 36 possible](http://www.12factor.net/dev-prod-parity). Packer can be used to 37 generate images for multiple platforms at the same time. So if you use AWS for 38 production and VMware (perhaps with [Vagrant](https://www.vagrantup.com)) for 39 development, you can generate both an AMI and a VMware machine using Packer at 40 the same time from the same template. 41 42 Mix this in with the continuous delivery use case above, and you have a pretty 43 slick system for consistent work environments from development all the way 44 through to production. 45 46 ### Appliance/Demo Creation 47 48 Since Packer creates consistent images for multiple platforms in parallel, it is 49 perfect for creating 50 [appliances](https://en.wikipedia.org/wiki/Software_appliance) and disposable 51 product demos. As your software changes, you can automatically create appliances 52 with the software pre-installed. Potential users can then get started with your 53 software by deploying it to the environment of their choice. 54 55 Packaging up software with complex requirements has never been so easy. Or 56 enjoyable, if you ask me.