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Packer
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Packer vs Terraform: What are the differences?

Developers describe Packer as "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. On the other hand, Terraform is detailed as "Describe your complete infrastructure as code and build resources across providers". 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.

Packer and Terraform belong to "Infrastructure Build Tools" category of the tech stack.

Some of the features offered by Packer are:

  • 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.

On the other hand, Terraform provides the following key features:

  • Infrastructure as Code: Infrastructure is described using a high-level configuration syntax. This allows a blueprint of your datacenter to be versioned and treated as you would any other code. Additionally, infrastructure can be shared and re-used.
  • Execution Plans: Terraform has a "planning" step where it generates an execution plan. The execution plan shows what Terraform will do when you call apply. This lets you avoid any surprises when Terraform manipulates infrastructure.
  • Resource Graph: Terraform builds a graph of all your resources, and parallelizes the creation and modification of any non-dependent resources. Because of this, Terraform builds infrastructure as efficiently as possible, and operators get insight into dependencies in their infrastructure.

"Cross platform builds" is the primary reason why developers consider Packer over the competitors, whereas "Infrastructure as code" was stated as the key factor in picking Terraform.

Packer and Terraform are both open source tools. It seems that Terraform with 17.4K GitHub stars and 4.77K forks on GitHub has more adoption than Packer with 9.03K GitHub stars and 2.46K GitHub forks.

Instacart, Slack, and Twitch are some of the popular companies that use Terraform, whereas Packer is used by Instacart, SendGrid, and Oscar Health. Terraform has a broader approval, being mentioned in 489 company stacks & 298 developers stacks; compared to Packer, which is listed in 113 company stacks and 20 developer stacks.

What is 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.

What is 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.
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Why do developers choose Packer?
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      What are some alternatives to Packer and Terraform?
      AWS CloudFormation
      You can use AWS CloudFormation鈥檚 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鈥檛 need to figure out the order in which AWS services need to be provisioned or the subtleties of how to make those dependencies work.
      GeoEngineer
      GeoEngineer uses Terraform to plan and execute changes, so the DSL to describe resources is similar to Terraform's. GeoEngineer's DSL also provides programming and object oriented features like inheritance, abstraction, branching and looping.
      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.
      Habitat
      Habitat is a new approach to automation that focuses on the application instead of the infrastructure it runs on. With Habitat, the apps you build, deploy, and manage behave consistently in any runtime鈥夆斺塵etal, VMs, containers, and PaaS. You'll spend less time on the environment and more time building features.
      Atlas
      Atlas is one foundation to manage and provide visibility to your servers, containers, VMs, configuration management, service discovery, and additional operations services.
      See all alternatives
      Decisions about Packer and Terraform
      John Kodumal
      John Kodumal
      CTO at LaunchDarkly | 3 upvotes 43.1K views
      atLaunchDarklyLaunchDarkly
      Ansible
      Ansible
      Spinnaker
      Spinnaker
      Terraform
      Terraform
      Packer
      Packer
      Armory
      Armory

      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.

      See more
      Joseph Kunzler
      Joseph Kunzler
      DevOps Engineer at Tillable | 9 upvotes 36.1K views
      atTillableTillable
      Amazon S3
      Amazon S3
      Amazon EC2
      Amazon EC2
      AWS Elastic Load Balancing (ELB)
      AWS Elastic Load Balancing (ELB)
      AWS CloudFormation
      AWS CloudFormation
      Terraform
      Terraform

      We use Terraform because we needed a way to automate the process of building and deploying feature branches. We wanted to hide the complexity such that when a dev creates a PR, it triggers a build and deployment without the dev having to worry about any of the 'plumbing' going on behind the scenes. Terraform allows us to automate the process of provisioning DNS records, Amazon S3 buckets, Amazon EC2 instances and AWS Elastic Load Balancing (ELB)'s. It also makes it easy to tear it all down when finished. We also like that it supports multiple clouds, which is why we chose to use it over AWS CloudFormation.

      See more
      Terraform
      Terraform
      Google Cloud Deployment Manager
      Google Cloud Deployment Manager
      AWS CloudFormation
      AWS CloudFormation

      I use Terraform because it hits the level of abstraction pocket of being high-level and flexible, and is agnostic to cloud platforms. Creating complex infrastructure components for a solution with a UI console is tedious to repeat. Using low-level APIs are usually specific to cloud platforms, and you still have to build your own tooling for deploying, state management, and destroying infrastructure.

      However, Terraform is usually slower to implement new services compared to cloud-specific APIs. It's worth the trade-off though, especially if you're multi-cloud. I heard someone say, "We want to preference a cloud, not lock in to one." Terraform builds on that claim.

      Terraform Google Cloud Deployment Manager AWS CloudFormation

      See more
      Pedro Arnal Puente
      Pedro Arnal Puente
      CTO at La Cupula Music SL | 7 upvotes 65.5K views
      atLa Cupula Music SLLa Cupula Music SL
      Debian
      Debian
      Amazon EC2
      Amazon EC2
      Amazon S3
      Amazon S3
      Amazon RDS for Aurora
      Amazon RDS for Aurora
      Redis
      Redis
      Amazon ElastiCache
      Amazon ElastiCache
      Terraform
      Terraform
      Packer
      Packer
      Ansible
      Ansible

      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 .

      See more
      Google Cloud IoT Core
      Google Cloud IoT Core
      Terraform
      Terraform
      Python
      Python
      Google Cloud Deployment Manager
      Google Cloud Deployment Manager
      Google Cloud Build
      Google Cloud Build
      Google Cloud Run
      Google Cloud Run
      Google Cloud Bigtable
      Google Cloud Bigtable
      Google BigQuery
      Google BigQuery
      Google Cloud Storage
      Google Cloud Storage
      Google Compute Engine
      Google Compute Engine
      GitHub
      GitHub

      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

      See more
      Interest over time
      Reviews of Packer and Terraform
      No reviews found
      How developers use Packer and Terraform
      Avatar of Royal Icing
      Royal Icing uses TerraformTerraform

      Terraform makes it so easy to deploy AWS and Google Cloud services, with the declarative approach avoiding so many headaches of manual work and possible mistakes.

      Avatar of B霉i Thanh
      B霉i Thanh uses TerraformTerraform
      • Infrastructure as Code.
      • Central tool to deploy all infratructure: AWS, CloudFlare, StatusCake
      Avatar of Bob P
      Bob P uses PackerPacker

      Packer makes it easy to setup custom images to import into vagrant.

      Avatar of Prime Technologies
      Prime Technologies uses TerraformTerraform

      The entire AWS environments is described and setup using Terraform.

      Avatar of Binded
      Binded uses TerraformTerraform

      All of our infrastructure is stored as code thanks to Terraform.

      Avatar of Razorpay
      Razorpay uses TerraformTerraform

      We orchestrate our AWS infrastructure using Terraform.

      Avatar of Zinc
      Zinc uses PackerPacker

      We use Packer to build our Base AMIs.

      Avatar of Endource
      Endource uses PackerPacker

      Application deployment packages

      Avatar of Go Furuya
      Go Furuya uses PackerPacker

      To make the "Golden Image"

      Avatar of Scott Miller
      Scott Miller uses PackerPacker

      Used for packing AMIs

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