Google Cloud Deployment Manager vs Packer

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Google Cloud Deployment Manager

21
82
+ 1
5
Packer

515
460
+ 1
42
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Google Cloud Deployment Manager vs Packer: What are the differences?

Developers describe Google Cloud Deployment Manager as "Create and manage cloud resources with simple templates". Google Cloud Deployment Manager allows you to specify all the resources needed for your application in a declarative format using yaml. On the other hand, Packer is detailed 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.

Google Cloud Deployment Manager and Packer can be categorized as "Infrastructure Build" tools.

Packer is an open source tool with 9.09K GitHub stars and 2.48K GitHub forks. Here's a link to Packer's open source repository on GitHub.

Decisions about Google Cloud Deployment Manager and Packer

I personally am not a huge fan of vendor lock in for multiple reasons:

  • I've seen cost saving moves to the cloud end up costing a fortune and trapping companies due to over utilization of cloud specific features.
  • I've seen S3 failures nearly take down half the internet.
  • I've seen companies get stuck in the cloud because they aren't built cloud agnostic.

I choose to use terraform for my cloud provisioning for these reasons:

  • It's cloud agnostic so I can use it no matter where I am.
  • It isn't difficult to use and uses a relatively easy to read language.
  • It tests infrastructure before running it, and enables me to see and keep changes up to date.
  • It runs from the same CLI I do most of my CM work from.
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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

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Pros of Google Cloud Deployment Manager
Pros of Packer
  • 2
    Automates infrastructure deployments
  • 1
    Infrastracture as a code
  • 1
    Fast deploy and update
  • 1
    Easy to deploy for GCP
  • 27
    Cross platform builds
  • 9
    Vm creation automation
  • 4
    Bake in security
  • 1
    Good documentation
  • 1
    Easy to use

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Cons of Google Cloud Deployment Manager
Cons of Packer
  • 1
    Only using in GCP
    Be the first to leave a con

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    - No public GitHub repository available -

    What is Google Cloud Deployment Manager?

    Google Cloud Deployment Manager allows you to specify all the resources needed for your application in a declarative format using yaml.

    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.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use Google Cloud Deployment Manager?
    What companies use Packer?
    See which teams inside your own company are using Google Cloud Deployment Manager or Packer.
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    What tools integrate with Google Cloud Deployment Manager?
    What tools integrate with Packer?

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    What are some alternatives to Google Cloud Deployment Manager and Packer?
    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.
    Chef
    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.
    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.
    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.
    AWS Cloud Development Kit
    It is an open source software development framework to model and provision your cloud application resources using familiar programming languages. It uses the familiarity and expressive power of programming languages for modeling your applications. It provides you with high-level components that preconfigure cloud resources with proven defaults, so you can build cloud applications without needing to be an expert.
    See all alternatives