Google Cloud Deployment Manager聽vs聽Terraform

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Google Cloud Deployment Manager

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Google Cloud Deployment Manager vs Terraform: What are the differences?


This Markdown code provides a comparison between Google Cloud Deployment Manager and Terraform, highlighting their key differences.

  1. 1. Resource Support: Google Cloud Deployment Manager focuses on providing native support for Google Cloud resources, allowing users to create and manage them using YAML or Python files. In contrast, Terraform is a multi-cloud infrastructure provisioning tool that supports a wide range of resources across multiple cloud providers, including Google Cloud.

  2. 2. Declarative vs Imperative: Google Cloud Deployment Manager follows a declarative approach, where users define the desired state of their infrastructure, and the tool takes care of creating and managing the resources to achieve that state. On the other hand, Terraform follows an imperative approach, where users specify the exact steps and sequence to provision and manage their infrastructure.

  3. 3. Configuration Language: Google Cloud Deployment Manager uses YAML or Python configuration files, allowing users to define their infrastructure and resource specifications. Terraform, on the other hand, uses a Domain-Specific Language (DSL) called HashiCorp Configuration Language (HCL), which provides a concise and expressive way to define infrastructure configurations.

  4. 4. Ecosystem and Community: Terraform boasts a larger ecosystem and community compared to Google Cloud Deployment Manager. Terraform has a wide range of modules and providers contributed by its community, enabling users to easily provision resources beyond the scope of a single cloud provider. Google Cloud Deployment Manager, on the other hand, has a smaller ecosystem focused primarily on Google Cloud resources.

  5. 5. Learning Curve: Google Cloud Deployment Manager has a relatively lower learning curve, especially for users already familiar with YAML or Python. Its simple and intuitive approach makes it easier to get started. In contrast, Terraform has a steeper learning curve due to its unique HCL language syntax and additional concepts like state management and plan execution.

  6. 6. Maturity and Release Cycle: Google Cloud Deployment Manager is built specifically for Google Cloud and tightly integrated with its services, making it more aligned with Google's release cycles and updates. Terraform, being a multi-cloud tool, follows a broader release cycle and may have a time lag in adopting certain cloud provider features or enhancements.

In Summary, Google Cloud Deployment Manager focuses on native support for Google Cloud resources, follows a declarative approach, uses YAML or Python configuration files, and has a smaller ecosystem and learning curve compared to Terraform, which supports multi-cloud provisioning, follows an imperative approach using HCL, has a larger ecosystem and community, and a steeper learning curve.

Decisions about Google Cloud Deployment Manager and Terraform
Kirill Shirinkin
Cloud and DevOps Consultant at mkdev | 3 upvotes 路 145.5K views

Ok, so first - AWS Copilot is CloudFormation under the hood, but the way it works results in you not thinking about CFN anymore. AWS found the right balance with Copilot - it's insanely simple to setup production-ready multi-account environment with many services inside, with CI/CD out of the box etc etc. It's pretty new, but even now it was enough to launch Transcripto, which uses may be a dozen of different AWS services, all bound together by Copilot.

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Because Pulumi uses real programming languages, you can actually write abstractions for your infrastructure code, which is incredibly empowering. You still 'describe' your desired state, but by having a programming language at your fingers, you can factor out patterns, and package it up for easier consumption.

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Sergey Ivanov

We use Terraform to manage AWS cloud environment for the project. It is pretty complex, largely static, security-focused, and constantly evolving.

Terraform provides descriptive (declarative) way of defining the target configuration, where it can work out the dependencies between configuration elements and apply differences without re-provisioning the entire cloud stack.


Terraform is vendor-neutral in a way that it is using a common configuration language (HCL) with plugins (providers) for multiple cloud and service providers.

Terraform keeps track of the previous state of the deployment and applies incremental changes, resulting in faster deployment times.

Terraform allows us to share reusable modules between projects. We have built an impressive library of modules internally, which makes it very easy to assemble a new project from pre-fabricated building blocks.


Software is imperfect, and Terraform is no exception. Occasionally we hit annoying bugs that we have to work around. The interaction with any underlying APIs is encapsulated inside 3rd party Terraform providers, and any bug fixes or new features require a provider release. Some providers have very poor coverage of the underlying APIs.

Terraform is not great for managing highly dynamic parts of cloud environments. That part is better delegated to other tools or scripts.

Terraform state may go out of sync with the target environment or with the source configuration, which often results in painful reconciliation.

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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 Terraform
  • 2
    Automates infrastructure deployments
  • 1
    Fast deploy and update
  • 1
    Infrastracture as a code
  • 1
    Easy to deploy for GCP
  • 122
    Infrastructure as code
  • 73
    Declarative syntax
  • 45
  • 28
  • 24
  • 8
  • 8
    Cloud agnostic
  • 6
    It's like coding your infrastructure in simple English
  • 6
    Immutable infrastructure
  • 5
    Platform agnostic
  • 4
  • 4
  • 4
    Automates infrastructure deployments
  • 4
  • 2
  • 2
    Scales to hundreds of hosts

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Cons of Google Cloud Deployment Manager
Cons of Terraform
  • 1
    Only using in GCP
  • 1
    Doesn't have full support to GKE

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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 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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What companies use Google Cloud Deployment Manager?
What companies use Terraform?
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