AWS CloudFormation vs Google Compute Engine

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AWS CloudFormation

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AWS CloudFormation vs Google Compute Engine: What are the differences?

Introduction

In this analysis, we will explore and highlight the key differences between AWS CloudFormation and Google Compute Engine.

  1. Automation of Infrastructure Deployment: AWS CloudFormation provides a Infrastructure as Code (IaC) service that allows users to define and deploy infrastructure resources using templates. Google Compute Engine also allows automation of infrastructure deployment but via tools like Deployment Manager or Terraform, which are not integrated into the platform as seamlessly as CloudFormation in AWS.

  2. Pricing Model: AWS CloudFormation does not incur separate charges for its usage, only the resources being deployed through the service will incur charges. On the other hand, Google Compute Engine charges users for the use of Deployment Manager or other infrastructure automation tools, in addition to the resources being deployed.

  3. Resource Availability: AWS CloudFormation supports a wider range of AWS resources and services compared to Google Compute Engine, making it a more comprehensive tool for deploying complex cloud infrastructures that require diverse services for different purposes.

  4. Integration with Ecosystem: AWS CloudFormation is tightly integrated with other AWS services, allowing seamless deployment and management of resources across different AWS offerings. Google Compute Engine, while effective in deploying resources on Google Cloud Platform, may not provide the same level of integration with other Google services.

  5. Learning Curve: AWS CloudFormation requires users to learn its specific syntax and structure for defining infrastructure templates, which can have a steep learning curve for beginners. Google Compute Engine, on the other hand, may have a simpler learning curve as it allows for more flexibility in defining infrastructure using tools like Deployment Manager.

In Summary, AWS CloudFormation provides a more comprehensive, integrated, and cost-effective solution for automating infrastructure deployment compared to Google Compute Engine, which offers flexibility and simplicity in defining infrastructure but may lack the same level of integration and resource availability.

Decisions about AWS CloudFormation and Google Compute Engine
Kirill Shirinkin
Cloud and DevOps Consultant at mkdev · | 3 upvotes · 151.9K 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
Overview

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.

Advantages

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.

Disadvantages

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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Stephen Fox
Artificial Intelligence Fellow · | 2 upvotes · 197.1K views

GCE is much more user friendly than EC2, though Amazon has come a very long way since the early days (pre-2010's). This can be seen in how easy it is to edit the storage attached to an instance in GCE: it's under the instance details and is edited inline. In AWS you have to click the instance > click the storage block device (new screen) > click the edit option (new modal) > resize the volume > confirm (new model) then wait a very long time. Google's is nearly instant.

  • In both cases, the instance much be shut down.

There also the preference between "user burden-of-security" and automatic security: AWS goes for the former, GCE the latter.

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Pros of AWS CloudFormation
Pros of Google Compute Engine
  • 43
    Automates infrastructure deployments
  • 21
    Declarative infrastructure and deployment
  • 13
    No more clicking around
  • 3
    Any Operative System you want
  • 3
    Atomic
  • 3
    Infrastructure as code
  • 1
    CDK makes it truly infrastructure-as-code
  • 1
    Automates Infrastructure Deployment
  • 0
    K8s
  • 87
    Backed by google
  • 79
    Easy to scale
  • 75
    High-performance virtual machines
  • 57
    Performance
  • 52
    Fast and easy provisioning
  • 15
    Load balancing
  • 12
    Compliance and security
  • 9
    Kubernetes
  • 8
    GitHub Integration
  • 7
    Consistency
  • 4
    Free $300 credit (12 months)
  • 3
    One Click Setup Options
  • 3
    Good documentation
  • 2
    Great integration and product support
  • 2
    Escort
  • 2
    Ease of Use and GitHub support
  • 1
    Nice UI
  • 1
    Easy Snapshot and Backup feature
  • 1
    Integration with mobile notification services
  • 1
    Low cost
  • 1
    Support many OS
  • 1
    Very Reliable

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Cons of AWS CloudFormation
Cons of Google Compute Engine
  • 4
    Brittle
  • 2
    No RBAC and policies in templates
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    What is 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.

    What is Google Compute Engine?

    Google Compute Engine is a service that provides virtual machines that run on Google infrastructure. Google Compute Engine offers scale, performance, and value that allows you to easily launch large compute clusters on Google's infrastructure. There are no upfront investments and you can run up to thousands of virtual CPUs on a system that has been designed from the ground up to be fast, and to offer strong consistency of performance.

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    What companies use AWS CloudFormation?
    What companies use Google Compute Engine?
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    What tools integrate with AWS CloudFormation?
    What tools integrate with Google Compute Engine?

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    What are some alternatives to AWS CloudFormation and Google Compute Engine?
    AWS CodeDeploy
    AWS CodeDeploy is a service that automates code deployments to Amazon EC2 instances. AWS CodeDeploy makes it easier for you to rapidly release new features, helps you avoid downtime during deployment, and handles the complexity of updating your applications.
    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.
    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.
    AWS Elastic Beanstalk
    Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring.
    AWS Config
    AWS Config is a fully managed service that provides you with an AWS resource inventory, configuration history, and configuration change notifications to enable security and governance. With AWS Config you can discover existing AWS resources, export a complete inventory of your AWS resources with all configuration details, and determine how a resource was configured at any point in time. These capabilities enable compliance auditing, security analysis, resource change tracking, and troubleshooting.
    See all alternatives