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  1. Stackups
  2. DevOps
  3. Build Automation
  4. Infrastructure Build Tools
  5. AWS CloudFormation vs SparkleFormation

AWS CloudFormation vs SparkleFormation

OverviewDecisionsComparisonAlternatives

Overview

AWS CloudFormation
AWS CloudFormation
Stacks1.6K
Followers1.3K
Votes88
SparkleFormation
SparkleFormation
Stacks2
Followers5
Votes0

AWS CloudFormation vs SparkleFormation: What are the differences?

Introduction

AWS CloudFormation and SparkleFormation are both tools used in the field of cloud computing, specifically in the realm of infrastructure as code. However, they have distinct differences that set them apart from each other.

  1. Template Language: AWS CloudFormation uses JSON or YAML as its template language, which allows users to define their infrastructure in a format that AWS can understand. On the other hand, SparkleFormation employs a Ruby DSL (Domain-Specific Language) which provides users with more flexibility and expressiveness in defining their infrastructure.

  2. Abstraction Level: AWS CloudFormation operates at a higher level of abstraction, focusing on defining resources and their dependencies in a declarative manner. In contrast, SparkleFormation offers a lower-level abstraction by allowing users to directly manipulate the AWS CloudFormation templates, enabling more fine-grained control over the infrastructure definitions.

  3. Community Support: AWS CloudFormation boasts a larger and more established user community due to its association with AWS, which results in extensive documentation, forums, and community support. On the other hand, SparkleFormation, being a wrapper around AWS CloudFormation, has a smaller user base and may lack some of the extensive community resources available for AWS CloudFormation.

  4. Extensibility: SparkleFormation offers more extensibility and customization options compared to AWS CloudFormation. Users can create reusable components, share templates, and leverage Ruby libraries to enhance their infrastructure definitions. AWS CloudFormation, while powerful, may not provide the same level of extensibility.

  5. Ease of Use: AWS CloudFormation is straightforward to use for those familiar with JSON or YAML syntax, offering a relatively simple way to define and manage infrastructure. On the other hand, SparkleFormation, with its Ruby DSL, may have a steeper learning curve for users who are not familiar with Ruby or object-oriented programming concepts.

  6. Compatibility: AWS CloudFormation is directly integrated with AWS services and resources, ensuring seamless compatibility and support for the latest features and updates from AWS. SparkleFormation, being a wrapper around AWS CloudFormation, may have limitations in terms of supporting the newest AWS functionalities or services in a timely manner.

In Summary, AWS CloudFormation and SparkleFormation differ in their template languages, abstraction levels, community support, extensibility, ease of use, and compatibility with AWS services.

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Advice on AWS CloudFormation, SparkleFormation

Timothy
Timothy

SRE

Mar 20, 2020

Decided

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.
385k views385k
Comments
Daniel
Daniel

May 4, 2020

Decided

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.

426k views426k
Comments
Sergey
Sergey

Contractor at Adaptive

Apr 17, 2020

Decided

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.

426k views426k
Comments

Detailed Comparison

AWS CloudFormation
AWS CloudFormation
SparkleFormation
SparkleFormation

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.

It is a Ruby DSL library that assists in programmatically composing template files commonly used by orchestration APIs. It can be used to compose templates for any orchestration API that accepts serialized documents to describe resources.

AWS CloudFormation comes with the following ready-to-run sample templates: WordPress (blog),Tracks (project tracking), Gollum (wiki used by GitHub), Drupal (content management), Joomla (content management), Insoshi (social apps), Redmine (project mgmt);No Need to Reinvent the Wheel – A template can be used repeatedly to create identical copies of the same stack (or to use as a foundation to start a new stack);Transparent and Open – Templates are simple JSON formatted text files that can be placed under your normal source control mechanisms, stored in private or public locations such as Amazon S3 and exchanged via email.;Declarative and Flexible – To create the infrastructure you want, you enumerate what AWS resources, configuration values and interconnections you need in a template and then let AWS CloudFormation do the rest with a few simple clicks in the AWS Management Console, via the command line tools or by calling the APIs.
Template compilation; Resource discovery; Complex stack operations.
Statistics
Stacks
1.6K
Stacks
2
Followers
1.3K
Followers
5
Votes
88
Votes
0
Pros & Cons
Pros
  • 43
    Automates infrastructure deployments
  • 21
    Declarative infrastructure and deployment
  • 13
    No more clicking around
  • 3
    Any Operative System you want
  • 3
    Infrastructure as code
Cons
  • 4
    Brittle
  • 2
    No RBAC and policies in templates
No community feedback yet
Integrations
No integrations available
CloudFlare
CloudFlare
Google Compute Engine
Google Compute Engine
Consul
Consul
Heroku
Heroku
DigitalOcean
DigitalOcean
Otto
Otto
Scaleway
Scaleway

What are some alternatives to AWS CloudFormation, SparkleFormation?

Packer

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.

Scalr

Scalr

Scalr is a remote state & operations backend for Terraform with access controls, policy as code, and many quality of life features.

Pulumi

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.

Azure Resource Manager

Azure Resource Manager

It is the deployment and management service for Azure. It provides a management layer that enables you to create, update, and delete resources in your Azure subscription. You use management features, like access control, locks, and tags, to secure and organize your resources after deployment.

Habitat

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 — metal, VMs, containers, and PaaS. You'll spend less time on the environment and more time building features.

Google Cloud Deployment Manager

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.

AWS Cloud Development Kit

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.

Yocto

Yocto

It is an open source collaboration project that helps developers create custom Linux-based systems regardless of the hardware architecture. It provides a flexible set of tools and a space where embedded developers worldwide can share technologies, software stacks, configurations, and best practices that can be used to create tailored Linux images for embedded and IOT devices, or anywhere a customized Linux OS is needed.

GeoEngineer

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.

Atlas

Atlas

Atlas is one foundation to manage and provide visibility to your servers, containers, VMs, configuration management, service discovery, and additional operations services.

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