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  1. Stackups
  2. DevOps
  3. Build Automation
  4. Java Build Tools
  5. Gradle vs Terraform

Gradle vs Terraform

OverviewDecisionsComparisonAlternatives

Overview

Gradle
Gradle
Stacks24.3K
Followers9.8K
Votes254
GitHub Stars18.1K
Forks5.0K
Terraform
Terraform
Stacks22.9K
Followers14.7K
Votes344
GitHub Stars47.0K
Forks10.1K

Gradle vs Terraform: What are the differences?

Introduction

In this article, we will compare the key differences between Gradle and Terraform. Both Gradle and Terraform are popular tools used in software development, but they serve different purposes and have distinct features. Let's dive into their differences.

  1. Build Automation vs Infrastructure Provisioning: The primary difference between Gradle and Terraform lies in their main functionalities. Gradle is a powerful build automation tool that is used for compiling, building, and testing software projects. It helps in managing dependencies, running tests, and creating software artifacts. On the other hand, Terraform is an infrastructure provisioning tool that focuses on creating and managing infrastructure resources in a cloud environment. It enables developers to define and deploy infrastructure as code using declarative configuration files.

  2. Programming Language: Another significant difference between Gradle and Terraform is the programming languages they use. Gradle is written in Groovy and Kotlin, while Terraform uses its own domain-specific language (DSL) called HCL (HashiCorp Configuration Language). This means that developers who are familiar with Groovy or Kotlin might find it easier to work with Gradle, whereas those who prefer a DSL for infrastructure provisioning might find Terraform more suitable.

  3. Ecosystem and Compatibility: Gradle has a wide and mature ecosystem with support for various plugins and integrations. It is compatible with multiple build systems and can be easily integrated with popular IDEs like IntelliJ IDEA and Eclipse. Terraform, on the other hand, has a growing ecosystem with support for various cloud providers and services. It is designed to be compatible with infrastructure as a service (IaaS) providers such as AWS, Azure, and Google Cloud Platform.

  4. Scope and Granularity: The scope and granularity of Gradle and Terraform also differ. Gradle is primarily focused on individual software projects, allowing developers to define and manage the build process for a single project or multiple interconnected projects. In contrast, Terraform is designed to handle the provisioning and management of infrastructure resources at a higher level. It allows for the creation and management of complex infrastructure deployments consisting of multiple resources across different cloud providers.

  5. Dependencies and State Management: Gradle has built-in dependency management capabilities, allowing developers to specify dependencies and resolve them automatically. It can retrieve dependencies from remote repositories and cache them locally for faster builds. On the other hand, Terraform manages the state of infrastructure resources and tracks changes using its backend system. It allows for state versioning, locking, and collaboration between team members when working on infrastructure changes.

  6. Lifecycle and Workflow: Gradle follows a lifecycle-based approach with commonly used build phases like initialization, configuration, and task execution. It supports task dependencies and incremental builds, which can significantly speed up the build process. Terraform, on the other hand, follows a plan-apply cycle. Developers define the desired infrastructure state and then create an execution plan that shows the changes to be made. Finally, they apply the plan to create or modify the infrastructure resources.

In summary, Gradle is a build automation tool primarily used for software projects, written in Groovy and Kotlin, with a mature ecosystem and support for various plugins. Terraform, on the other hand, is an infrastructure provisioning tool with its own DSL, designed for managing infrastructure resources in the cloud, and focused on achieving infrastructure as code using a plan-apply workflow.

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Advice on Gradle, Terraform

Sung Won
Sung Won

Nov 4, 2019

DecidedonGoogle Cloud IoT CoreGoogle Cloud IoT CoreTerraformTerraformPythonPython

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

2.25M views2.25M
Comments
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

Detailed Comparison

Gradle
Gradle
Terraform
Terraform

Gradle is a build tool with a focus on build automation and support for multi-language development. If you are building, testing, publishing, and deploying software on any platform, Gradle offers a flexible model that can support the entire development lifecycle from compiling and packaging code to publishing web sites.

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.

Declarative builds and build-by-convention;Language for dependency based programming;Structure your build;Deep API;Gradle scales;Multi-project builds;Many ways to manage your dependencies;Gradle is the first build integration tool
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.;Change Automation: Complex changesets can be applied to your infrastructure with minimal human interaction. With the previously mentioned execution plan and resource graph, you know exactly what Terraform will change and in what order, avoiding many possible human errors
Statistics
GitHub Stars
18.1K
GitHub Stars
47.0K
GitHub Forks
5.0K
GitHub Forks
10.1K
Stacks
24.3K
Stacks
22.9K
Followers
9.8K
Followers
14.7K
Votes
254
Votes
344
Pros & Cons
Pros
  • 110
    Flexibility
  • 51
    Easy to use
  • 47
    Groovy dsl
  • 22
    Slow build time
  • 10
    Crazy memory leaks
Cons
  • 8
    Inactionnable documentation
  • 6
    It is just the mess of Ant++
  • 4
    Hard to decide: ten or more ways to achieve one goal
  • 2
    Dependency on groovy
  • 2
    Bad Eclipse tooling
Pros
  • 121
    Infrastructure as code
  • 73
    Declarative syntax
  • 45
    Planning
  • 28
    Simple
  • 24
    Parallelism
Cons
  • 1
    Doesn't have full support to GKE
Integrations
No integrations available
Heroku
Heroku
Amazon EC2
Amazon EC2
CloudFlare
CloudFlare
DNSimple
DNSimple
Microsoft Azure
Microsoft Azure
Consul
Consul
Equinix Metal
Equinix Metal
DigitalOcean
DigitalOcean
OpenStack
OpenStack
Google Compute Engine
Google Compute Engine

What are some alternatives to Gradle, Terraform?

Ansible

Ansible

Ansible is an IT automation tool. It can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments or zero downtime rolling updates. Ansible’s goals are foremost those of simplicity and maximum ease of use.

Apache Maven

Apache Maven

Maven allows a project to build using its project object model (POM) and a set of plugins that are shared by all projects using Maven, providing a uniform build system. Once you familiarize yourself with how one Maven project builds you automatically know how all Maven projects build saving you immense amounts of time when trying to navigate many projects.

Chef

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.

Capistrano

Capistrano

Capistrano is a remote server automation tool. It supports the scripting and execution of arbitrary tasks, and includes a set of sane-default deployment workflows.

Puppet Labs

Puppet Labs

Puppet is an automated administrative engine for your Linux, Unix, and Windows systems and performs administrative tasks (such as adding users, installing packages, and updating server configurations) based on a centralized specification.

Salt

Salt

Salt is a new approach to infrastructure management. Easy enough to get running in minutes, scalable enough to manage tens of thousands of servers, and fast enough to communicate with them in seconds. Salt delivers a dynamic communication bus for infrastructures that can be used for orchestration, remote execution, configuration management and much more.

Bazel

Bazel

Bazel is a build tool that builds code quickly and reliably. It is used to build the majority of Google's software, and thus it has been designed to handle build problems present in Google's development environment.

Fabric

Fabric

Fabric is a Python (2.5-2.7) library and command-line tool for streamlining the use of SSH for application deployment or systems administration tasks. It provides a basic suite of operations for executing local or remote shell commands (normally or via sudo) and uploading/downloading files, as well as auxiliary functionality such as prompting the running user for input, or aborting execution.

AWS OpsWorks

AWS OpsWorks

Start from templates for common technologies like Ruby, Node.JS, PHP, and Java, or build your own using Chef recipes to install software packages and perform any task that you can script. AWS OpsWorks can scale your application using automatic load-based or time-based scaling and maintain the health of your application by detecting failed instances and replacing them. You have full control of deployments and automation of each component

Pants

Pants

Pants is a build system for Java, Scala and Python. It works particularly well for a source code repository that contains many distinct projects.

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