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  1. Stackups
  2. DevOps
  3. Continuous Deployment
  4. Server Configuration And Automation
  5. AWS OpsWorks vs Terraform

AWS OpsWorks vs Terraform

OverviewDecisionsComparisonAlternatives

Overview

AWS OpsWorks
AWS OpsWorks
Stacks196
Followers222
Votes51
Terraform
Terraform
Stacks22.9K
Followers14.7K
Votes344
GitHub Stars47.0K
Forks10.1K

AWS OpsWorks vs Terraform: What are the differences?

Introduction

In this article, we will discuss the key differences between AWS OpsWorks and Terraform, two popular infrastructure automation tools used in the cloud computing industry.

  1. Ease of Use: AWS OpsWorks is a managed service that provides a high-level abstraction layer for deploying and managing applications on AWS. It abstracts away the underlying infrastructure details and simplifies the deployment process. On the other hand, Terraform is an open-source tool that requires more technical expertise to set up and configure. It allows users to define infrastructure as code and provides more fine-grained control over resources.

  2. Supported Cloud Providers: AWS OpsWorks is primarily designed for managing applications and infrastructure on the AWS platform. It integrates tightly with other AWS services and provides native support for AWS resources. In contrast, Terraform is cloud-agnostic and supports multiple cloud providers, including AWS, Azure, Google Cloud, and more. It offers a consistent workflow and syntax for provisioning resources across different cloud platforms.

  3. Version Control Integration: AWS OpsWorks does not have native integration with version control systems like Git. This means that managing and tracking changes to infrastructure configurations can be more challenging. On the other hand, Terraform integrates seamlessly with Git and other version control systems. It allows users to store their infrastructure code in a repository, track changes over time, and collaborate with other team members more effectively.

  4. State Management: AWS OpsWorks manages the state of the infrastructure internally and does not expose it to users directly. This means that users do not have direct access to the infrastructure state and cannot easily manage it. In contrast, Terraform keeps track of the infrastructure state in a state file that can be stored locally or remotely. This allows users to easily manage, version control, and share the state file, making it easier to collaborate on infrastructure changes.

  5. Resource Granularity: AWS OpsWorks provides a higher-level abstraction and manages resources at the stack or application level. It simplifies the deployment and management of infrastructure components as a whole. In contrast, Terraform allows users to define and manage resources at a more granular level, such as individual instances, databases, load balancers, etc. This provides more flexibility and control over the infrastructure configuration but also requires more fine-grained management.

  6. Cost Structure: AWS OpsWorks is a managed service provided by AWS and is billed based on the resources used. The cost structure is more aligned with the specific AWS resources provisioned and the usage patterns. On the other hand, Terraform itself is an open-source tool and does not have any additional costs. However, users still need to pay for the cloud resources provisioned through Terraform, which are billed separately by the cloud provider.

In summary, the key differences between AWS OpsWorks and Terraform lie in their ease of use, supported cloud providers, version control integration, state management, resource granularity, and cost structure.

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Advice on AWS OpsWorks, 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

AWS OpsWorks
AWS OpsWorks
Terraform
Terraform

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

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 OpsWorks lets you model the different components of your application as layers in a stack, and maps your logical architecture to a physical architecture. You can see all resources associated with your application, and their status, in one place.;AWS OpsWorks provides an event-driven configuration system with rich deployment tools that allow you to efficiently manage your applications over their lifetime, including support for customizable deployments, rollback, partial deployments, patch management, automatic instance scaling, and auto healing.;AWS OpsWorks lets you define template configurations for your entire environment in a format that you can maintain and version just like your application source code.;AWS OpsWorks supports any software that has a scripted installation. Because OpsWorks uses the Chef framework, you can bring your own recipes or leverage hundreds of community-built configurations.
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
-
GitHub Stars
47.0K
GitHub Forks
-
GitHub Forks
10.1K
Stacks
196
Stacks
22.9K
Followers
222
Followers
14.7K
Votes
51
Votes
344
Pros & Cons
Pros
  • 32
    Devops
  • 19
    Cloud management
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 AWS OpsWorks, 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.

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.

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.

cPanel

cPanel

It is an industry leading hosting platform with world-class support. It is globally empowering hosting providers through fully-automated point-and-click hosting platform by hosting-centric professionals

Webmin

Webmin

It is a web-based interface for system administration for Unix. Using any modern web browser, you can setup user accounts, Apache, DNS, file sharing and much more. It removes the need to manually edit Unix configuration files.

Mina

Mina

Mina works really fast because it's a deploy Bash script generator. It generates an entire procedure as a Bash script and runs it remotely in the server. Compare this to the likes of Vlad or Capistrano, where each command is run separately on their own SSH sessions. Mina only creates one SSH session per deploy, minimizing the SSH connection overhead.

Puppet Bolt

Puppet Bolt

It is an open source orchestration tool that automates the manual work it takes to maintain your infrastructure. Use it to automate tasks that you perform on an as-needed basis or as part of a greater orchestration workflow.

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