Automate and Speed up your Terraform Workflow Today

Terraform is one of the most useful open-source tools that help you apply changes to your infrastructure more smoothly, safely, and as expected.   

Whether you know a lot about Terraform workflow or are just doing the first steps to find out how it works, here we are to help you with the basics you need to know about this open-source tool. 

What is Terraform and how does it work internally?

Terraform workflow is an open-source provisioning infrastructure tool that consists of several steps which allow you to write, change, and improve your cloud infrastructure with the help of using code. 

This tool is developed by HashiCorp and written in the Go language. Many operating systems utilize it to manage and keep control over the lifecycle of the infrastructure, using the infrastructure as a code. Terraform supports the use of public clouds such as AWS and Azure. 

To help you better understand the aim of Terraform workflow, let’s say Terraform is a general language that helps to build and manage different servers of different cloud providers in one place parallelly and smoothly. 

What is the basic concept of Terraform workflow?

Well, in order to understand how this tool works we need to know the main concept of Terraform workflow. This will allow us to go further into details and realize why and when we should use it. 

Since Terraform workflow is more often used by DevOps teams, its main task lies in automating different infrastructure tasks. It leads to a smoother collaboration between the team members and provides a more productive result for the company/organization. 

What are the 3 steps in Terraform and what are their roles?

As mentioned above, Terraform workflow consists of 3 main steps about which we’ll talk in this paragraph. So, those 3 steps are as follows: 
  • Write: Code or write the way you write code.

  • Plan: Review, add, or remove resources.

  • Apply: Accept the changes. 

When we say WRITE we mean allowing the infrastructure to code in Hashicorp Configuration Language (HCL). 

When we say PLAN, we mean previewing the changes before you may apply. It enables adding or removing resources. 

When we say APPLY, we mean provision. With the help of this step, you accept the changes planned in the previous step. 

What are the main use cases of Terraform?

Now you may ask yourself this question because, after all, you need to know when to use Terraform and which are the basic cases that call for the help of this tool. Let’s discuss the 4 most common cases. 

  • Writing infrastructure as a code

    The first and most common use of Terraform is for enabling the infrastructure to write as code. That is to say, use it as a code tool. It supports public cloud resources including AWS, Azuree, and GCP as well as Stripe and Auth0, and the like. 

  • Public Cloud Provisioning

    You can use terraform for public cloud provisioning. Terraform allows you to use public clouds via a provider. Let’s say a provider in Terraform is a plugin that collects the existing organization APIs and creates a declarative Terraform syntax. 

    The biggest advantage, in this case, is that it uses a human-readable programming language called HCL instead of human-unfriendly YAML or JSON languages. 

  • Multi-Cloud Deployment

    Another common case to use Terraform is for multi-cloud deployment. It’s just wonderful how smoothly this tool organizes, deploys, and works with different public cloud providers at the same time. 

    With the help of this function, you can use the same syntax and tools avoiding the additional effort of learning multiple tools and technologies. That is to say, it saves time, and effort and provides a better result for the whole team. 

  • Terraform Custom Provider

    The next special opportunity of this tool is the Terraform customer provision. You already know that Terraform can collect an existing API and transform it to the Terraform declarative syntax. It handles working with various providers at a time. 

Common examples of Terraform implementation

Here are the most common examples of Terraform implementation. They cover the common situations where Terraform is used and will give you a better understanding of how to deal with it in practice.

ML Model Deployment on AWS for Customer Churn Prediction

ML Model deployment on AWS is a Terraform project that’s usually used to predict whether the customer will churn or not soon.

If you already work on this project then you probably know how it works in developing AWS services. If not, then I recommend you work on it to learn more about the performance of Terraform workflow.

You will need to use the Gunicorn web server to create an AWS S3 bucket when deploying the app. 

Deploy a Django App to AWS ECS with Terraform

You can use Terraform to deploy a Django app to AWS ECS. This will help you to learn more about Terraform when it comes to the usage of infrastructure as code. 

You will need to follow several steps to use this feature. First, store the images in the ECR Docker image registry, then go for the needed Terraform configuration and use it to start an ECS cluster and AWS infrastructure. 

After this, you can deploy the Django app on a group of EC2 cases that are managed by an ECS Cluster. Use Boto3 to update an ECS Service. 

As a final step, you add an HTTPS listener for an AWS load balancer and configure AWS RDS for data persistence.

Deploy Discourse on Digital Ocean with Terraform

In order to use Terraform with DigitalOcean, first of all, you need to create a DigitalOcean Account or a Mailgun Account.

After this, you can deploy discourse on digital ocean with terraform where the tool automatically wraps and merges all *.tf files in a directory. 

Deploy a Site-to-Site VPN Between AWS and Azure using Terraform

To deploy a site-to-site VPN between AWS and Azure with the help of Terraform, first, you need to create an Azure infrastructure.

Then add a Virtual Network Gateway and use Terraform's data resource to bring out the two public IP addresses from AWS. As a final step, create the Azure components connected to AWS.

Deploy OpenStack Instances with Terraform

Terraform gives you the opportunity to deploy 2 OpenStack instances, and add a web server on each instance. You need to create a file called in your Terraform directory and then insiatlize Teraform.

Next, create an OpenStack application credential and the main Terraform file. After you build a Terraform plan you can deploy it. 

A step-by-step guide on how to create a workflow using Terraform

Take a break and let’s pass on to the creation of the workflow using Terraform. Here you’ll find a step-by-step guide on how to do it and even if you have no idea how it works, don’t worry, we are here to help you. So, let’s go!

To start creating the workflow you need to follow the below-mentioned steps.

  1. 1

    Set up your AWS account: although besides AWS, Terraform also supports many other open clouds including Azure, Digital Ocean, and Google Cloud. AWS is perhaps the most convenient and helpful code example to refer to. 

  2. 2

    Install terraform: next you need to install Terraform by using the package manager of your operating system. This is the easiest way to install Terraform. 

  3. 3

    Deploy a single server: Terraform uses the declarative language HCL in files with the extension .tf. At this step you are supposed to describe the infrastructure you need and Terraform will create it for you across various providers. 

  4. 4

    Deploy a single web server: at this point, your main aim is to deploy the simplest web architecture that’s a single web server able to respond to HTTP requests.

    As a result, you build a web server on EC2 Instance in AWS. Now you can check it in the AWS web console. 

  5. 5

    Create a name for the instance: you need to do it by modifying your configuration file. Apply the configuration with “terraform apply”.

  6. 6

    Create a web server: modify your and apply the configuration. Then create a security group named “poc-instance” and open port 8080.

    Apply this group to your instance and run the web server by adding the command to the instance. Finish this step by applying the configuration; “terraform apply”

  7. 7

    Once you are done with the previous step you can access your web server with the link. 

  8. 8

    Clean up: this is the final step and here you should run the “terraform destroy” command to bring the AWS back to its original state. Apply “yes” to destroy the instances mentioned in the configuration file. 

Best practices when using Terraform workflow

When you know some of the nuances, details and helpful tools found in Terraform workflow, things get simpler and easier.

Of course, you’ll meet some challenges as a beginner but once you start, it’s better to discover every possible detail about the usage of the tool even if it seems a trifle. 

And here I leave a list of the best practices with Terraform workflow so that you could know how to use it more productively. They will help you take your Terraform skills to the next level and make you feel more confident when dealing with this tool. 
  •  Standard module structure

    There is no need to write your own modules for every case. You can just check whether there is a standard module structure for you and use it. It saves time and effort. 

  • Escape changeable hard coding

    You can avoid hardcoding several values. You may check the data source to find out whether you can get a value attribute through it or not. 

  • Import an existing infrastructure

    If you have a project handy, you can import the existing infrastructure in Terraform. Perhaps several parts of this infrastructure were built manually and you can save some time due to  the importing feature of Terraform. 

  • Limit the use of scripts and use helper scripts

    Terraform offers helper scripts that allow you to avoid using custom scripts. You can use them only when necessary. Use custom scripts called by Terraform; they are custom scripts through provisioners. Also, include helper scripts that aren’t called by Terraform. 

  • Root modules and minimizing the number of resources.

    In order to work more productively, it’s important to have a function of minimizing the number of resources in each root module. So, Terraform comes for help with this feature too. 


Summing up this topic I want to mention the importance of using Terraform workflow, especially for DevOps. This tool has definitely made life easier for DevOps teams.

It’s a time-saver, productive, and well-organized OS tool to learn and use in your companies. It works with almost all data service providers and clouds and is one of the best platform-agnostic clouds with a reliable cybersecurity partnership. 

About the author


Youssef is a Senior Cloud Consultant & Founder of

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