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:
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.
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 providers.tf 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.
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.
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.
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.
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.
Create a name for the instance: you need to do it by modifying your configuration file. Apply the configuration with “terraform apply”.
Create a web server: modify your main.cf 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”.
Once you are done with the previous step you can access your web server with the link.
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 main.tf 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.
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.