NashTech Insights

How to Achieve Continuous Integration and Deployment with Terraform and CI/CD Pipelines

Rahul Miglani
Rahul Miglani
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Continuous Integration and Deployment (CI/CD) has become a crucial practice in software development, enabling teams to deliver software faster and more reliably. While CI/CD pipelines are commonly associated with application code, they can also be applied to infrastructure provisioning and management. In this blog post, we will explore how to achieve CI/CD for infrastructure using Terraform and CI/CD pipelines. We will discuss the benefits of integrating Terraform with CI/CD pipelines and provide an example Terraform code snippet to demonstrate the process.

Understanding CI/CD and Terraform:

Continuous Integration (CI) is the practice of frequently integrating code changes into a shared repository. It involves building and testing the code to identify integration issues early. Continuous Deployment (CD) extends CI by automatically deploying the tested and validated changes to production or staging environments.

Terraform, an infrastructure as code tool, allows you to define and provision infrastructure resources in a declarative manner. It enables you to codify your infrastructure, making it version-controlled, reproducible, and auditable. By integrating Terraform with CI/CD pipelines, you can automate the provisioning and management of your infrastructure, ensuring consistency and reducing manual errors.

Benefits of CI/CD with Terraform:

Consistent Infrastructure:

CI/CD pipelines enable you to maintain consistent infrastructure across environments. By using Terraform code as part of your pipeline, you ensure that the same infrastructure configuration is deployed in every environment, reducing the risk of configuration drift.

Faster Feedback Loop:

CI/CD pipelines provide rapid feedback on infrastructure changes. Automated testing and validation processes can be integrated into the pipeline to catch errors or misconfigurations early, allowing you to fix issues before they impact production.

Improved Collaboration:

CI/CD encourages collaboration between development, operations, and infrastructure teams. With Terraform code stored in a version control system, teams can collaborate on infrastructure changes, review code, and propose improvements, fostering a culture of collaboration and shared responsibility.

Traceability and Auditing:

CI/CD pipelines create a clear audit trail of infrastructure changes. With Terraform, you have a history of infrastructure revisions, making it easier to track changes, rollbacks, and perform compliance audits.

Example Terraform Code Snippet:

Let’s dive into an example that demonstrates how to achieve CI/CD for infrastructure using Terraform and a CI/CD pipeline. In this scenario, we will use GitLab CI/CD as our pipeline tool and provision an AWS Elastic Beanstalk application.

In this code snippet, we define an AWS Elastic Beanstalk application and environment using Terraform. The aws_elastic_beanstalk_application resource represents the application, while the aws_elastic_beanstalk_environment resource defines the environment where the application will be deployed. The output block allows us to capture and display the environment’s URL.

Integrating with a CI/CD Pipeline:

In this GitLab CI/CD pipeline configuration file, we define two stages: build and deploy. The terraform job is responsible for the build stage. It uses the hashicorp/terraform Docker image to execute Terraform commands. The script includes initializing Terraform, validating the configuration, and generating an execution plan. The plan is saved as an artifact (tfplan) to be used in the next stage.

The deploy job handles the deploy stage. It also uses the hashicorp/terraform Docker image and executes the terraform apply command with the tfplan file generated in the previous stage. The -auto-approve flag ensures non-interactive execution.

By integrating this Terraform code and the CI/CD pipeline configuration file into your GitLab repository, you can automate the provisioning and deployment of your infrastructure. The pipeline will execute the Terraform commands, validate the configuration, and apply the changes when triggered by a push or merge request.


Integrating Terraform with CI/CD pipelines enables you to achieve continuous integration and deployment for your infrastructure. By treating infrastructure as code and automating the provisioning process, you can ensure consistency, reduce manual errors, and accelerate the deployment of changes.

In this blog post, we explored the benefits of CI/CD with Terraform and provided an example Terraform code snippet for provisioning an AWS Elastic Beanstalk application. We also demonstrated how to integrate the Terraform code with a GitLab CI/CD pipeline, automating the infrastructure deployment process.

By leveraging the power of Terraform and CI/CD pipelines, you can establish an efficient and reliable workflow for managing your infrastructure changes. This approach promotes collaboration, reduces deployment time, and increases the overall quality of your infrastructure.

So why not start integrating Terraform into your CI/CD pipelines today and experience the benefits of automating your infrastructure deployment process? Happy automating!

Rahul Miglani

Rahul Miglani

Rahul Miglani is Vice President at NashTech and Heads the DevOps Competency and also Heads the Cloud Engineering Practice. He is a DevOps evangelist with a keen focus to build deep relationships with senior technical individuals as well as pre-sales from customers all over the globe to enable them to be DevOps and cloud advocates and help them achieve their automation journey. He also acts as a technical liaison between customers, service engineering teams, and the DevOps community as a whole. Rahul works with customers with the goal of making them solid references on the Cloud container services platforms and also participates as a thought leader in the docker, Kubernetes, container, cloud, and DevOps community. His proficiency includes rich experience in highly optimized, highly available architectural decision-making with an inclination towards logging, monitoring, security, governance, and visualization.

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