HashiCorp Terraform Enterprise

At Remessa, we use HashiCorp Terraform  for everything involving infrastructure. We use HashiCorp Terraform  to manage our repository on GitHub , to manage permissions, invitations, and teams. We use HashiCorp Terraform to manage our AWS  infrastructure, DNS, policies on Cloudflare . We use HashiCorp Terraform to manage our alerts on PagerDuty, and we set up some things on Grafana  with other services.

We use GitOps, so when we need to make changes such as upgrading our databases when a new Postgres version is released, we can see the version of each database that worked, allowing us to manage the process effectively. We can see in the state that our main database will be upgraded immediately. We can prevent breaks or issues because of the states, which allows us to schedule a window time for upgrades when needed.

HashiCorp Terraform operates on a declarative rather than imperative approach. This enables us to repeat processes and creation, which is the greatest advantage because we can test. If something doesn't work, we can do a rollback or change everything, and using Git , we have the history of every change. We can pick a change in the history tree to discuss and see what changed.

Our infrastructure has a repository with HashiCorp Terraform, and we have modules for that. The benefit is the concept of not repeating yourself, so we have an instance that we can use to create a new instance or cluster as quickly and correctly as possible. Everything works the same way. We don't have servers running on different systems such as Ubuntu , Red Hat, or Debian . Everything is uniform, so we don't need to think about different ways to create, manage, or access. The benefit of this uniformity is significant.

We utilize HashiCorp Terraform's state management capabilities.

Two aspects of HashiCorp Terraform could be improved: it should have better included tests and a more precise validator. I have faced issues where I needed to create something in a particular way and wanted to validate if everything was working properly, but the validator is not a strong point of HashiCorp Terraform.

Using HashiCorp Terraform Cloud is straightforward, but using other backends such as AWS  S3  or Oracle Object Store is not as straightforward. Working with modules can be complex. However, when using HashiCorp Terraform's modules, you're typically a more advanced user, so this complexity isn't problematic.

I have been working with HashiCorp Terraform for five years.

HashiCorp Terraform is extremely stable. I faced an issue once in five years where the way I declared the resource was correct, but I had problems with the binary. When I investigated the problem, the community had created an issue, and they released patches the next day. It has been totally stable with only one minor issue in five years.

Given it's in the cloud, HashiCorp Terraform is very much scalable.

When HashiCorp Terraform changed their license version, I considered migrating to another similar tool. However, after understanding the changes, I decided to continue using it since it remained open source, with restrictions only for HashiCorp competitors. This was crucial for me as I only work with open-source solutions.

All my colleagues in the company shared the same concern, and we studied migrating from HashiCorp Terraform because of the license change. I have experience with alternatives such as Crossplane, which I studied once and wanted to test. There is also OpenTofu, a fork of HashiCorp Terraform, which I tested a few times.

I continue using HashiCorp Terraform because the HashiCorp Language (HCL) is excellent to work with. The syntax is clear, and we have numerous resources and examples. Usually, I can find examples of what I want to create from other users' implementations. The benefits are the language, syntax, agility, and velocity. HashiCorp Terraform works effectively even with complex infrastructures.

To others considering HashiCorp Terraform, planning the infrastructure is key, including drawing out the idea. Using HashiCorp Terraform is straightforward, but migrating everything to modules or reworking on HashiCorp Terraform can be complicated and overwhelming. Think thoroughly before implementation, but don't hesitate to try it. All necessary information is available online, and the community is excellent.

On a scale of one to ten, I would rate HashiCorp Terraform as a solution nine out of ten.

Public Cloud

Amazon Web Services (AWS)

What do you like best about the product?

What I like best about HashiCorp Terraform is its ability to automate and standardize infrastructure provisioning across cloud environments. As an administrator, the declarative syntax makes it easy to define infrastructure as code, while the plan and apply workflow gives full visibility and control before making any changes. Terraform’s modular structure helps maintain reusable and scalable configurations, and its cloud-agnostic support allows me to manage AWS, Azure, GCP, and more using a single tool. It simplifies my workflow, reduces manual errors, and makes infrastructure management efficient and predictable.

What do you dislike about the product?

While I truly value Terraform for its automation and flexibility, one area that I find can be challenging is state file management, especially in larger teams. It requires careful handling and secure backend configuration to avoid conflicts and ensure consistency — but it has taught me the importance of proper collaboration practices and the use of remote state backends with locking.

What problems is the product solving and how is that benefiting you?

Manual provisioning replaced with automation – Terraform helps me automate infrastructure deployment, saving time and reducing human error.

Standardized configurations across environments – I can manage multi-cloud infrastructure using consistent, version-controlled code.

Change visibility and control – With the plan/apply workflow, I get clear visibility into changes before they’re made, reducing risk.

We primarily use HashiCorp Terraform  for our infrastructure deployments and cloud deployments. As a cloud architect and infra DevOps architect, we use HashiCorp Terraform  to deploy our code, builds, and set up CI/CD pipelines. We create Terraform code and deploy it through Terraform Enterprise.

Regarding state management and orchestration capabilities of HashiCorp Terraform's impact on our workflows, we had two different environments. Initially, we used Jenkins  for our CI/CD pipelines. Because we primarily work on Azure , we use remote state files for Azure  deployments. Jenkins  runs the HashiCorp Terraform code, and then the state file gets saved in our Azure storage as a remote location. Whenever we require that state file, we can retrieve it from there.

At a later stage, we enhanced the environment by setting up Terraform Enterprise in our environment. Currently, we have it within our environment. We set up Terraform Enterprise with HashiCorp's license. We create modules from HashiCorp Terraform using the Azure ARM provider, and then we set up those modules to apply Azure best practices. We provide this to the development team and other teams so they can reuse these modules and deploy secure codes. We also manage upgrades and the complete lifecycle of TFE, and we provide these services to our other teams.

One of the major benefits of HashiCorp Terraform is that it is platform-agnostic because it supports multiple cloud platforms. This is the biggest advantage.

The state file is one of the key features of HashiCorp Terraform that helps us because whenever there is a drift, it actually helps us identify those and reset the environment to the actual desired state.

From our environment, we have enabled the health monitoring and drift detection features in HashiCorp Terraform. These have been really useful for our environment. It helps us where we do not have HashiCorp Terraform code for the environments and get that created, and whenever there is a manual change, we get to know that.

One issue we have faced with HashiCorp Terraform is that sometimes the latest features that Microsoft suggests are added in their services take some time for HashiCorp Terraform to get enhanced. Sometimes there is that lag where we want some service or configuration which is not yet enabled in the HashiCorp Terraform module.

The initial setup process for HashiCorp Terraform was fine and possible without major challenges. However, currently, our organization helps set up governance and policies, including those related to the OS. There is a challenge where our organization is recommending a specific OS, which is currently not supported by HashiCorp Terraform.

I have been working with HashiCorp Terraform for the last 10 years.

Since it is based on Azure, HashiCorp Terraform is highly scalable.

From the maintenance point of view, it is not difficult to maintain HashiCorp Terraform because primarily all those resources or the infrastructure we set up in Azure, and we have the high availability setup. From that perspective, there haven't been major challenges.

In terms of the stability and reliability of HashiCorp Terraform, I have not had any performance issues with it. There was only one challenge when we installed one of the patches in HashiCorp Terraform, and we lost some database. That was one challenge, which was not a known issue. Later, they identified that there was one defect in that code. Apart from that, there have been no challenges.

Since it is based on Azure, HashiCorp Terraform is highly scalable.

Whenever we face any issues, we escalate it to HashiCorp technical support, and we get that support. We have regular interaction with them. I would rate the HashiCorp technical support an eight on a scale of one to ten, where ten is the best.

Positive

From a configuration management perspective, we have used Jenkins and SCCM. My experience is limited to that, but some of my team members have used Ansible  and others as well.

The major benefit of HashiCorp Terraform in comparison to Jenkins and SCCM is that these are only configuration management tools, but HashiCorp Terraform is a language where you can deploy those, and you provide those providers for different cloud environments. This gives it a tactical advantage. It deals with having a seat, or it always helps having a lesser technical landscape. We don't have to have additional tools or any other feature to develop that IaC  code as well.

When we did the POC and wanted to set up our production environment, it took us around three to four months. Now that we have set up that pipeline for the upgrades, it doesn't take us that long. For the production deployment, currently, it takes us around two weeks, excluding the testing, the stage deployment, development, and deployment.

We have not calculated the measurable benefits recently from using HashiCorp Terraform. On a high level, I would say it has improved our overall environment, speed, and excellence by approximately 20%.

I can provide feedback regarding my experience working with HashiCorp Terraform. We haven't found any major challenges with the integration of HashiCorp Terraform. Frankly speaking, we haven't explored it completely, but for our requirements, it has been working fine.

I have not had any AI-driven projects or AI-driven tasks, nor have I utilized any AI within HashiCorp Terraform yet. I might not be the right person regarding the HashiCorp Terraform licensing part because I haven't been involved from the costing perspective.

Based on my experience, I would recommend HashiCorp Terraform to others, majorly because of the advantages of being platform-agnostic and all those other features. My overall rating for HashiCorp Terraform is eight out of ten.

Microsoft Azure

Microsoft Azure

I use it to deploy our Kubernetes  clusters and Boomi  as well. I can run Boomi  by itself and not worry about Terraform  and Kubernetes , and that's okay. 

However, my use case requires me to run it in a cluster environment to scale up and scale down accordingly and manage costs. This is why I chose Kubernetes. Although it's possible to manually roll it out, I have security requirements to consider for a secure environment. To make it repeatable, I use Bicep or Terraform , as I'm mostly running in Azure . 

I decided on Terraform to manage deployments across multiple environments. This includes a dev environment, a QA environment, and now a production environment. I test and then run Terraform to deploy these environments. In AI, it's more about setting up your environment. 

I develop AI-based products and use Terraform to create a consistent and secure environment in Azure . Once deployed, I get a security score from Azure and receive recommendations for improvements. If a resource is noncompliant under SOC 2, type one or two, ISO, or HIPAA, I make the changes in Terraform, redeploy, and observe score improvements. Terraform aids in ensuring my deployments are correctly configured across environments.

The most valuable feature is predictability. When I need to put something, it is repeatable. I can deploy it in one environment, change the parameter, and it will work in another. If changes are needed, I track who did what because my Terraform scripts are version-controlled. This reduces guesswork and trial and error from the UI, replacing it with code, which enhances maintainability. In cloud environments, manual configurations can be forgotten or misunderstood if the original person leaves, but Terraform ensures documentation and consistent configurations.

The area for improvement is the speed at which resources become available. When a new resource is introduced in AWS  or Azure, especially since I work mostly in Azure, how quickly can it be integrated into my Terraform scripts ensuring rapid availability of resources is crucial.

I have used the solution for two to three years now.

The solution is stable because I can define which version I want to use. I am not at the mercy of the latest version. I can choose a stable version and decide whether to upgrade based on its performance.

The solution scales well. Terraform runs only when our pipelines run and parallelizes resource creation/updates whenever possible.

The setup is straightforward, but mastering it may take a day or two. Maintenance requires significant expertise. The challenge lies in understanding the environments being created, not Terraform itself.

I am using the free version. The paid version is necessary when you run it and manage it in the environment, however, I only use Terraform runtimes. The documentation is excellent, and understanding how to read it is crucial. 

Once I understand the different concepts of Terraform, it becomes straightforward, allowing for further capabilities. A major challenge was applying Terraform to existing resources, yet now the new import method is much improved. 

My product rating is eight out of ten.

Public Cloud

Microsoft Azure

The primary use case for Terraform  is the deployment of infrastructure as a code, creating pipelines, and deploying scripts for services like VPC, EC2 , and other AWS  services. I also use Terraform  for managing multi-cloud environments, easily connecting with services like AWS , Azure , and GCP.

The most valuable feature of Terraform is its ability to easily connect and manage various cloud services, such as AWS, Azure  and GCP. I appreciate that with just a few commands, Terraform can deploy tools into the server, which simplifies the process significantly. 

Additionally, the support for YAML and Bash scripts allows for straightforward deployment. Terraform's infrastructure as a code tool facilitates deploying code on tools, and once configured with AWS and local Terraform systems, it can be reused multiple times without much issue.

When connecting to services on a hybrid cloud, I sometimes face issues with understanding usernames or passwords, leading to loss of connectivity. User education could improve this.

I have been using Terraform for approximately three years.

Once the configuration is set, there are generally no significant stability issues. Terraform runs smoothly.

Scalability is effective, and I would rate it a ten out of ten.

I have not faced any significant issues that required me to contact support, however, they provide mail IDs, a portal, and contact numbers for assistance. I would rate it nine out of ten.

Positive

I used Ansible  before using Terraform. Currently, I prefer Terraform for its ease of use, though Ansible  is also very efficient with few commands.

The initial setup is straightforward, using YAML and Bash scripts for creating infrastructure, which can then be easily deployed using tools like Visual Studio Code.

I use the open-source version of Terraform, so there is no cost for me. There is a paid version available for clients who require premium features such as security and compliance.

I have worked with Ansible, which is also effective for connecting to servers and services with minimal commands.

On a scale of one to ten, I rate Terraform a ten. 

Ansible is also highly effective when minimal command usage is required.

Hybrid Cloud

Amazon Web Services (AWS)