tflint VS terraform

‍TFLint is a Terraform linter focused on possible errors, best practices, and style conventions in your Terraform code.

TFlint is a powerful linter for Terraform, designed to catch errors and issues that terraform plan may not detect. As Terraform grows in popularity for infrastructure as code, the need for robust tools to ensure code quality and reliability becomes paramount. TFlint fulfills this need by analyzing Terraform configurations to find problems that are not covered by syntax checks. It checks for things like unsuitable AWS instance types, incorrect IAM policy syntax, and the use of deprecated syntax or features. By integrating TFlint into the development process, users can proactively identify potential problems, improving the stability and efficiency of their infrastructure deployments. This additional layer of validation is crucial for maintaining high standards in complex, cloud-based infrastructures.

Looking at the description, https://github.com/terraform-linters/tflint , I think it's not what I am looking for. The reason I used a different tcp port is to make the health check on load balancer fail. It's also the same as not changing the tcp port but developer making a code change in their javascript, nodejs, java, etc fail to start properly. If that happens, load balancer's health check will fail as well.

TFLint is an open-source infrastructure as code linter tool that helps developers and DevOps teams identify potential issues and errors in their Terraform code by checking the Terraform configuration files for best practices, coding standards, and policy compliance.

Indeed, that is the case, atm. Your comment got me searching a little bit more. It seems that they are planning to implement a flag for small fixes https://github.com/terraform-linters/tflint/issues/266

Sounds like tflint to me!

I created a .tflint.hcl with the following content: https://github.com/terraform-linters/tflint/blob/master/docs/user-guide/config.md (The example)

TFLint: This is a Terraform linter that checks for errors and best practices in your Terraform code. TFLint helps to catch common mistakes, such as variable name clashes, missing required variables, or invalid resource arguments. It also checks for compliance with best practices, such as naming conventions and resource ordering. By using TFLint, you can catch errors early on, which helps to improve the quality of your Terraform code.

tflint: Linter para Terraform, serve para avisar sobre problemas com sintaxe, erros nos principais provedores de nuvem, garantir boas práticas e outras coisas.

State Encryption was one of those long requested features[0] (I had it on my ideas list for years[1]) that Hashicorp didn't have much incentive to build. I don't think it has to with distancing opentofu as such, but the opentofu team prioritizing the right things that customers actually need.

[0]: https://github.com/hashicorp/terraform/issues/9556

[1]: https://github.com/captn3m0/ideas#-mars-terraform-remote-htt...

https://github.com/hashicorp/terraform/issues/34402

I’m not a lawyer and have no idea who is right or wrong but I understand why Hashicorp is scrutinizing this.

Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.

Each app’s front end is built with Qwik and uses Tailwind for styling. The server-side is powered by Qwik City (Qwik’s official meta-framework) and runs on Node.js hosted on a shared Linode VPS. The apps also use PM2 for process management and Caddy as a reverse proxy and SSL provisioner. The data is stored in a PostgreSQL database that also runs on a shared Linode VPS. The apps interact with the database using Drizzle, an Object-Relational Mapper (ORM) for JavaScript. The entire infrastructure for both apps is managed with Terraform using the Terraform Linode provider, which was new to me, but made provisioning and destroying infrastructure really fast and easy (once I learned how it all worked).

For example, integrating Terraform for infrastructure as code (IaC) into the IDP can streamline updates and rollbacks.

In this project, you will understand and get hands on experience around the entire concept around CI/CD from applications perspective. To fully gain real expertise around this idea, it is best to see it in action across different programming languages and from the platform perspective too. From the application perspective, we will be focusing on PHP here; there are more projects ahead that are based on Java, Node.js, .Net and Python. By the time you start working on Terraform, Docker and Kubernetes projects, you will get to see the platform perspective of CI/CD in action.

Infrastructure as Code (IaC) is an important part of any true hosting operation in the public cloud. Each of these platforms has their own IaC solution, e.g. AWS CloudFormation. But they also support popular open-source IaC tools like Pulumi or Terraform. A category of tools that also needs to be discussed is API gateways and other app-specific load balancers. There are applications for internal consumption, which can be called microservices if you have a lot of them. And often microservices use advanced networking options such as a service mesh instead of just the native private network offered by a VPC.

To quickly deploy the architecture, we will be using Terraform. With Terraform, we can automate the deployment process and have our infrastructure up and running in minutes.