digger VS tflint

Currently, Github Actions is de-facto the only fully supported CI platform in Digger, we’ve been building it as a CI-agnostic tool (https://github.com/diggerhq/digger) from get go. We keep getting requests to support more CI systems on our community slack and over Github issues (https://github.com/diggerhq/digger/issues/81).

Unlike other automation tools for Terraform, Digger doesn’t run jobs on the server; instead it uses your CI (like Actions) as a compute backend. This is more secure and also much cheaper if you use your own runners in your CI.

But each CI and each VCS is ever so slightly different; and we are now at a crossroads - Should we build support for more CI platforms, or more features for GitHub Actions? We’d love any thoughts/inputs!

We just had a user submit an issue and a PR to revert the changes we made earlier that remove the option to disable telemetry. We feel like it’s a fair ask to share usage data with authors of an open-source tool that’s early in the making; but the user’s viewpoint is also perfectly understandable. Are we in the wrong here?

https://github.com/diggerhq/digger/issues/1179

Surely we aren’t the first open-source company to face this dilemma. We don’t want to alienate the community; but losing visibility of usage doesn’t sound great either. Give people the “more privacy” button and most are going to press it. Is there a happy medium?

Detecting and managing drift in Terraform is a multifaceted process. The use of Terraform commands such as terraform refresh and terraform plan plays a critical role in identifying drifts. Additionally, periodic monitoring of the infrastructure using these commands can aid in early detection and prevention of larger issues. Tools like Digger and Terraform Cloud offer dedicated drift detection and remediation mechanisms. These tools provide continuous monitoring and notifications, enabling teams to stay informed about the state of their infrastructure.

Star us on GitHub | Check out Docs | Blog | Slack

I would be extremely grateful if you could give us a star & share your thoughts in the comments section below https://github.com/diggerhq/digger

Check Digger's repo on GitHub

Digger is an Open Source Infrastructure as Code management tool that helps orchestrate IaC such as Terraform & OpenTofu within GitHub Actions. Digger reuses compute used for application code so that you don't overpay for 3rd party managed compute for IaC. This approach eliminates the duplication of CI/CD infrastructure such as compute, jobs, and logs, and reduces security concerns by keeping sensitive data within the CI job. Digger's integration with existing CI systems offers scalability by leveraging on-demand compute resources and enhances security by confining data within the existing CI environment.

Digger is an Open Source IaC management platform that allows you to orchestrate terraform/OpenTofu in your CI/CD system. It helps you resue async jobs infrastructure with compute, orchestration, logs, etc of your existing CI. Digger also has a pro version built on top of Digger’s community edition. Digger’s “bring your own compute” ensures that users have private runners by defualt and don’t have to pay for it additionally. Digger pro gives team leads, managers and IaC practitioners dashboards, Drift Detection, RBAC via OPA policies and concurrency so they can help guide the team.

We have this issue filed by a user and cannot quite decide internally what to do about it. It is clear that allowing everyone who comments to trigger apply is problematic. And we have this covered by the RBAC via OPA feature that allows users to set granular rego policies for who can do what. But it can also be viewed as an overkill to introduce the whole policy-as-code setup for a basic restriction like this.

‍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.