tflint VS serverless-application-model

‍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.

The complete solution with SAM is available here.

There are many options to deploy Serverless Applications in AWS and one of them is SAM, the Serverless Application Model. I chose to use it here, because it doesn't add too many layers of abstraction between what's being deployed and the code we write and our infrastructure is quite simple.

The solution uses AWS SAM with the global configuration for Lambda functions and the public API you can use to access Apache Zeppelin. The stack deployment provides the URL as an output value.

When you combine this with the AWS Serverless Application Model you can also very easily include your dependencies. Or use a compiled language like golang for your Lambda functions. You simply run sam build before you run the aws cloudformation package and aws cloudformation deploy commands. SAM will build the binary and update the template to point to the newly built binary. Package will then upload it to S3 and replace the local reference to the S3 location. Deploy can then create or update the stack or you can use the CloudFormation integration in CodePipeline.

I'm a big fan of using an Infrastructure as Code (IaC) approach for any project. My go to tools for this are the Servlerless Application Model (SAM) and it's associated CLI (SAM CLI). For more official use cases and for cross platform apps I typically use Terraform.

AWS SAM

Kicking off the tour and not starting a war, but I'm going to be using the Serverless Application Model.

The diagram here is super simple. I'm going to write something a little later that shows how this code could fit into a bigger workflow, but for now, I'm keeping it basic. And yes, that's the SAM Squirrel in there.

Interestingly, AWS CDK and SAM are both explicitly mentioned. While CDK broadly addresses Infrastructure as Code, SAM is highlighted for its role in developing serverless data pipelines - a hugely underrated concept.

Naturally, there are several options available to declare your cloud resources. The options with the most popularity are the CDK, AWS CloudFormation, SST, Serverless framework, Terraform, and AWS SAM. There are others, but when talking about Infrastructure as Code (IaC), these are the ones you hear about most often.