troposphere VS dashboard

Under the IaC category, in July 2023, AWS added loops to CloudFormation, finally ticking a box the community has been asking for since troposphere. I suspect that, in combination with the Terraform licensing changes, it may keep people using CloudFormation for a while longer.

Because ECS Compose-X uses Troposphere, I was able to create a very light and simple python library(https://github.com/JohnPreston/troposphere-awscommunity-applicationautoscaling-scheduledaction) to distribute the resource for other Troposphere users to re-use.

Written in house, but the library troposphere is the primary component of how it is built. Example stacks are here.

I am kind of going off topic here, but isn't the point of being an SA to be created with code services to deliver solutions at scale that are cost-effective? How in the hell can you do that when you can't write a simple Python template that generates code at 50 times the rate you can manually? How can you ever be expected to deploy a serverless solution if you can't write any code yourself? There has to be some level of proficiency there.

Wouldn't using troposphere[1] be easier?

[1] https://github.com/cloudtools/troposphere

You might have seen some tutorials on how to set up S3 buckets using the AWS Console. This works fine, but I'm a firm believer of managing your resources with code. I've chosen the native solution of AWS, called AWS CloudFormation. This makes it easier to reproduce the setup if I ever need to tear it down of move it to another account or region. Below is the full CloudFormation template, I've used a framework called Troposphere, a Python library that creates CloudFormation.

For CF for example I no longer write template in yaml or shudders json, and instead I use troposphere.

refer : https://github.com/cloudtools/troposphere

Additionally, feel free to install the Tekton dashboard to visualize our pipeline in a GUI using the Tekton Dashboard.

Tekton Dashboard and Hub Use web-based graphical interfaces to run pipelines and observe pipeline execution logs, resource details, and resources for the entire cluster (see dashboard in Figure 3).

after downloading the Read Only YAML from this GitHub link. Next we setup the persistent volume, refer to the generated EFS IDs from Terraform run in your PV definition, here's an example for a PV and PVC that will be used by a maven task for running tekton pipeline