shadow VS LocalStack

So: I am making a JavaFX application to act as a remote console for my server. I'm the only person that will have a copy of it, so it doesn't need to be snazzy or 100% efficient. I have turned the project into a jar via ShadowJar, turned that into an EXE via Launch4j, and yesterday turned that into an installer via Inno.

I’ve never tried this and I I’m not libgdx expert, but you can try running a Uber jar with shadow. it’s the Gradle equivalent of the shade plug-in for maven builds.

When you get into a situation where you need to sandbox a dependency within another, including this example, where you want each of your dependencies to get its own unique instance of their dependency, you can "shadow" the dependency that is to be sandboxed this way. Look into https://github.com/johnrengelman/shadow.

Try using the shadow plugin for gradle https://github.com/johnrengelman/shadow

and also apparently, it's a problem with shadowJar itself https://github.com/johnrengelman/shadow/issues/713

Behind the scenes, Shadow creates a FatJar with all the things we may need in the future.

Note: **According to Serverless documentation you can use the command **serverless deploy -v. However, with Java-based-projects that’s not true because it needs to create a Fatjar with all the needed requirements (so the command will fail). By default, Serverless will set **shadow** as a dependency in the gradle file for those purposes. The deploy command will generate a build file called -all.jar that is the one that’s going to be uploaded to the AWS Lambda function.

The result .jar is going to submitted to Apache Spark cluster (e.g. spark-submit command). So, it should contain all runtime artefacts. Unfortunately, the standard Spring Boot packaging does not put the dependencies in the way Apache Spark expects it. So, we'll use shadow-jar Gradle plugin. Take a look at the example below.

I've writen many Kotlin+Gradle projects that produce jars without the shadow plugin. They're not fat, shaded, standalone executable jars though - is that what you need?

Later you can use any S3 compatible storage because the code I write will still work, but for testing purposes on my local machine, I will use LocalStack:

Acesse o site da LocalStack e faça login.

To give this a slightly different spin:

--> "The best optimization is simply not spinning things up."

At least for local development and testing, as made possible by LocalStack (https://localstack.cloud), among other local testing solutions and emulators.

We've seen so many teams fall into the trap of "someone forgot to shut down dev resource X for a week and now we've racked up a $$$ bill on AWS".

What is everyone's strategy to avoid this kind of situation? Tools like `aws-nuke` (https://github.com/rebuy-de/aws-nuke) are awesome (!) to clean up unused resources, but frankly they should not be necessary in the first place.

(For others who hadn't heard of it: localstack is

LocalStack Website

O Localstack: https://localstack.cloud/, é um recurso que possibilita simular diversos recursos AWS (dynamoDB, s3, iam, cognito, ses), dentro da sua máquina, utilizando o docker.