New Template Suggestion Java+Quarkus Native

[AayushSaini101]

Hi Team,

I want to propose a new idea for a template that is Java+Quarkus. Quarkus is a very popular and open-source framework as well as very fast-growing in the cloud native community, I also used it in my company,

Around the world, in 2024, over 1334 companies started using Quarkus https://6sense.com/tech/other-dev-tools/quarkus-market-share.

Let me know your thoughts on this, thanks :)

@asyncapi/tsc_members

[lbroudoux]

Hello!

This is a super exciting idea! I'm a big fan of Quarkus.

At Microcks, we provide a demo of using Microcks via a Quarkus Dev Service. The app demonstrates using Quarkus + Kafka with AsyncAPI with all the things you need for mocking messages and validating your producer and consumer are actually conformant to an AsyncAPI spec.

Maybe you can have a look at it here: https://github.com/microcks/microcks-quarkus-demo and see if some elements can integrate your template.

Cheers,

[edeandrea]

I would also be very careful with the comparison link you are sharing in this discussion (https://www.iot83.com/spring-boot-vs-quarkus-end-to-end-comparison-guide/). The numbers there in the screenshot don’t really make sense to me as they are not consistent with what is seen in industry. Additionally, the article itself isn't even dated. There is no way to know how old it is.

I venture to guess that their benchmark isn’t set up correctly or isn’t comparing “apples-to-apples”. We’ve seen this on other more prominent sites as well. Nowhere in that article do they show how they measured, what technologies were used to measure, how the comparison apps were constructed, or what versions of each they are comparing.

The screenshot you are sharing in the comment doesn't look like it came from that article, either. It looks to be a screenshot from some other site, probably the same other prominent site I mentioned earlier. The whole article looks to be a copy of an article on the more prominent site I mentioned.

I'd be very careful about using data like this that isn't completely transparent as to how it was gathered.