cadence VS mats3

Uber | Software Engineers | Hybrid (Denmark) | https://www.uber.com/dk/en/careers/locations/aarhus/

Work with an amazing team responsible for the infrastructure software that makes Uber’s data centers around the world reliable and scalable. If you want to solve the toughest engineering challenges alongside some of the smartest people in the industry, Uber Aarhus is the right place for you.

The team in Aarhus build and operate the stateless and stateful compute platforms used by nearly every other engineer in the company (Up - https://www.uber.com/en-GB/blog/up-portable-microservices-re... and Odin - https://www.uber.com/en-GB/blog/how-uber-optimized-cassandra...) as well as other related infrastructure projects such as Cadence - https://github.com/uber/cadence.

May be this..https://cadenceworkflow.io/

a managed esb orchestration for example is exactly same as step functions and workflow engines like cadence - https://github.com/uber/cadence

Having done a reasonable amount of messaging code in my time, I would say the final form of this sort of thing might look more like Cadence[0] than anything like this.

[0] https://github.com/uber/cadence

Emit events from your primary DB (postgres, etc.) to something like kafka or rabbitmq and then catch that in your search engine. There's also some end-to-end solutions like temporal (temporal.io) or cadence (https://cadenceworkflow.io/)

The “restart from where it failed”-aspect was a big reason for why I made Mats3. It is message-based, async, transactional, staged stateless services, or message-oriented asynchronous RPC. Due to the transactionality, and the “state lives on the wire”, if a flow fails, it can be restarted from where it left off.

https://mats3.io

I am truly finding it hard to explain it. I have tried along a dozen angles. I actually think it is a completely new concept - and that might be the problem.

There is an illustration on the front-page: https://mats3.io/

Here's a set of small answers to "What is Mats?": https://github.com/centiservice/mats3/blob/main/README.md#wh...

Here's a way to code up Mats3 endpoints using JBang and a small toolkit which makes it extremely simple to explore the ideas: https://github.com/centiservice/mats3/blob/main/README.md#wh...

If you read these and then get it, I would be extremely happy if you gave me a sentence or paragraph that would have led you to understanding faster!

The use of JMS is just a transport. I could really have used anything, incl. any MQ, or ZeroMQ, or plain TCP - or just a shared table in a database.

Wrt. WebSockets, that is a transport typically between a server, and a end-user client, e.g. an iOS App. Actually, there's also a "sister project", MatsSockets, that bring the utter async-ness of Mats3 all the way out to the client, e.g. a webpage or an app. https://matssocket.io/

NATS is just a message queue, with some ability to orchestrate. I do not like this concept of orchestration as an external service, that is one of the founding ideas of Mats3: Do the orchestration within each service, as you would do if you employed REST as the ISC mechanism.

Read more about mats3 here: https://mats3.io/

I've made a Java library to facilitate the latter. https://mats3.io/ - you can start reading here: https://mats3.io/docs/message-oriented-rpc/, or test out some code right away, using JBang, here: https://mats3.io/explore/jbang-mats/

I have explained about this on the frontpage of Mats3: https://mats3.io/, and more in-depth in the first step of the "Walkthrough": https://mats3.io/docs/message-oriented-rpc/ - and even more into it at "Rationale for Mats", here: https://mats3.io/background/rationale-for-mats/

JBang’s tagline: “Lets Students, Educators and Professional Developers create, edit and run self-contained source-only Java programs with unprecedented ease.”

Mats3’s tagline: “Message-Oriented Async RPC. Message-based Interservice Communication made easy! Naturally resilient and highly available microservices, with great DevX and OpsX.”

JBang is a cool "execute single Java source file with dependencies" solution, which offers a simple way to test new libraries. The article tries to showcase Mats3's core concepts through a series of JBang scripts.

To streamline the process, a small library called 'MatsJbangKit' has been developed, which not only takes care of pulling up the Mats infrastructure but also depends on all the necessary dependencies. This means users only need to reference this single library in their JBang scripts. The aim is to pique curiosity and inspire further exploration of Mats3 and its potential.

If you like it, a star on Github would be much appreciated: https://github.com/centiservice/mats3

This is a "tack on"-tool to the otherwise fully async nature of Mats/messaging.

> For this to really work well, the message passing has to be integrated with the CPU dispatcher

It sounds like you are 100% set on speed. This is not really what Mats is after - it is meant as a inter-service communcation system, and IO will be your limiting factor at any rate. Mats sacrifices a bit of speed for developer ergonomics - the idea is that by easily enabling fully async development of ISC in a complex microservice system, you gain back that potential loss from a) actually being able to use fully async processing (!), and b) the inherent speed of messaging (it is at least as fast as HTTP, and you avoid the overhead of HTTP headers etc.

It is mentioned here, "What Mats is not": https://github.com/centiservice/mats3#what-mats-is-not