What is Vert.x?
Who uses Vert.x?
Here are some stack decisions, common use cases and reviews by companies and developers who chose Vert.x in their tech stack.
We use Quarkus with native compilation in GraalVM for our global REST-API "Charon", that can be used by every developer to request user, server and game-data (protected through OAuth2). Quarkus offers a reliable framework, library and stack for high-quality APIs and integrates Vert.x into its core.
GraalVM pushes the performance boundaries even further with the ability to perform ahead-of-time native compilation so we can reach an incredible small memory-footprint and fast bootup-times that we need for our microservices architecture.
We use GraphQL for the communication between our Minecraft-Proxies/Load-Balancers and our global Minecraft-Orchestration-Service JCOverseer.
This connection proved to be especially challenging, as there were so many available options and very specific requirements and we tried our hardest to put as little complexity into this interface as possible.
Initially we considered designing our very own Netty based Packet-Protocol. While the performance of this approach probably would've been noteworthy, we would have had to write a lot of packets as the individual payloads would differ a lot and for the protocol specification a new project would've been needed, so we scrapped that idea.
Our second idea was to use a combination of Redis Key/Value store (in particular the ability to write whole, complex sets as the values of keys) for existing data, Redis Pub-Sub for the synchronization of new/changed/deleted data and a Vert.x based REST API for the mutation requests of the clients. While this would certainly have been possible, we decided against it, as redis offers no real other data types than strings and typing was important to us.
So we finally settled for GraphQL as it would allow us to define dynamic queries and mutations and additionally has subscriptions in store, so we would only need one component instead of three separate. The proxies register as subscribers to the server changes channel and fetch the current data set in advance. If they need to request changes, this is done through a mutation in GraphQL aswell.
The status of the invidiual servers is fetched through Docker healthchecks and a Docker client in the orchestration service, that subscribes to changed HEALTHINESS values in docker. If a service becomes unhealthy it is unregistered and synchronized through GraphQL. The healthcheck is comparable to a ping packet that expects a response in a given time frame.
- Simple concurrency model