Glassfish Grizzly FilterChain vs WebSocketApplication - websocket

What is the difference for FilterChain and WebSocketApplication? From what I understand, FilterChain are processors that transforms the state of a message and WebSocketApplication is an interface that processes incoming message. Both sounds like they process messages. What is the difference here?

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Quarkus Mutiny and Imperitave vs Reactive

TL;DR: which is more pattern? Using Mutiny + Imperative resteasy, or just use Reactive resteasy?
My understanding is Mutiny allows for me to pass Quarkus a longer running action, and have it handle the specifics of how that code gets run in the context. Does using Reactive provide equal or more benefit than Mutiny+imperative? If from a functional point of view from a thread handling perspective it's equal or better, then Reactive would be great as it requires less code to maintain (Creating Unis, etc). However, if passing a Uni back is significantly better, then it might make sense to use that.
https://quarkus.io/guides/getting-started-reactive#imperative-vs-reactive-a-question-of-threads
Mutiny + imperative:
#GET
#Path("/getState")
#Produces(MediaType.APPLICATION_JSON)
public Uni<State> getState() throws InterruptedException {
return this.serialService.getStateUni();
}
Reactive:
#GET
#Path("/getState")
#Produces(MediaType.APPLICATION_JSON)
public State getState() throws InterruptedException {
return this.serialService.getState();
}
As always, it depends.
First, I recommend you to read https://quarkus.io/blog/resteasy-reactive-smart-dispatch/, which explains the difference between the two approaches.
It's not about longer action (async != longer); it's about dispatching strategies.
When using RESTEasy Reactive, it uses the I/O thread (event loop) to process the request and switches to a worker thread only if the signature of the endpoint requires it. Using the I/O thread allows better concurrency (as you do not use worker threads), reduces memory usage (because you do not need to create the worker thread), and also tends to make the response time lower (as you save a few context switches).
Quarkus detects if your method can be called on the I/O thread or not. The heuristics are based on the signature of the methods (including annotations). To reuse the example from the question:
a method returning a State is considered blocking and so will be called on a worker thread
a method returning a Uni<State> is considered as non-blocking and so will be called on the I/O thread
a method returning a State but explicitly annotated with #NonBlocking is considered as non-blocking and so will be called on the I/O thread
So, the question is, which dispatching strategy should you use?
It really depends on your application and context. If you do not expect many concurrent requests (it's hard to give a general threshold, but it's often between 200 and 500 req/sec), it is perfectly fine to use a blocking/imperative approach. If your application acts as an API Gateway with potential peaks of requests, non-blocking will provide better results.
Remember that even if you choose the imperative/blocking approach, RESTEasy Reactive provides many benefits. As most of the heavy-lifting request/response processing is done on the I/O thread, you get faster and use less memory for... free.

Send TraceId across Threads

We have a distributed application following microservice Architecture. In one of our microservice we are following producer-consumer pattern.
The producer receives requests, persists it to database, pushes the request into a BlockingQueue and sends the response back to the client. The consumer running on a separate thread is listening to the blocking queue. The moment it gets the request object it performs specific operations on it.
The request received by the producer is persisted to the database asynchronously using CompleteableFutures.
The problem here is how to forward TraceId to the methods processing the requestObject inside consumer thread. Since the consumer thread might process these objects much later after the response is sent to the consumer.
Also how to forward the traceId across Asynchronous calls?
Thanks
That's an interesting question. I think that what you can do is to persist the request together with its headers. Then on the consumer side you can use the SpanExtractor interface in a similar way as we do here - https://github.com/spring-cloud/spring-cloud-sleuth/blob/v1.3.0.RELEASE/spring-cloud-sleuth-core/src/main/java/org/springframework/cloud/sleuth/instrument/web/TraceFilter.java#L351 (Span parent = spanExtractor().joinTrace(new HttpServletRequestTextMap(request));). That means that from the HttpServletRequest we're extracting values to build a span. Then, once you've retrieved the Span, you can just use Tracer#continueSpan(Span) method before processing, and then Tracer#detach(Span) in the finally block. E.g.
Span parent = spanExtractor().joinTrace(new HttpServletRequestTextMap(request));
try {
tracer.continueSpan(parent);
// do whatever you need
} catch(Exception e) {
tracer.addTag("error", doSthWithTheExceptionMsg(e));
} finally {
tracer.detach(parent);
}

Kafka stream with Http request

I want to realize the next flow of kafka stream
from(kafka topic) -> transform (here should be http request) -> to (kafka topic)
Is it correct to set http request during tranformaton in kafka stream or its more correct to use standart consumer ?
It is possible but not recommended to do external requests within a transform() because the request would need to be synchronous and thus negatively impacts performance (ie, throughput).
However, if this is no concern for you it's no problem to do external request.

Retaining MDC with Spring AMQP Request/Reply

I have two services, A and B, communicating via Spring Remoting with AMQP. A exposes a REST API and populates the MDC (Mapped Diagnostic Context) with a UUID.randomUUID() (from within a Filter) on every request (and clears it when processing is finished). Now I'd like to pass this UUID to B in the request/reply cycle so that...
... when a consumer in B starts processing the request, its MDC is populated with the UUID.
... when the consumer in B finishes processing the request, its MDC is cleared.
I've extended SimpleMessageConverter so as to set an AMQP header containing the UUID, but I don't really seem to figure out how/where to populate and how/where to clear the MDC in B. Can anyone please shed some light?
Inject another custom message converter into the AmqpInvokerServiceExporter.
Set the MDC (from the header) in fromMessage(), clear it when the reply is mapped (in toMessage).

What is OncePerRequestFilter?

Documentation says org.springframework.web.filter.OncePerRequestFilter "guarantees to be just executed once per request". Under what circumstances a Filter may possibly be executed more than once per request?
Under what circumstances a Filter may possibly be executed more than once per request?
You could have the filter on the filter chain more than once.
The request could be dispatched to a different (or the same) servlet using the request dispatcher.
A common use-case is in Spring Security, where authentication and access control functionality is typically implemented as filters that sit in front of the main application servlets. When a request is dispatched using a request dispatcher, it has to go through the filter chain again (or possibly a different one) before it gets to the servlet that is going to deal with it. The problem is that some of the security filter actions should only be performed once for a request. Hence the need for this filter.
To understand the role of OncePerRequestFilter, we need to first clearly understand how a normal filter behaves.
When you want some specific code to execute just before or after servlet execution, you create a filter which works as:
code1 ===> servlet execution (using chain.doFilter()) ===> code2
So code1 executes before servlet and code2 after servlet execution.
But here, while servlet execution, there can be some other request to a different servlet and that different servlet is also having this same filter. In this case, this filter will execute again.
OncePerRequestFilter prevents this behavior. For our one request, this filter will execute exactly one time (no more no less). This behavior is very useful while working with security authentication.
A special kind of GenericFilterBean was introduced to live in Servlet 3.0 environment. This version added a possibility to treat the requests in separate threads. To avoid multiple filters execution for this case, Spring Web project defines a special kind of filter, OncePerRequestFilter. It extends directly GenericFilterBean and, as this class, is located in org.springframework.web.filter package. OncePerRequestFilter defines doFilter method. Inside it checks if given filter was already applied by looking for "${className}.FILTER" attribute corresponding to true in request's parameters. In additionally, it defines an abstract doFilterInternal((HttpServletRequest request, HttpServletResponse response, FilterChain filterChain) method. Its implementations will contain the code to execute by given filter if the filter hasn't been applied.
Under what circumstances a Filter may possibly be executed more than once per request?
A filter may be invoked as part of a REQUEST or ASYNC dispatches that occur in separate threads. We should use OncePerRequestFilter since we are doing a database call to retrieve the principal or the authenticated user, there is no point in doing this more than once. After that, we set the principal to the security context.
Authentication auth = jwtTokenProvider.getAuthentication(token);
SecurityContextHolder.getContext().setAuthentication(auth);
where jwtTokenProvider is your service for getting authentication from the jwt token.
OncePerRequestFilter implements logic to make sure that the filter’s doFilter() method is executed only one time per request.

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