I want to make a req/res request from IConsumer.Consume() method, but I don't see any method on ConsumeContext<> that returns a reference to IRequestClient<,>. Do I need to hold a reference to IBusControl somewhere and use it or I can use context somehow?
In this case, it is best to create the request client outside of the consumer and pass it as a dependency to the consumer as an IRequestClient<,> interface. The request client is created with IBus, which is outside of the consumer context.
It also ensures that the request will be less likely to deadlock with the broker because responses are received on the bus endpoint, and not the receive endpoint of the consumer (which, if you had a concurrency limit of 1, would never finish).
It's also not possible to connect consumers to a started receive endpoint, which is a requirement of the request/response handling (it happens under the covers). The bus, however, can connect consumers for messages which are sent (responses are sent to the bus address, versus being published) which is why it is used for responses to the requests.
To keep message tracking continuous, it may be nice to set the InitiatorId on the outbound request to the CorrelationId of the consumer message, as well as copying the ConversationId. This helps with tracing and keeping track of the overall message command/event flow.
Related
I am implementing a REST API that internally places a message on a message queue and receives a message as a response on a different topic.
How could API implementation handle publishing and consuming different messages and responds to the client?
What if it never receives a message?
How does the service handle this time-out scenario?
Example
I am implementing a REST API to process an order. The implementation internally publishes a series of messages to verify the payment, update inventory, and prepare shipping info. Finally, it sends the response back to the client.
Queues are too low-level abstraction to implement your requirements directly. Look at an orchestration solution like temporal.io that makes programming such async systems trivial.
Disclaimer: I'm one of the founders of the Temporal open source project.
How could API implementation handle publishing and consuming different messages and responds to the client?
Even though messaging systems can be used in RPC like fashion:
there is a request topic/queue and a reply topic/queue
with a request identifier in the messages' header/metadata
this type of communication kills the promise of the messaging system: decouple components in time and space.
Back to your example. If ServiceA receives the request then it publishes a message to topicA and returns with an 202 Accepted status code to indicate that the request is received but not yet processed completely. In the response you can indicate an url on which the consumer of ServiceA's API can retrieve the latest status of its previously issued request.
What if it never receives a message?
In that case the request related data remains in the same state as it was at the time of the message publishing.
How does the service handle this time-out scenario?
You can create scheduled jobs to clean-up never finished/got stuck requests. Based on your business requirements you can simple delete them or transfer them to manual processing by the customer service.
Order placement use case
Rather than creating a customer-facing service which waits for all the processing to be done you can define several statuses/stages of the process:
Order requested
Payment verified
Items locked in inventory
...
Order placed
You can inform your customers about these status/stage changes via websocket, push notification, e-mail, etc.. The orchestration of this order placement flow can be achieved for example via the Saga pattern.
Use case: I have a use case where the client send a request to an microservice endpoint (the producer) which does some operations and produce a message to the kafka to be consumed by a consumer which stores some data into his own database. Immediately after this, the client send another request to the consumer microservice to get latest updates (which should include data stored previously).
But the problem is that the client is sending the second request without waiting for consumer to finish storing data (for the first request).
Question: how should I handle it? Can somehow wait for consumer to finish storing data?
What I tried: I tried to add thread.sleep into producer endpoint, but I don't like that solution.
Thanks.
I come across many blog that say using rabbitmq improve the performance of microservices due to asynchronous nature of rabbitmq.
I don't understand in that case how the the http response is send to end user I am elaborating my question below more clearly.
user send a http request to microservice1(which is user facing service)
microservice1 send it to rabbitmq because it need some service from microservice2
microservice2 receive the request process it and send the response to rabbitmq
microservice1 receive the response from rabbitmq
NOW how this response is send to browser?
Does microservice1 waits untill it receive the response from rabbitmq?
If yes then how it become aynchronous??
It's a good question. To answer, you have to imagine the server running one thread at a time. Making a request to a microservice via RestTemplate is a blocking request. The user clicks a button on the web page, which triggers your spring-boot method in microservice1. In that method, you make a request to microservice2, and the microservice1 does a blocking wait for the response.
That thread is busy waiting for microservice2 to complete the request. Threads are not expensive, but on a very busy server, they can be a limiting factor.
RabbitMQ allows microservice1 to queue up a message to microservice2, and then release the thread. Your receive message will be trigger by the system (spring-boot / RabbitMQ) when microservice2 processes the message and provides a response. That thread in the thread pool can be used to process other users' requests in the meantime. When the RabbitMQ response comes, the thread pool uses an unused thread to process the remainder of the request.
Effectively, you're making the server running microservice1 have more threads available more of the time. It only becomes a problem when the server is under heavy load.
Good question , lets discuss one by one
Synchronous behavior:
Client send HTTP or any request and waits for the response HTTP.
Asynchronous behavior:
Client sends the request, There's another thread that is waiting on the socket for the response. Once response arrives, the original sender is notified (usually, using a callback like structure).
Now we can talk about blocking vs nonblocking call
When you are using spring rest then each call will initiate new thread and waiting for response and block your network , while nonblocking call all call going via single thread and pushback will return response without blocking network.
Now come to your question
Using rabbitmq improve the performance of microservices due to
asynchronous nature of rabbitmq.
No , performance is depends on your TPS hit and rabbitmq not going to improve performance .
Messaging give you two different type of messaging model
Synchronous messaging
Asynchronous messaging
Using Messaging you will get loose coupling and fault tolerance .
If your application need blocking call like response is needed else cannot move use Rest
If you can work without getting response go ahaead with non blocking
If you want to design your app loose couple go with messaging.
In short above all are architecture style how you want to architect your application , performance depends on scalability .
You can combine your app with rest and messaging and non-blocking with messaging.
In your scenario microservice 1 could be rest blocking call give call other api using rest template or web client and or messaging queue and once get response will return rest json call to your web app.
I would take another look at your architecture. In general, with microservices - especially user-facing ones that must be essentially synchronous, it's an anti-pattern to have ServiceA have to make a call to ServiceB (which may, in turn, call ServiceC and so on...) to return a response. That condition indicates those services are tightly coupled which makes them fragile. For example: if ServiceB goes down or is overloaded in your example, ServiceA also goes offline due to no fault of its own. So, probably one or more of the following should occur:
Deploy the related services behind a facade that encloses the entire domain - let the client interact synchronously with the facade and let the facade handle talking to multiple services behind the scenes.
Use MQTT or AMQP to publish data as it gets added/changed in ServiceB and have ServiceA subscribe to pick up what it needs so that it can fulfill the user request without explicitly calling another service
Consider merging ServiceA and ServiceB into a single service that can handle requests without having to make external calls
You can also send the HTTP request from the client to the service, set the application-state to waiting or similar, and have the consuming application subscribe to a eventSuccess or eventFail integration message from the bus. The main point of this idea is that you let daisy-chained services (which, again, I don't like) take their turns and whichever service "finishes" the job publishes an integration event to let anyone who's listening know. You can even do things like pass webhook URI's with the initial request to have services call the app back directly on completion (or use SignalR, or gRPC, or...)
The way we use RabbitMQ is to integrate services in real-time so that each service always has the info it needs to be responsive all by itself. To use your example, in our world ServiceB publishes events when data changes. ServiceA only cares about, and subscribes to a small subset of those events (and typically only a field or two of the event data), but it knows within seconds (usually less) when B has changed and it has all the information it needs to respond to requests. Each service literally has no idea what other services exist, it just knows events that it cares about (and that conform to a contract) arrive from time-to-time and it needs to pay attention to them.
You could also use events and make the whole flow async. In this scenario microservice1 creates an event representing the user request and then return a requested created response immediately to the user. You can then notify the user later when the request is finished processing.
I recommend the book Designing Event-Driven Systems written by Ben Stopford.
I asked a similar question to Chris Richardson (www.microservices.io). The result was:
Option 1
You use something like websockets, so the microservice1 can send the response, when it's done.
Option 2
microservice1 responds immediately (OK - request accepted). The client pulls from the server repeatedly until the state changed. Important is that microservice1 stores some state about the request (ie. initial state "accepted", so the client can show the spinner) which is modified, when you finally receive the response (ie. update state to "complete").
I am looking for a way for each consumer instance to receive a message that is published to RabbitMQ via MassTransit. The scenario would be, we have multiple microservices that need to invalidate a cache on notification. Pub-Sub won't work in this instance as there will be 5 consumers of the same type as its the same code per service instance, so only one would receive the message in a traditional PubSub.
Message observation could be an option but this means the messages would never be consumed and hang around forever on the bus.
Can anyone suggest a pattern to use in the context of MassTransit?
Thanks in advance.
You should create a management endpoint in each service, which could even be a temporary queue (just request a receive endpoint without a queue name and one will be dynamically generated). Then, put your queue invalidation consumers on that endpoint. Each service instance will receive a unique instance of the message (when Publish is called), and those queues and bindings will automatically be removed once the service exits.
This is exactly how the bus endpoint works, but in your case, you're creating a receive endpoint which can have consumer message type bindings, so that published messages are received, one copy per service.
cfg.ReceiveEndpoint(cfg => { ... });
Note that the queue name is not specified, and will be automatically generated uniquely.
I'm designing a quite complicated system and was wondering what the best way is to put a jms consumer (activemq, vm protocol, non persitent) inside a netty handler.
Let me explain, i have several clients connecting to my netty server using websockets. For every client connection i create a jms consumer that listens for interesting messages on one or more topics. If a interesting message arrives i need to do a extra step (additional filtering) before sending the message to the client using the websocket.
Is the following a good way to do this:
inside a SimpleChannelInboundHandler i declare a private non static consumer
the consumer is initialized in channelActive
the consumer is destroyed in channelInactive
when a message is received by consumer i do the extra filter a send it using ctx.channel().write()
In this setup i'm a bit worried that the consumer might turn into slow consumer and slow everything down, cause the websocket goes over the internet.
I came up with a more complex one to decouple the "receiving of message by consumer" and "sending of message through a websocket".
inside a SimpleChannelInboundHandler i declare a private non static consumer
the consumer is initialized in channelActive
the consumer is destroyed in channelInactive
when a message is received by consumer i put it in a blockedqueue
every minute i let a thread (created for every client) look in the queue and send the found messages to the client using ctx.channel().write().
At this point i'm a bit worried about the extra thread per client.
Or is there maybe a better way to accomplish this task?
This is a classic slow consumer problem and the first step to resolving it is to determine what the appropriate action is when a slow consumer is detected. If it is acceptable that the slow consumer misses messages then the solution is some variation on dropping messages or unsubscribing them from the feed. For example, if it's acceptable that the client misses messages then, when one is received from JMS, check if the channel is writable. If it isn't, drop the message. If you want to give yourself a bit more of a buffer (although OS buffers are quite large) you can track the number of write completion future's that haven't completed (ie the messages haven't been written to the OS send buffer) and drop messages if there are too many outstanding write requests.
If the client may not miss messages, and is consistently slow, then the problem is more difficult. One option might be to divert messages to a JMS queue with a specific header value, then open a new consumer that reads messages from that queue using a JMS selector. This will put more load on the JMS server but might be appropriate for temporary slowness and hopefully it won't interfere with you main topic feeds. Alternatively you might want to stash the messages in a different store, such as a database, so you can poll for messages when they can be sent. If you do this right a single polling thread can cope with many clients (query for clients which have outstanding messages, then for each client, load a bunch of messages). However this isn't as convenient as using JMS.
I wouldn't go with option 2 because the blocking queue is only going to solve the problem temporarily, and you can achieve the same thing by tracking how many write operations are waiting to complete.