We are using Akka.Net and in some cases we need actors to communicate reliably while preserving order over a message queue (i.e. Oracle Advanced Queues or WebSphere MQ, but any message queuing system would work such as RabbitMQ).
We have various requirements why we are using the message queue, so the question isn't if we should be using this with Akka, the question is how.
How would we go about connecting the queue up to Akka so that it is as seamless as possible?
Is a a custom Mailbox the route to go down? Do we need to right a custom IMessageQueue implementation? Or maybe we need a custom router? Are there any specific tests we can run to be sure our Mailbox/IMessageQueue works well with Akka.Net?
EDIT:
Should we maybe looking to implement a custom Transport?
Can any pointers be offered on where to start?
In general implementing custom mailbox based on some reliable queue is not feasible solution - actually it has been already done on the Akka JVM side, and it failed all hopes.
One of the basic reasons is usually the misunderstanding of the basic idea - when people are talking about reliable delivery (that MQ-systems offers), what they really mean, is reliable processing. What if your messages has been send with 100% delivery ratio, but ultimately receiving actor/node has crashed while processing them? From the mailbox point of view everything went smooth...
For this reason, usually the way to go is a dedicated actor - or hierarchy of them - working as a gateway to external messaging system. This way you can not only send message them but also mark them as receive after explicit acknowledgement from successfully completed process. One of the examples may be akka-rabbitmq (written in Scala).
Related
We have multiple web and windows applications which were deployed to different servers that we are planning to integrate using NservierBus to let all apps can pub/sub message between them, I think we using pub/sub pattern and using MSMQ transport will be good for it. but one thing I am not clear if it is a way to avoid hard code to set sub endpoint to MSMQ QueueName#ServerName which has server name in it directly if pub is on another server. on 6-pre I saw idea to set endpoint name then using routing to delegate to transport-level address, is that a solution to do that? or only gateway is the solution? is a broker a good idea? what is the best practice for this scenario?
When using pub/sub, the subscriber currently needs to know the location of the queue of the publisher. The subscriber then sends a subscription-message to that queue, every single time it starts up. It cannot know if it subscribed already and if it subscribed for all the messages, since you might have added/configured some new ones.
The publisher reads these subscriptions messages and stores the subscription in storage. NServiceBus does this for you, so there's no need to write code for this. The only thing you need is configuration in the subscriber as to where the (queue of the) publisher is.
I wrote a tutorial myself which you can find here : http://dennis.bloggingabout.net/2015/10/28/nservicebus-publish-subscribe-tutorial/
That being said, you should take special care related to issues regarding websites that publish messages. More information on that can be found here : http://docs.particular.net/nservicebus/hosting/publishing-from-web-applications
In a scale out situation with MSMQ, you can also use the distributor : http://docs.particular.net/nservicebus/scalability-and-ha/distributor/
As a final note: It depends on the situation, but I would not worry too much about knowing locations of endpoints (or their queues). I would most likely not use pub/sub just for this 'technical issue'. But again, it completely depends on the situation. I can understand that rich-clients which spawn randomly might want this. But there are other solutions as well, with a more centralized storage and an API that is accessed by all the rich clients.
I'm trying to understand how to persist data in a Twisted application. Let's say I've decided to write a Twisted server that:
Accepts inbound SMTP requests
Sends the message to a 3rd party system for modification
Relays the modified message to its destination
A typical Twisted tutorial would have you build this app using Deferreds and callbacks, roughly:
A Factory handles inbound requests
Each time a full email is received a call is sent to the remote message processor, returning a deferred
Add an errback that substitutes the original message if anything goes wrong in the modify call.
Add a callback to send the message on to the recipient, which again returns a deferred.
A real server would add/include additional call/errbacks to retry or notify the sender or whatnot. Again for simplicity, assume we consider this an acceptable amount of effort and just log errors.
Of course, this persists NO data in the event of a crash/restart/something else. I get that a solution involves a 3rd party persistent datastore (RabbitMQ is often mentioned) and could probably come up with a dozen random ways to achieve the outcome.
However, I imagine there are a few approaches that work best in a Twisted app. What do they look like? How do they store (and restore in the event of a crash) the in-process messages?
If you found this question, you probably already know that Twisted is event-based. It sounds simple, but the "hardest" part of the answer is to get the persistence platform generating the events we need when we need them. Naturally, you can persist the data in a DB or a message queue, but some platforms don't naturally generate events. For example:
ZeroMQ has (or at least had) no callback for new data. It's also relatively poor at persistence.
In other cases, events are easy but reliability is a problem:
pgSQL can be configured to generate events using triggers, but they're one-time things so you can't resume incomplete events
The light at the end of the tunnel seems to be something like RabbitMQ.
RabbitMQ can persist the message in a database to survive a crash
We can use acknowledgements on both legs (incoming SMTP to RabbitMQ and RabbitMQ to outgoing SMTP) to ensure the application is reliable. Importantly, RabbitMQ supports acknowledgements.
Finally, several of the RabbitMQ clients provide full asynchronous support (see for example pika, txampq, and puka)
It's enough for our purposes that the RabbitMQ client provides us an event-based interface.
At a more theoretical level, however, this need not be the case. In fact, despite the "notification" issue above, ZeroMQ has an event-based client. Even if our software is elegantly event-based, we will run into systems that aren't. In these cases, we have no choice but to fall back on polling. In principle, if not in practice, we just query the message provider for messages. When we exhaust the current queue (and immediately if there are no messages), we use a callLater command to check again in the future. It may feel anti-pattern, but it's (to the best of my knowledge anyway) the right way to handle this particular case.
In our application the publisher creates a message and sends it to a topic.
It then needs to wait, when all of the topic's subscribers ack the message.
It does not appear, the message bus implementations can do this automatically. So we are leaning towards making each subscriber send their own new message for the client, when they are done.
Now, the client can receive all such messages and, when it got one from each destination, do whatever clean-ups it has to do. But what if the client (sender) crashes part way through the stream of acknowledgments? To handle such a misfortune, I need to (re)implement, what the buses already implement, on the client -- save the incoming acknowledgments until I get enough of them.
I don't believe, our needs are that esoteric -- how would you handle the situation, where the sender (publisher) must wait for confirmations from multiple recipients (subscribers)? Sort of like requesting (and awaiting) Return-Receipts from each subscriber to a mailing list...
We are using RabbitMQ, if it matters. Thanks!
The functionality that you are looking for sounds like a messaging solution that can perform transactions across publishers and subscribers of a message. In The Java world, JMS specifies such transactions. One example of a JMS implementation is HornetQ.
RabbitMQ does not provide such functionality and it does for good reasons. RabbitMQ is built for being extremely robust and to perform like hell at the same time. The transactional behavior that you describe is only achievable with the cost of reasonable performance loss (especially if you want to keep outstanding robustness).
With RabbitMQ, one way to assure that a message was consumed successfully, is indeed to publish an answer message on the consumer side that is then consumed by the original publisher. This can be achieved through RabbitMQ's RPC procedure calls which might help you to get a clean solution for your problem setting.
If the (original) publisher crashes before all answers could be received, you can assume that all outstanding answers are still queued on the broker. So you would have to build your publisher in a way that it is capable to resume with processing those left messages. This might turn out to be none-trivial.
Finally, I recommend the following solution: Design your producing component in a way that you can consume the answers with one or more dedicated answer consumers that are separated from the origin publisher.
Benefits of this solution are:
the origin publisher can finish its task independent of consumer success
the origin publisher is independent of consumer availability and speed
the origin publisher implementation is far less complex
in a crash scenario, the answer consumer can resume with processing answers
Now to a more general point: One of the major benefits of messaging is the decoupling of application components by the broker. In AMQP, this is achieved with exchanges and bindings that allow you to move message distribution logic from your application to a central point of configuration.
If you add RPC-style calls to your clients, then your components are most likely closely coupled again, meaning that the publishing component fails if one of the consuming components fails / is not available / too slow. This is exactly what you will want to avoid. Otherwise, why would you have split the components then?
My recommendation is that you design your application in a way that publishers can complete their tasks independent of the success of consumers wherever possible. Back-channels should be an exceptional case and be implemented in the described not-so coupled way.
I am a newbie to real-time application development and am trying to wrap my head around the myriad options out there. I have read as many blog posts, notes and essays out there that people have been kind enough to share. Yet, a simple problem seems unanswered in my tiny brain. I thought a number of other people might have the same issues, so I might as well sign up and post here on SO. Here goes:
I am building a tiny real-time app which is asynchronous chat + another fun feature. I boiled my choices down to the following two options:
LAMP + RabbitMQ
Node.JS + Redis + Pub-Sub
I believe that I get the basics to start learning and building this out. However, my (seriously n00b) questions are:
How do I communicate with the end-user -> Client to/from Server in both of those? Would that be simple Javascript long/infinite polling?
Of the two, which might more efficient to build out and manage from a single Slice (assuming 100 - 1,000 users)?
Should I just build everything out with jQuery in the 'old school' paradigm and then identify which stack might make more sense? Just so that I can get the product fleshed out as a prototype and then 'optimize' it. Or is writing in one over the other more than mere optimization? ( I feel so, but I am not 100% on this personally )
I hope this isn't a crazy question and won't get flamed right away. Would love some constructive feedback, love this community!
Thank you.
Architecturally, both of your choices are the same as storing data in an Oracle database server for another application to retrieve.
Both the RabbitMQ and the Redis solution require your apps to connect to an intermediary server that handles the data communications. Redis is most like Oracle, because it can be used simply as a persistent database with a network API. But RabbitMQ is a little different because the MQ Broker is not really responsible for persisting data. If you configure it right and use the right options when publishing a message, then RabbitMQ will actually persist the data for you but you can't get the data out except as part of the normal message queueing process. In other words, RabbitMQ is for communicating messages and only offers persistence as a way of recovering from network problems or system crashes.
I would suggest using RabbitMQ and whatever programming languages you are already familiar with. Since the M in LAMP is usually interpreted as MySQL, this means that you would either not use MySQL at all, or only use it for long term storage of data, not for the realtime communications.
The RabbitMQ site has a huge amount of documentation about building apps with AMQP. I suggest that after you install RabbitMQ, you read through the docs for rabbitmqctl and then create a vhost to experiment in. That way it is easy to clean up your experiments without resetting everything. I also suggest using only topic exchanges because you can emulate the behavior of direct and fanout exchanges by using wildcards in the routing_key.
Remember, you only publish messages to exchanges, and you only receive messages from queues. The exchange is responsible for pattern matching the message's routing_key to the queue's binding_key to determine which queues should receive a copy of the message. It is worthwhile learning the whole AMQP model even if you only plan to send messages to one queue with the same name as the routing_key.
If you are building your client in the browser, and you want to build a prototype, then you should consider just using XHR today, and then move to something like Kamaloka-js which is a pure Javascript implementation of AMQP (the AMQ Protocol) which is the standard protocol used to communicate to a RabbitMQ message broker. In other words, build it with what you know today, and then speed it up later which something (AMQP) that has a long term future in your toolbox.
Should I just build everything out with jQuery in the 'old school' paradigm and then identify which stack might make more sense? Just so that I can get the product fleshed out as a prototype and then 'optimize' it. Or is writing in one over the other more than mere optimization? ( I feel so, but I am not 100% on this personally )
This is usually called RAD (rapid application design/development) and it is what I would recommend right now. This lets you build the proof of concept that you can use to work off of later to get what you want to happen.
As for how to talk to the clients from the server, and vice versa, have you read at all on websockets?
Given the choice between LAMP or event based programming, for what you're suggesting, I would tell you to go with the event based programming, so nodejs. But that's just one man's opinion.
Well,
LAMP - Apache create new process for every request. RabbitMQ can be useful with many features.
Node.js - Uses single process to handle all request asynchronously with help of event looping. So, no extra overhead process creation like apache.
For asynchronous chat application,
socket.io + Node.js + redis pub-sup is best stack.
I have already implemented real-time notification using above stack.
To make an OO system as decoupled as possible, I'm thinking of the following approach:
1) we run an RMI/directory like service where objects can register and discover each other. They talk to this service through an interface
2) we run a messaging service to which objects can publish messages, and register subscription callbacks. Again, this happens through interfaces
3) when object A wants to invoke a method on object B, it discovers the target object's unique identity through #1 above, and publishes a message on the message service for object B
4) message services invokes B's callback to give it the message
5) B processes the request and sends the response for A on message service
6) A's callback is called and it gets the response.
I feel this system is as decoupled as practically possible, but it has the following problems:
1) communication is typically asynchronous
2) hence it's non real time
3) the system as a whole is less efficient.
Are there any other practical problems where this design obviously won't be applicable ? What are your thoughts on this design in general ?
Books
Enterprise Integration Patterns
It appears he's talking about using a Message Oriented Middleware
Here are some things to consider
Security
What will prevent another rogue service from registering as a key component in your system. You will need way to validate and verify that services are who they say they are. This can be done through a PKI system. There are scenarios that you might not need to do this, if your system is hosted entirely on your intranet. IF that is the case Social Engineering and Rogue Employees will be your biggest threat.
Contract
What kind of contract will your clients have with the services? Will messages all be serialized as XML and sent as a TextMessage? If you use a pure byte message you'll have to be careful about byte order if your services are to run on multiple platforms.
Synchronization
Most developers are not able to comprehend and utilize asynchronous messages correctly. Where possible it might be in the best interest of your design to create a way to invoke "synchronous" messages. I've done this in the past by creating a sendMessageAndWait() method with a timeout and a return object. Within the method you can create a temporary topic id to receive the response, register a listener for it, then use locks to wait for a message to be returned on your temporary topic.
Unsolicited Messages
What happens if you want to allow your service(s) to send unsolicited messages to your clients? A critical event happened in Service A and it must notify your clients or possibly a Watch Dog service. Allow for your design to register for a common communication channel for services to communicate with clients without clients initiating the conversation.
Failover
What happens if a critical service processing your credit cards goes down? You'll need to implement a Failover and Watch Dog service to ensure that your key infrastructure is always up and running. You could register a list of services within your registry then your register could give out the primary service, falling back to a secondary service if your primary stops communicating. Or if your Message Oriented Middleware can handle Round Robin messaging you might be able to register all the services on the same topic. Think about creating a way to know when a service has died. Since most messages are Asynchronous it will be difficult to determine when a service has gone offline. This can be done with a Heartbeat and Watch Dog.
I've created this type of system a few times in my past for large systems that needed to communicate. If you and other developers understand the pros and cons of such a system it can be very powerful and flexible.
The biggest piece of advice I can give is to build a toolkit for your other developers so they don't have to think about how to register a service, or implement failover, or respond to messages from a client. These are the sorts of things that will kill your system and have others say it is too complicated. Making it painless for them will allow your system to work the way you need it with flexibility and decoupling while not burdening your developers with understanding enterprise design patterns.
This is not a Ivory Tower Architect/Architecture. It would be if he said, "This is how it will do done, now go do it and don't bother me about it because I know I'm right." If you really wanted to reference a Anti-Pattern it could be Kitchen Sink, maybe. Nah now that I think about it, it isn't Kitchen Sink either.
If you can find one please post it as a comment.
Anti-Patterns
Coupling is simply a balance between efficiency and re-usability. If you wish the modules of your system to be as reusable as possible then that will undoubtedly come at a cost.
Personally I think it best to define some key assumptions which may tighten coupling, but bring increased efficiency.
There are design patterns which never see the light of day just because the benefit they provide is not worth the cost in complexity.
What's the simplest thing that could possibly work? Do modularize into reasonable size routines, but avoid interfaces, services, messages and all of this unless you are going to have multiple implementations or multiple hardware resources to divide a job.
Make it simple, then refactor those parts that turned out to matter.