I am trying to implement a proof of concept service bus using MassTransit. I have three applications which need to communicate changes of a common entity type between each other. So when the user updates the entity in one application, the other two are notified.
Each application is configured as follows with their own queue:
bus = ServiceBusFactory.New(sbc =>
{
sbc.UseMsmq();
sbc.VerifyMsmqConfiguration();
sbc.ReceiveFrom("msmq://localhost/app1_queue");
sbc.UseSubscriptionService("msmq://localhost/subscription");
sbc.UseControlBus();
sbc.Subscribe(subs =>
{
subs.Handler<IMessage1>(IMessage1_Received);
});
});
There is also a subscription service application configured as follows:
subscriptionBus = ServiceBusFactory.New(sbc =>
{
sbc.UseMsmq();
sbc.VerifyMsmqConfiguration();
sbc.ReceiveFrom("msmq://localhost/subscription");
});
var subscriptionSagas = new InMemorySagaRepository<SubscriptionSaga>();
var subscriptionClientSagas = new InMemorySagaRepository<SubscriptionClientSaga>();
subscriptionService = new SubscriptionService(subscriptionBus, subscriptionSagas, subscriptionClientSagas);
subscriptionService.Start();
The problem is that when one of the applications publishes a message, all three applications receive it (including the original sender).
Is there any way to avoid this (without resorting to adding the application name to the message)?
Thanks,
G
So MassTransit is a pub/sub system. If you publish a message, everyone registered to receive it will. If you need only some endpoints to receive it, then you really need to directly send. It's just how this works.
You could include the source in your message and discard messages that aren't of interest to you. If you implement the Consumes.Accept interface, I think the Accept method would allow you to do so easily without mixing that into the normal consumption code.
Related
We are using the Azure SignalR service from functions to send messages back to our UI and all is working without issue. But I can't find a definitive answer on how long lived the ServiceManager or HubContext should be.
At the moment each time we want to send a message to the UI we call a class we have written which does the following:
using var serviceManager = return new ServiceManagerBuilder().WithOptions(option =>
{
option.ConnectionString = _connectionString;
option.ServiceTransportType = ServiceTransportType.Persistent;
})
.WithNewtonsoftJson()
.BuildServiceManager();
await using var hubContext = await serviceManager .CreateHubContextAsync(hubName, System.Threading.CancellationToken.None);
await hubContext.Clients.Group(group).SendAsync(method, message);
This all works fine, but we are creating a new ServiceManager and ServiceHubContext every time we send a message.
The samples I have looked at do not include running in functions where we inject a service which handles publishing. Should either of these be Singleton? The functions we have are processing data and sending updates in a loop so we may send 100s of messages in a single function.
I am building a bot for for Facebook Messenger using Microsoft Bot Framework. I am planning to use CosmosDB for State Management and also as my backend data store. (I am not stuck to CosmosBD and can use any other store if needed)
I need to send daily/weekly proactive messages(push notifications) to users based on their time preference. I will capturing their time preference when they first interact with the bot.
What is the best way to deliver these notifications?
As I will be storing these preferences in CosmosDB, I am thinking using ComosDB trigger of creating an Azure Function and schedule it based on the user time preference. This Azure function will make a call to my webhook which will deliver these messages. If requried, I will change Function schedule when a user changes his/her preference.
My questions are:
Is this a good approach?
Are there any other alternatives (Notifications Hub?)
I should be able to set specific times for notifications (like at the top of the hour or something like that), does it make sense to schedule an Azure Function to run at these hours rather than creating a function based on user preference (I can actually combine these two approaches too)
Thank you in advance.
First, I don't think there's any "right" answer to be given here; it's going to depend a lot on your domain's specific needs. Scale is going to play a major factor in the design of this. Will you have 100 users? 10000 users? 1mil users? I'm going to assume you want to design for maximum scale up front, but it could be overkill.
First, based on what you've described, I don't think a CosmosDB trigger is necessarily the solution to your problem because that's only going to fire when the preference data is created/updated. I assume that, from that point forward, your function needs to continuously fire at the time slot they've opted into, correct?
So let's pretend you let people choose from the 24hrs in the day. A naïve approach would be to simply use a scheduled trigger that fires up every hour, queries the CosmosDB for all the documents where the preference is set to that particular hour and then begins sending out notifications from there. The problem is how you scale from there and deal with issues of idempotency in the face of failures.
First off, a timer trigger only ever spins up one instance. If you were to just go query the CosmosDB documents and start processing them one by one in the scope of that single trigger, you'd hit a ceiling relatively quickly on how many notifications you can scale to. Instead what you'd want to do is use that timer trigger to fan out the notifications to as many "worker" function instances as possible. The timer trigger can act as the orchestrator in the sense that it can own the query against the CosmosDB and then turn each document result it finds for that particular notification time window into a message that it places on a queue to be processed by a separate function which will scale out on its own.
There are actually a couple ways you can accomplish this with Azure Functions, it really depends on how early an adopter of technology you are comfortable with being.
The first is what I would call the "manual" way which would be done by simply using the existing Azure Storage Queue extension by taking an IAsyncCollector<YourNotificationWorkerMessage> as a parameter to the timer function that's bound to the worker queue and then pumping out the messages through that. Then you write a second companion function which uses a QueueTrigger, bind it to that same queue, and it will take care of processing each message. This second function is where you get the scaling, enabling process all of the queued messages as quickly as possible based on whatever scaling parameters you choose to configure. This is the "simplest" approach
The second approach would be to adopt the newer Durable Functions extension. With that model, you don't have to directly think about creating a worker queue. You simply kick off a new instance of your orchestrator function from the timer function and the orchestrator fans out the work by invoking N "concurrent" calls to an action for each notification. Now, it happens to distribute those calls using queues under the covers, but that's an implementation detail that you need no longer maintain yourself. Additionally, if the work of delivering the notification requires more involved work and/or retry logic, you might actually consider using a sub-orchestration instead of a simple action. Finally, another added benefit of this approach, is that you can "fan back in" to your main orchestrator function once all the notifications are delivered to do some follow up work... even if that's simply some kind of event logging that the notification cycle has completed for this hour.
Now, the challenge with either of these approach is actually dealing with failure in initially fetching the candidates for notification from CosmosDB, paging through the results and making sure you actually fan all of them out in an idempotent manner. You need to deal with possible hiccups as you page and you need to deal with the fact that your whole function could be torn down and you might have to restart. Perhaps on the initial run of the 8AM notifications you got through page 273 out of 371 pages and then you got hit with a complete network connectivity fail or the VM your function was running on suffered a power failure. You could resume, but you'd need to know that you left off on page 273 and that you actually processed the 27th record out of that page and start from there. Otherwise, you risk sending double notifications to your users. Maybe that's something you can accept, maybe it's not. Maybe you're ok with the 27 notifications on that page being duplicated as long as the first 272 pages aren't. Again, this is something you need to decide for your domain, but if you want to avoid this issue your orchestrator function will need to track its progress to ensure that it doesn't send out dupes. Again I would say Durable Functions has a leg up here as it comes with the ability to configure retries. Maintaining the state of a particular run is left up to the author in either approach though.
I use pro-active dialog extensively with botframwork and messenger without any issue. During your facebook approval process you simply need to inform them you will be sending notifications trough messenger with your bot. Usually if you use it to inform your user and stay away from promotional content you should be fine.
I also use azure function to trigger the pro-active dialog from a custom controller endpoint.
Bellow sample code for azure function:
public static void Run(TimerInfo notificationTrigger, TraceWriter log)
{
try
{
//Serialize request object
string timerInfo = JsonConvert.SerializeObject(notificationTrigger);
//Create a request for bot service with security token
HttpRequestMessage hrm = new HttpRequestMessage()
{
Method = HttpMethod.Post,
RequestUri = new Uri(NotificationEndPointUrl),
Content = new StringContent(timerInfo, Encoding.UTF8, "application/json")
};
hrm.Headers.Add("Authorization", NotificationApiKey);
log.Info(JsonConvert.SerializeObject(hrm));
//Call service
using (var client = new HttpClient())
{
Task task = client.SendAsync(hrm).ContinueWith((taskResponse) =>
{
HttpResponseMessage result = taskResponse.Result;
var jsonString = result.Content.ReadAsStringAsync();
jsonString.Wait();
if (result.StatusCode != System.Net.HttpStatusCode.OK)
{
//Throw what ever problem as an exception with details
throw new Exception($"AzureFunction - ERRROR - HTTP {result.StatusCode}");
}
});
task.Wait();
}
}
catch (Exception ex)
{
//TODO log
}
}
Bellow sample code for starting the pro-active dialog:
public static async Task Resume<T, R>(string resumptionCookie) where T : IDialog<R>, new()
{
//Deserialize reference to conversation
ConversationReference conversationReference = JsonConvert.DeserializeObject<ConversationReference>(resumptionCookie);
//Generate message from bot to user
var message = conversationReference.GetPostToBotMessage();
var builder = new ContainerBuilder();
using (var scope = DialogModule.BeginLifetimeScope(Conversation.Container, message))
{
//From a cold start the service is not yet authenticated with dev bot azure services
//We thus must trust endpoint url.
if (!MicrosoftAppCredentials.IsTrustedServiceUrl(message.ServiceUrl))
{
MicrosoftAppCredentials.TrustServiceUrl(message.ServiceUrl, DateTime.MaxValue);
}
var botData = scope.Resolve<IBotData>();
await botData.LoadAsync(CancellationToken.None);
//This is our dialog stack
var task = scope.Resolve<IDialogTask>();
T dialog = scope.Resolve<T>(); //Resolve the dialog using autofac
try
{
task.Call(dialog.Void<R, IMessageActivity>(), null);
await task.PollAsync(CancellationToken.None);
}
catch (Exception ex)
{
//TODO log
}
finally
{
//flush dialog stack
await botData.FlushAsync(CancellationToken.None);
}
}
}
Your dialog needs to be registered in autofac.
Your resumptionCookie needs to be saved in your db.
You might want to check FB policy regarding proactive messages
There’s a 24h limit but it might not be totally screwed in your case
https://developers.facebook.com/docs/messenger-platform/policy/policy-overview#standard_messaging
I'm pretty new to Scala, the Play Framework and Akka. In the project I currently work on, the user of the web application should be able to ask the server several things to do (like starting a particular computation) in an asynchronous way. If the server is done it should notify the user also async. I solve this demand by a WebSocket connection which is established when the user first connects with the Application and the WebSocket is handled by a UserActor, which is attached to the User Session:
def ws = WebSocket.tryAcceptWithActor[JsValue, JsValue] { implicit request =>
Future.successful(request.session.get(UID) match {
case None => Left(Forbidden)
case Some(uid) => Logger.info("WebSocket has accepted the request with uid " + uid)
Right(UserActor.props(uid))
})
}
Currently, the only thing the UserActor does is receiving messages from the WebSocket as JsValue. The UID of the session is generated when requesting index:
def index = Action { implicit request => {
val uid = request.session.get(UID).getOrElse {
counter += 1
counter.toString
}
Ok(views.html.index(uid)).withSession {
Logger.debug("create uid " + uid)
request.session + (UID -> uid)
}}
}
The UserActor should represent the actual user on the Server and thus include the logic of all actions that the user can perform on the Server. This works fine as long as I send all user interaction over the WebSocket.
Now what is the case with other user input, like form submission? The application includes a form whose data should not go over the WebSocket, but rather be submitted with a POST request (perhaps with AJAX) and bound in a controller to the Model like described in the documentation.
def saveContact = Action { implicit request =>
contactForm.bindFromRequest.fold(
formWithErrors => {
BadRequest(views.html.contact.form(formWithErrors))
},
contact => {
val contactId = Contact.save(contact)
Redirect(routes.Application.showContact(contactId)).flashing("success" -> "Contact saved!")
}
)
}
This example is taken from the Playframework documentation.
Now, how do I link the Form Submission handler with the UserActor? Say I want to tell the user actor that a form has been submitted. A trivial example would be that the UserActor sends one value of the form back over the WebSocket to the client as soon it is received. So basically the problem reduces to the issue that I want to send the UserActor Messages from any Controller.
I might come up with the idea to send all form data over the WebSocket, but I also want to realize the upload of large data in the future, which I want to tackle like described in this blog post. Then one scenario I could imagine is that the UserActor should be messaged for each chunk it receives.
I guess one problem is that the UserActor and the WebSocketActor are the same and I rather should split their logic, such that the UserActor is only associated with the Session, but I have no idea how to accomplish this. Maybe I need another actor, say a UserManager, which keeps track of present UserActors and enables access to UserActors?
Do you have any suggestions, recommendations or perhaps an example application which also deals with this case? Thank you very much in advance.
Best regards
Don't use the actor that you pass to tryAcceptWithActor as a representation of the User. It should represent a particular session with that user. Possibly, one of many concurrent sessions (multiple browsers, or tabs) a user could have open at a particular time.
Create a separate actor to represent the user and all of the actions it can perform. Now the session actors should forward their messages to the user actor. Traditional controller methods can also forward requests to the corresponding user actors.
The question assumes the use of Event Sourcing.
When rebuilding current state by replaying events, event handlers should be idempotent. For example, when a user successfully updates their username, a UsernameUpdated event might be emitted, the event containing a newUsername string property. When rebuilding current state, the appropriate event handler receives the UsernameUpdated event and sets the username property on the User object to the newUsername property of the UsernameUpdated event object. In other words, the handling of the same message multiple times always yields the same result.
However, how does such an event handler work when integrating with external services? For example, if the user wants to reset their password, the User object might emit a PasswordResetRequested event, which is handled by a portion of code that issues a 3rd party with a command to send an SMS. Now when the application is rebuilt, we do NOT want to re-send this SMS. How is this situation best avoided?
There are two messages involved in the interaction: commands and events.
I do not regard the system messages in a messaging infrastructure the same as domain events. Command message handling should be idempotent. Event handlers typically would not need to be.
In your scenario I could tell the aggregate root 100 times to update the user name:
public UserNameChanged ChangeUserName(string username, IServiceBus serviceBus)
{
if (_username.Equals(username))
{
return null;
}
serviceBus.Send(new SendEMailCommand(*data*));
return On(new UserNameChanged{ Username = userName});
}
public UserNameChanged On(UserNameChanged #event)
{
_username = #event.UserName;
return #event;
}
The above code would result in a single event so reconstituting it would not produce any duplicate processing. Even if we had 100 UserNameChanged events the result would still be the same as the On method does not perform any processing. I guess the point to remember is that the command side does all the real work and the event side is used only to change the state of the object.
The above isn't necessarily how I would implement the messaging but it does demonstrate the concept.
I think you are mixing two separate concepts here. The first is reconstructing an object where the handlers are all internal methods of the entity itself. Sample code from Axon framework
public class MyAggregateRoot extends AbstractAnnotatedAggregateRoot {
#AggregateIdentifier
private String aggregateIdentifier;
private String someProperty;
public MyAggregateRoot(String id) {
apply(new MyAggregateCreatedEvent(id));
}
// constructor needed for reconstruction
protected MyAggregateRoot() {
}
#EventSourcingHandler
private void handleMyAggregateCreatedEvent(MyAggregateCreatedEvent event) {
// make sure identifier is always initialized properly
this.aggregateIdentifier = event.getMyAggregateIdentifier();
// do something with someProperty
}
}
Surely you wouldn't put code that talks to an external API inside an aggregate's method.
The second is replaying events on a bounded context which could cause the problem you are talking about and depending on your case you may need to divide your event handlers into clusters.
See Axon frameworks documentation for this point to get a better understanding of the problem and the solution they went with.
Replaying Events on a Cluster
TLDR; store the SMS identifier within the event itself.
A core principle of event sourcing is "idempotency". Events are idempotent, meaning that processing them multiple times will have the same result as if they were processed once. Commands are "non-idempotent", meaning that the re-execution of a command may have a different result for each execution.
The fact that aggregates are identified by UUID (with a very low percentage of duplication) means that the client can generate the UUIDs of newly created aggregates. Process managers (a.k.a., "Sagas") coordinate actions across multiple aggregates by listening to events in order to issue commands, so in this sense, the process manager is also a "client". Cecause the process manager issues commands, it cannot be considered "idempotent".
One solution I came up with is to include the UUID of the soon-to-be-created SMS in the PasswordResetRequested event. This allows the process manager to only create the SMS if it does not yet already exist, hence achieving idempotency.
Sample code below (C++ pseudo-code):
// The event indicating a password reset was successfully requested.
class PasswordResetRequested : public Event {
public:
PasswordResetRequested(const Uuid& userUuid, const Uuid& smsUuid, const std::string& passwordResetCode);
const Uuid userUuid;
const Uuid smsUuid;
const std::string passwordResetCode;
};
// The user aggregate root.
class User {
public:
PasswordResetRequested requestPasswordReset() {
// Realistically, the password reset functionality would have it's own class
// with functionality like checking request timestamps, generationg of the random
// code, etc.
Uuid smsUuid = Uuid::random();
passwordResetCode_ = generateRandomString();
return PasswordResetRequested(userUuid_, smsUuid, passwordResetCode_);
}
private:
Uuid userUuid_;
string passwordResetCode_;
};
// The process manager (aka, "saga") for handling password resets.
class PasswordResetProcessManager {
public:
void on(const PasswordResetRequested& event) {
if (!smsRepository_.hasSms(event.smsUuid)) {
smsRepository_.queueSms(event.smsUuid, "Your password reset code is: " + event.passwordResetCode);
}
}
};
There are a few things to note about the above solution:
Firstly, while there is a (very) low possibility that the SMS UUIDs can conflict, it can actually happen, which could cause several issues.
Communication with the external service is prevented. For example, if user "bob" requests a password reset that generates an SMS UUID of "1234", then (perhaps 2 years later) user "frank" requests a password reset that generates the same SMS UUID of "1234", the process manager will not queue the SMS because it thinks it already exists, so frank will never see it.
Incorrect reporting in the read model. Because there is a duplicate UUID, the read side may display the SMS sent to "bob" when "frank" is viewing the list of SMSes the system sent him. If the duplicate UUIDs were generated in quick succession, it is possible that "frank" would be able to reset "bob"s password.
Secondly, moving the SMS UUID generation into the event means you must make the User aggregate aware of the PasswordResetProcessManager's functionality (but not the PasswordResetManager itself), which increases coupling. However, the coupling here is loose, in that the User is unaware of how to queue an SMS, only that an SMS should be queued. If the User class were to send the SMS itself, you could run into the situation in which the SmsQueued event is stored while the PasswordResetRequested event is not, meaning that the user will receive an SMS but the generated password reset code was not saved on the user, and so entering the code will not reset the password.
Thirdly, if a PasswordResetRequested event is generated but the system crashes before the PasswordResetProcessManager can create the SMS, then the SMS will eventually be sent, but only when the PasswordResetRequested event is re-played (which might be a long time in the future). E.g., the "eventual" part of eventual consistency could be a long time away.
The above approach works (and I can see that it should also work in more complicated scenarious, like the OrderProcessManager described here: https://msdn.microsoft.com/en-us/library/jj591569.aspx). However, I am very keen to hear what other people think about this approach.
I am implementing a Service Bus and having a look at MassTransit. My pattern is not Publish/Subscribe but Sender/Receiver where the Receiver can be offline and came back online later.
Right now I am starting to write my tests to verify that MassTransit succesfully deliver the message using the following code:
bus = ServiceBusFactory.New(sbc =>
{
sbc.UseMsmq(
cfg =>
{
cfg.Configurator.UseJsonSerializer();
cfg.Configurator.ReceiveFrom("msmq://localhost/my_queue");
cfg.VerifyMsmqConfiguration();
});
});
Then I grab the bus and publish a message like this:
bus.Publish<TMessage>(message);
As I can notice from MSMQ, two queues are created and the message is sent cause Mass Transit does not raise any error but I cannot find any message in the queue container.
What am I doing wrong?
Update
Reading the Mass Transit newsgroup I found out that in a scenario of Sender/Receiver where the receiver can come online at any time later, the message can be Send using this code:
bus.GetEndpoint(new Uri("msmq://localhost/my_queue")).Send<TMessage>(message);
Again in my scenario I am not writing a Publisher/Subscriber but a Sender/Receiver.
First, to send, you can use a simple EndpointCacheFactory instead of a ServiceBusFactory...
var cache = EndpointCacheFactory.New(x => x.UseMsmq());
From the cache, you can retrieve an endpoint by address:
var endpoint = cache.GetEndpoint("msmq://localhost/queue_name");
Then, you can use the endpoint to send a message:
endpoint.Send(new MyMessage());
To receive, you would create a bus instance as you specified above:
var bus = ServiceBusFactory.New(x =>
{
x.UseMsmq();
x.ReceiveFrom("msmq://localhost/queue_name");
x.Subscribe(s => s.Handler<MyMessage>(x => {});
});
Once your receiver process is complete, call Dispose on the IServiceBus instance. Once your publisher is shutting down, call Dispose on the IEndpointCache instance.
Do not dispose of the individual endpoints (IEndpoint) instances, the cache keeps them available for later use until it is disposed.