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
Related
I want to delete all of a user's inserts in a collection when they stop watching a change stream from a React client. I'm using the Realm Web SDK for this.
Here's a summary of my code with what I want to do at the end of it:
import * as Realm from "realm-web";
const realmApp: Realm.App = new Realm.App({ id: realmAppId });
const credentials = Realm.Credentials.anonymous();
const user: Realm.User = await realmApp.logIn(credentials);
const mongodb = realmApp?.currentUser?.mongoClient("mongodb-atlas");
const users = mongodb?.db("users").collection("users");
const changeStream = users.watch();
for await (const change of changeStream) {
switch (change.operationType) {
case "insert": {
...
break;
}
case ...
}
}
// This pseudo-code shows what I want to do
changeStream.on("close", () => // delete all user's inserts)
changeStream.on("timeout", () => // delete all user's inserts)
changeStream.on("user closes app thus also closing stream", () => ... )
Realm Web SDK patterns seem rather different from the NodeJS ones and do not seem to include a method for closing a stream or for running a callback when it closes. In any case, they don't fit my use case.
These MongoDB Realm Web docs lead to more docs about Realm. Unless I'm missing it, both sets don't talk about how to monitor for closing and timing out of a change stream watcher instantiated from the Realm Web SDK, and how to do something when it happens.
I thought another way to do this would be in Realm's Triggers. But it doesn't seem likely from their docs.
Can this even be done from a front end client? Is there a way to do this on MongoDB itself in a "serverless" way?
If you want to delete the inserts specifically when a (client-)listener of a change-stream stops listening you have to implement some logic on client side. There is currently no way to get notified of such even within Mongodb Realm.
Sice a watcher could be closed because the app / browser is closed I would recommend against running the deletion logic on your client. Instead notify a server (or call a Mongodb Realm function / http endpoint) to make the deletions.
You can use the Beacon API to reliably send a request to trigger the delete, even when the window unloads.
Client side
const inserts = [];
for await (const change of changeStream) {
switch (change.operationType) {
case 'insert': inserts.push(change);
}
}
// This point is only reached if the generator returns / stream closes
navigator.sendBeacon('url/to/endpoint', JSON.stringify(inserts));
// Might also add a handler to catch users closing the app.
window.addEventListener('unload', sendBeacon);
Note that the unload event is not reliable MDN. But there are some alternatives which maybe be good enough for your use case.
Inside a realm function you could delete the documents.
That being said, maybe there is a better way to do what you want to achieve. Is it really the timeout of the change stream listener that has to trigger the delete or some other userevent?
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 have a ServiceWorker registered on my page and want to pass some data to it so it can be stored in an IndexedDB and used later for network requests (it's an access token).
Is the correct thing just to use network requests and catch them on the SW side using fetch, or is there something more clever?
Note for future readers wondering similar things to me:
Setting properties on the SW registration object, e.g. setting self.registration.foo to a function within the service worker and doing the following in the page:
navigator.serviceWorker.getRegistration().then(function(reg) { reg.foo; })
Results in TypeError: reg.foo is not a function. I presume this is something to do with the lifecycle of a ServiceWorker meaning you can't modify it and expect those modification to be accessible in the future, so any interface with a SW likely has to be postMessage style, so perhaps just using fetch is the best way to go...?
So it turns out that you can't actually call a method within a SW from your app (due to lifecycle issues), so you have to use a postMessage API to pass serialized JSON messages around (so no passing callbacks etc).
You can send a message to the controlling SW with the following app code:
navigator.serviceWorker.controller.postMessage({'hello': 'world'})
Combined with the following in the SW code:
self.addEventListener('message', function (evt) {
console.log('postMessage received', evt.data);
})
Which results in the following in my SW's console:
postMessage received Object {hello: "world"}
So by passing in a message (JS object) which indicates the function and arguments I want to call my event listener can receive it and call the right function in the SW. To return a result to the app code you will need to also pass a port of a MessageChannel in to the SW and then respond via postMessage, for example in the app you'd create and send over a MessageChannel with the data:
var messageChannel = new MessageChannel();
messageChannel.port1.onmessage = function(event) {
console.log(event.data);
};
// This sends the message data as well as transferring messageChannel.port2 to the service worker.
// The service worker can then use the transferred port to reply via postMessage(), which
// will in turn trigger the onmessage handler on messageChannel.port1.
// See https://html.spec.whatwg.org/multipage/workers.html#dom-worker-postmessage
navigator.serviceWorker.controller.postMessage(message, [messageChannel.port2]);
and then you can respond via it in your Service Worker within the message handler:
evt.ports[0].postMessage({'hello': 'world'});
To pass data to your service worker, the above mentioned is a good way. But in case, if someone is still having a hard time implementing that, there is an other hack around for that,
1 - append your data to get parameter while you load service-worker (for eg., from sw.js -> sw.js?a=x&b=y&c=z)
2- Now in service worker, fetch those data using self.self.location.search.
Note, this will be beneficial only if the data you pass do not change for a particular client very often, other wise it will keep changing the loading url of service worker for that particular client and every time the client reloads or revisits, new service worker is installed.
I have a jobque mechanism in ZF.
The jobque simlpy stores the the function call (Class, Method and params) and later executes it as CLI daemon. The daemon works, however at places the application looks for information from the request object, and when called from the CLI these places fail, or get no info.
I would like to store the original request object together with the job and when the job is processed set the request object back as if the job was done by the originall request, somethin along the line of the following pseudo code:
$ser_request = serialize(Zend_Controller_Front::getInstance ()->getRequest ());
-->save to db
-->retrive from db
$ZCF= new Zend_Controller_Front;
$ZCF::getInstance ()->setRequest (unserialize($ser_request))
The aim is to store and replay the jobs later withouth having to change the rest of the application.
Any suggestions how to do that?
I am not sure if this works, but here's an idea. Try to implement _sleep and _wakeup magic methods for the request object. Haven't tried it out, but maybe it's at least a starting solution.
The preamble
We're implementing a MVC2 site that needs to consume an external API via https (We cannot use WCF or even old-style SOAP WebServices, I'm afraid). We're using AsyncController wherever we need to communicate with the API, and everything is running fine so far.
Some scenarios have come up where we need to make multiple API calls in series, using results from one step to perform the next.
The general pattern (simplified for demonstration purposes) so far is as follows:
public class WhateverController : AsyncController
{
public void DoStuffAsync(DoStuffModel data)
{
AsyncManager.OutstandingOperations.Increment();
var apiUri = API.getCorrectServiceUri();
var req = new WebClient();
req.DownloadStringCompleted += (sender, e) =>
{
AsyncManager.Parameters["result"] = e.Result;
AsyncManager.OutstandingOperations.Decrement();
};
req.DownloadStringAsync(apiUri);
}
public ActionResult DoStuffCompleted(string result)
{
return View(result);
}
}
We have several Actions that need to perform API calls in parallel working just fine already; we just perform multiple requests, and ensure that we increment AsyncManager.OutstandingOperations correctly.
The scenario
To perform multiple API service requests in series, we presently are calling the next step within the event handler for the first request's DownloadStringCompleted. eg,
req.DownloadStringCompleted += (sender, e) =>
{
AsyncManager.Parameters["step1"] = e.Result;
OtherActionAsync(e.Result);
AsyncManager.OutstandingOperations.Decrement();
}
where OtherActionAsync is another action defined in this same controller following the same pattern as defined above.
The question
Can calling other async actions from within the event handler cause a possible race when accessing values within AsyncManager?
I tried looking around MSDN but all of the commentary about AsyncManager.Sync() was regarding the BeginMethod/EndMethod pattern with IAsyncCallback. In that scenario, the documentation warns about potential race conditions.
We don't need to actually call another action within the controller, if that is off-putting to you. The code to build another WebClient and call .DownloadStringAsync() on that could just as easily be placed within the event handler of the first request. I have just shown it like that here to make it slightly easier to read.
Hopefully that makes sense! If not, please leave a comment and I'll attempt to clarify anything you like.
Thanks!
It turns out the answer is "No".
(for future reference incase anyone comes across this question via a search)