Facebook Messenger Bot Proactive/Push Notifications using Azure

Question

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:

1. Is this a good approach?
2. Are there any other alternatives (Notifications Hub?)
3. 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.

Answer 1

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.

Answer 2

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.

Answer 3

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