Manage custom state data with Azure Table Storage for .NET in the v3 C# SDK

Article
12/13/2017

APPLIES TO: SDK v3

In this article, you’ll implement Azure Table storage to store and manage your bot’s state data. The default Connector State Service used by bots is not intended for the production environment. You should either use Azure Extensions available on GitHub or implement a custom state client using data storage platform of your choice. Here are some of the reasons to use custom state storage:

Higher state API throughput (more control over performance)
Lower-latency for geo-distribution
Control over where the data is stored
Access to the actual state data
Store more than 32kb of data

Prerequisites

You'll need:

Create Azure account

If you don't have an Azure account, click here to sign up for a free account.

Set up the Azure Table storage service

After you’ve logged into the Azure portal, create a new Azure Table storage service by clicking on New.
Search for Storage account that implements the Azure Table.
Fill in the fields, click the Create button at the bottom of the screen to deploy the new storage service. After the new storage service is deployed, it will display features and options available to you.
Select the Access keys tab on the left, and copy the connection string for later use. Your bot will use this connection string to call the storage service to save state data.

Install NuGet packages

Open an existing C# bot project, or create a new one using the C# Bot template in Visual Studio.
Install the following NuGet packages:
- Microsoft.Bot.Builder.Azure
- Autofac.WebApi2

Add connection string

Add the following entry in your Web.config file:

  <connectionStrings>
    <add name="StorageConnectionString"
    connectionString="YourConnectionString"/>
  </connectionStrings>

Replace "YourConnectionString" with the connection string to the Azure Table storage you saved earlier. Save the Web.config file.

Modify your bot code

In the Global.asax.cs file, add the following using statements:

using Autofac;
using System.Configuration;
using Microsoft.Bot.Connector;
using Microsoft.Bot.Builder.Azure;
using Microsoft.Bot.Builder.Dialogs;
using Microsoft.Bot.Builder.Dialogs.Internals;

In the Application_Start() method, create an instance of the TableBotDataStore class. The TableBotDataStore class implements the IBotDataStore<BotData> interface. The IBotDataStore interface allows you to override the default Connector State Service connection.

var store = new TableBotDataStore(ConfigurationManager.ConnectionStrings["StorageConnectionString"].ConnectionString);

Conversation.UpdateContainer(
           builder =>
           {
               builder.Register(c => store)
                         .Keyed<IBotDataStore<BotData>>(AzureModule.Key_DataStore)
                         .AsSelf()
                         .SingleInstance();

               builder.Register(c => new CachingBotDataStore(store,
                          CachingBotDataStoreConsistencyPolicy
                          .ETagBasedConsistency))
                          .As<IBotDataStore<BotData>>()
                          .AsSelf()
                          .InstancePerLifetimeScope();

               
           });

Save the Global.asax.cs file.

Run your bot app

Run your bot in Visual Studio, the code you added will create the custom botdata table in Azure.

Connect your bot to the emulator

At this point, your bot is running locally. Next, start the emulator and then connect to your bot in the emulator:

Type http://localhost:port-number/api/messages into the address bar, where port-number matches the port number shown in the browser where your application is running. You can leave Microsoft App ID and Microsoft App Password fields blank for now. You'll get this information later when you register your bot.
Click Connect.
Test your bot by typing a few messages in the emulator.

View data in Azure Table storage

To view the state data, open Storage Explorer and connect to Azure using your Azure Portal credential or connect directly to the table using the storage name and storage key then navigate to your table name.

Next steps

In this article, you implemented Azure Table storage for saving and managing your bot's data. Next, learn how to model conversation flow by using dialogs.

Manage conversation flow

Additional resources

If you are unfamiliar with Inversion of Control containers and Dependency Injection pattern used in the code above, go to Autofac site for information.

You can also download a complete Azure Table storage sample from GitHub.

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