Skip to main content

Service Bus Topic - Automatic forward messages from a subscription to a topic

Windows Azure Service Bus Topic is a service that enables us to distribute the same messages to different consumers without having to know each consumer. The only think that we need to do is to know the topic name. Each consumer will need to create and connect to a different subscription. Each message added to topic will be forward to each subscription.
There are times when we need to forward a message from a subscription to another topic or queue. Until now we had to use a worker role that took the message from the subscription and adding it to the second topic.
From now, a subscription supports this great functionality, by default. We only need to set the name of the topic or queue of the Service Bus where we want to forward the message.
SubscriptionDescription description = new SubscriptionDescription("topic1","subscription1");
description.ForwardTo = "topic2";
SqlFilter filter = new SqlFilter("FW = true");
namespaceManager.CreateSubscription(description, filter);
In this setup, all the messages that have the property FW set to true will be send automatically from subscription1 to topic2.
MessagingFactory messageFactory =
    MessagingFactory.CreateFromConnectionString(connectionString);
MessageSender messageSender = messageFactory.CreateMessageSender("topic1");
BrokeredMessage message = new BrokeredMessage();
messageToSend.Properties.Add("FW", true);
messageSender.Send(message);
Don’t forget that the message is not automatically forward to the next topic. Because of this, if you write a unit test you will need to wait 5-10 seconds before checking the second subscription.
SubscriptionClient messageReceiver =
     messageFactory.CreateSubscriptionClient("topic2", "subscription1");
BrokeredMessage message = messageReceiver.Receive(new TimeSpan(0, 0, 5));
We saw how easy is to forward a message from one subscription to another topic. We don’t need a consumer for a subscription or something similar. This is a great feature that permit us to define workflows using Service Bus Topic.

Comments

Popular posts from this blog

Windows Docker Containers can make WIN32 API calls, use COM and ASP.NET WebForms

After the last post , I received two interesting questions related to Docker and Windows. People were interested if we do Win32 API calls from a Docker container and if there is support for COM. WIN32 Support To test calls to WIN32 API, let’s try to populate SYSTEM_INFO class. [StructLayout(LayoutKind.Sequential)] public struct SYSTEM_INFO { public uint dwOemId; public uint dwPageSize; public uint lpMinimumApplicationAddress; public uint lpMaximumApplicationAddress; public uint dwActiveProcessorMask; public uint dwNumberOfProcessors; public uint dwProcessorType; public uint dwAllocationGranularity; public uint dwProcessorLevel; public uint dwProcessorRevision; } ... [DllImport("kernel32")] static extern void GetSystemInfo(ref SYSTEM_INFO pSI); ... SYSTEM_INFO pSI = new SYSTEM_INFO(

Azure AD and AWS Cognito side-by-side

In the last few weeks, I was involved in multiple opportunities on Microsoft Azure and Amazon, where we had to analyse AWS Cognito, Azure AD and other solutions that are available on the market. I decided to consolidate in one post all features and differences that I identified for both of them that we should need to take into account. Take into account that Azure AD is an identity and access management services well integrated with Microsoft stack. In comparison, AWS Cognito is just a user sign-up, sign-in and access control and nothing more. The focus is not on the main features, is more on small things that can make a difference when you want to decide where we want to store and manage our users.  This information might be useful in the future when we need to decide where we want to keep and manage our users.  Feature Azure AD (B2C, B2C) AWS Cognito Access token lifetime Default 1h – the value is configurable 1h – cannot be modified

What to do when you hit the throughput limits of Azure Storage (Blobs)

In this post we will talk about how we can detect when we hit a throughput limit of Azure Storage and what we can do in that moment. Context If we take a look on Scalability Targets of Azure Storage ( https://azure.microsoft.com/en-us/documentation/articles/storage-scalability-targets/ ) we will observe that the limits are prety high. But, based on our business logic we can end up at this limits. If you create a system that is hitted by a high number of device, you can hit easily the total number of requests rate that can be done on a Storage Account. This limits on Azure is 20.000 IOPS (entities or messages per second) where (and this is very important) the size of the request is 1KB. Normally, if you make a load tests where 20.000 clients will hit different blobs storages from the same Azure Storage Account, this limits can be reached. How we can detect this problem? From client, we can detect that this limits was reached based on the HTTP error code that is returned by HTTP