Skip to main content

Service Bus Topic - Messages processing problems

In the last post about Service Bus Topics we discover how we can write code in such a way that migration from Service Bus Queues from Service Bus Topics can be done only changing the configuration file. Today I want to talk a little about what we should be aware where we process messages from topics using Peek and Lock pattern.
As we have already seen, Service Bus Topics allows us to process messages in two ways:
Receive and Delete – when messages are automatically removed after there are received
Peek and Lock – when messages are removed from the topic only after subscription call the Complete() method
We will talk about the last one. When we are using the Peel and Lock pattern, each message after is received from Service Bus is automatically locked and cannot be consumed by other client from the same subscription. If the client is able to process the message with success, he can call the Complete() method. In that moment the message is automatically removed from Service Bus. Is something happen with the message processing, for example an error occurred, the client can call the Abandon() message. In that moment the message is available once again for the given subscription. In the same time, after a message is send to a client of the given subscription, each client have a specific time when he can call Complete() or Abandon method(). If this method is not called, the message will be available one again for the given subscription. The default value is 60 seconds, but can be configured to any value.
In the next example we will try to process a message from the subscription. If an error occurred, in the catch block we will call the Abandon() method:
BrokeredMessage message = topicClient.Receive();
try
{
// process message
message.Complete();
} catch(Exception ex)
{
// log error
message.Abandon();
}
We would saw that the solution is okay and we covered this specials case. We have only on half of the solution. In a case of an error we abandon the message, this is great but what happens next? The message will be unlocked and we will be able to process it again.
We should take care about two other things. The first one is what we are doing when we process a message. For example if we insert some information to database or call another service. In these cases we should have a transactional call. We should be able when calling the Abandon() message to rollback all things that we done.
To be able to make the rollback you can image very complicate scenarios ad there will be cases when an external service will not permit a rollback (for ex. if you call an external service). One simple solution involves the MessageId of each message. This id never changes, even if we call the abandon message for 100 times. Because of this we can store the MessageId in a list and check the id before processing it. In this way we will be able to know if we process the message already. We can image a situation when we have some steps for each message. We can store the step in this list. In this way we will not make some calls to different resources more than one. This type of processing is called “At least once processing”.
The other thing that we need to care about is about the messages that cannot be processed and will throw an error each time. For these cases, BrokeredMessage has a property that tells us how many times the client tried to processes the message. The name of the property is DeliveryCount. I gave a solution in another post for Service Bus Queues. The solution is the same for Service Bus Topics also. http://vunvulearadu.blogspot.hu/2012/08/service-bus-queues-from-windows-azure_1953.html
    BrokeredMessage message = topicClient.Receive();
if(message == null)
{
Thread.Sleep(1000);
continue;
}

try
{
// process our message.
message.Complete()
}
catch(Exception ex)
{
if( message.DeliveryCount > 3 )
{
message.DeadLetter();
}
message.Abandon();
}
In this post we saw what we should handle some specials case situations when working we are receiving and processing message from Service Bus Topics. We should not ignore these cases because we can create duplicate data in our storage system or to process the same messages over and over again.

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