Real time data storage with Azure Tables using ASP.NET

Question

I am using a Lab View application to simulate a test running, which would post a JSON string to my ASP.NET application. Within the ASP.NET application I format the data with the proper partition and row keys, then send it to Azure Table Storage.

The problem that I am having is that after what seems like a random amount of time (ie 5 minutes, 2 hours, 5 hours), the data fails to be saved into Azure. I am try to catch any exceptions within the ASP.NET application and send the error message back to the Lab View app and the Lab View app is also catching any exceptions in may encounter so I can trouble shoot where the issue is occurring.

The only error that I am able to catch is a Timeout Error 56 in the Lab View program. My question is, does anyone have an idea of where I should be looking for the root cause of this? I do not know where to begin.

EDIT:

I am using a table storage writer that I found here to do batch operations with retries.

Answer 1

You need to check whether an exception is transient or not. As Peter said on his comment, Azure Storage client already implements a retry policy. You can also wrap your code with another retry code (eg using polly) or you should change the default policy associated to Azure Storage Client.

Answer 2

The constructor for exponential retry policy is below:

public ExponentialRetry(TimeSpan deltaBackoff, int maxAttempts)

when you (or the library you use to be exact) instantiate this as RetryPolicy = new ExponentialRetry(TimeSpan.FromMilliseconds(2),100) you are basically setting the max attempts as 100 which means you may end up waiting up to around 2^100 milliseconds (there is some more math behind this but just simplifying) for each of your individual batch requests to fail on the client side until the sdk gives up retrying.

The other issue with that code is it executes batch requests sequentially and synchronously, that has multiple bad effects, first, all subsequent batch requests are blocked by the current batch request, second your cores are blocked waiting on I/O operations, third it has no exception handling so if one of the batch operations throw an exception, the method bails out and would not continue any further processing other batch requests.

My recommendation, do not use that library, batch operations are fairly straight forward. The default retry policy if you do not explicitly define is the exponential retry policy anyways with sensible default parameters (does 3 retries) so you do not even need to define your own retry object. For best scalability and throughput run your batch operations async (and concurrently).

As to why things fail, when you write your own api, catch the StorageException and check the http status code on the exception itself. You could be getting throttled by azure as one of the possibilities but it is hard to say without further debugging or you providing the http status code for the failed batch operations to us.