Deleting items from Azure queue painfully slow

Question

My application relies heavily on a queue in in Windows Azure Storage (not Service Bus). Until two days ago, it worked like a charm, but all of a sudden my worker role is no longer able to process all the items in the queue. I've added several counters and from that data deduced that deleting items from the queue is the bottleneck. For example, deleting a single item from the queue can take up to 1 second!

On a SO post How to achive more 10 inserts per second with azure storage tables and on the MSDN blog http://blogs.msdn.com/b/jnak/archive/2010/01/22/windows-azure-instances-storage-limits.aspx I found some info on how to speed up the communication with the queue, but those posts only look at insertion of new items. So far, I haven't been able to find anything on why deletion of queue items should be slow. So the questions are:

(1) Does anyone have a general idea why deletion suddenly may be slow?

(2) On Azure's status pages (https://azure.microsoft.com/en-us/status/#history) there is no mentioning of any service disruption in West Europe (which is where my stuff is situated); can I rely on the service pages?

(3) In the same storage, I have a lot of data in blobs and tables. Could that amount of data interfere with the ability to delete items from the queue? Also, does anyone know what happens if you're pushing the data limit of 2TB?

Answer 1

1) Sorry, no. Not a general one.

2) Can you rely on the service pages? They certainly will give you information, but there is always a lag from the time an issue occurs and when it shows up on the status board. They are getting better at automating the updates and in the management portal you are starting to see where they will notify you if your particular deployments might be affected. With that said, it is not unheard of that small issues crop up from time to time that may never be shown on the board as they don't break SLA or are resolved extremely quickly. It's good you checked this though, it's usually a good first step.

3) In general, no the amount of data you have within a storage account should NOT affect your throughput; however, there is a limit to the amount of throughput you'll get on a storage account (regardless of the data amount stored). You can read about the Storage Scalability and Performance targets, but the throughput target is up to 20,000 entities or messages a second for all access of a storage account. If you have a LOT of applications or systems attempting to access data out of this same storage account you might see some throttling or failures if you are approaching that limit. Note that as you saw with the posts on improving throughput for inserts these are the performance targets and how your code is written and configurations you use have a drastic affect on this. The data limit for a storage account (everything in it) is 500 TB, not 2TB. I believe once you hit the actual storage limit all writes will simply fail until more space is available (I've never even got close to it, so I'm not 100% sure on that).

Throughput is also limited at the partition level, and for a queue that's a target of Up to 2000 messages per second, which you clearly aren't getting at all. Since you have only a single worker role I'll take a guess that you don't have that many producers of the messages either, at least not enough to get near the 2,000 msgs per second.

I'd turn on storage analytics to see if you are getting throttled as well as check out the AverageE2ELatency and AverageServerLatency values (as Thomas also suggested in his answer) being recorded in the $MetricsMinutePrimaryTransactionQueue table that the analytics turns on. This will help give you an idea of trends over time as well as possibly help determine if it is a latency issue between the worker roles and the storage system.

The reason I asked about the size of the VM for the worker role is that there is a (unpublished) amount of throughput per VM based on it's size. An XS VM gets much less of the total throughput on the NIC than larger sizes. You can sometimes get more than you expect across the NIC, but only if the other deployments on the physical machine aren't using their portion of that bandwidth at the time. This can often lead to varying performance issues for network bound work when testing. I'd still expect much better throughput than what you are seeing though.

Answer 2

There is a network in between you and the Azure storage, which might degrade the latency.

Sudden peaks (e.g. from 20ms to 2s) can happen often, so you need to deal with this in your code.

To pinpoint this problem further down the road (e.g. client issues, network errors etc.) You can turn on storage analytics to see where the problem exists. There you can also see if the end2end latency is too big or just the server latency is the limiting factor. The former usually tells about network issues, the latter about something beeing wrong on the Queue itself.

Usually those latency issues a transient (just temporary) and there is no need to announce that as a service disruption, because it isn't one. If it has constantly bad performance, you should open a support ticket.