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Editorial Team
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Editorial Team
Asked: May 25, 20262026-05-25T02:48:26+00:00 2026-05-25T02:48:26+00:00

Scenario: if I’ve spin off multiple Worker roles or ONE Worker role with multiple

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Scenario:

if I’ve spin off multiple Worker roles or ONE Worker role with multiple threads, which polls the new messages in Azure Queue.

Could someone please confirm if the this the correct design approach? The reason I would like to have many worker roles is to speed up the PROCESSJOB. Our application should be near real time, i.e. as soon as there are messages we should get, apply complex business rules and commit to AZURE DB. We are expecting 11,000 message per 3min.

Thank you.

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  1. Editorial Team
    Editorial Team
    2026-05-25T02:48:26+00:00Added an answer on May 25, 2026 at 2:48 am

    You may have as many queue-readers as you like. It’s very common to scale out worker role instances, as they can all read from the same queue, giving you much greater work throughput.

    When you read a queue message, it’s marked “invisible” for a period of time, to prevent others from reading and doing the same work. The owner of the message must delete it before the time period expires, otherwise the message becomes visible again, and an exception will be thrown when the original reader attempts to delete it. This means your operations must be idempotent.

    There’s no direct poison-message handling, but it’s easy to implement, as each message has a dequeue count. Just check it and remove poison messages after being read 3-4 times. You can also dynamically adjust the timeout period based on dequeue count, as maybe the processing fails due to too-short a time window.

    Here’s the MSDN documentation for DequeueCount.

    EDIT: As far as processing 11,000 messages in 3 minutes: the scalability target for queues is 500 2,000 TPS, or up to 360,000 transactions in 3 minutes (far beyond the 11,000 message requirement you have). You can speed things up further by combining messages into a single queue message, as well as reading multiple messages at a time, which will also reduce your transaction count. You can also look at the ApproximateMessageCount property of a queue to see if your queue is backing up (and then scaling out to additional intstances to help consume queue items).

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