train model - S0 Standard

Question

Hi , when i train a custom classification model (22 document types) i got an error about rate limit using F0 pricing tier:

I want to know if the solution is scale to S0 pricing tier .

Regards,

Leonardo

Answer 1

Hello @Leonardo Torres Altez , Thanks for using Microsoft Q&A Platform.

The service limits for the different pricing are listed here: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/service-limits?view=doc-intel-3.1.0#custom-model-usage

As we know for the free tier as mentioned in the table (second column) the max number of pages is 10,000. Firstly, please try to check all these limitations for your pricing tier are followed accordingly.

Coming to your error, generally the Response Code 429 is due to too many requests. Some best practices are to implement retry logic in your application and avoid sudden spikes in workload. Instead, you can gradually increase the workload to give the service enough time to scale up and meet the demand: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/service-limits?view=doc-intel-3.1.0#general-best-practices-to-mitigate-throttling-during-autoscaling

For instance, your current workload is 10 TPS (transactions per second), you can increase the load to 40 TPS gradually instead of increasing it four times immediately. This will allow the service to scale up and prevent the occurrence of Response Code 429.

I would suggest going through this documentation and try the best practices to mitigate throttling and see if that helps: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/service-limits?view=doc-intel-3.1.0#general-best-practices-to-mitigate-throttling-during-autoscaling

Please note that by default the number of transactions per second is limited to 15 transactions per second for a Document Intelligence resource. For the Standard pricing tier, this amount can be increased. To resolve this issue, you can either upgrade to a higher pricing tier or follow these practices to continue using the service.

You can monitor the rate limit for your resource in the Azure portal by navigating to the metrics column by adding filters.

I hope this helps.

Regards,
Vasavi

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