408 Timeout Error in Azure OpenAI Playground Despite High Rate Limits

Question

Hello everyone,

I'm encountering a recurring 408: The operation was timeout error in the Azure OpenAI Playground, and I'm trying to understand the root cause.

My current rate limits are quite high:

• Tokens per minute: 900,000
• Requests per minute: 5,400

Previously, the same prompt was working fine, but starting yesterday, I'm consistently seeing this timeout error — even though nothing has changed in my configuration.

Interestingly, when I ask very simple questions like:

"Can you give me 5 rows of Accounts.csv?"

the response comes back quickly without any issues.

This leads me to wonder:

Is the timeout purely related to prompt length or complexity?

Could it be caused by too many concurrent requests, even though I'm well within my quota?

If it's related to backend issues or throttling, how can I monitor or resolve that?

In addition, why does our assigned quota become 0 as shown in the picture?

Any insights, tips, or similar experiences would be greatly appreciated. Thanks in advance!

Answer 1

Hi Minji Kim à,

I Understand that you're facing a 408: The operation was timeout error in the Azure OpenAI Playground despite having high-rate limits (900,000 TPM and 5,400 RPM). Let's break down the possible reasons and solutions.

Possible Causes & Solutions

1.Prompt Length & Complexity

Observation: Simple prompts like “Can you give me 5 rows of Accounts.csv?” return quickly, but complex prompts time out.

Explanation: Azure OpenAI models dynamically allocate compute resources. Complex prompts:

Require more computation, which increases latency.

Might exceed model’s internal time threshold, triggering a timeout.

Solution:

Try reducing prompt complexity or breaking it into smaller parts.

Use streaming mode in API calls (if applicable) to get partial responses faster.

Check token limits per request (max_tokens parameter) and try reducing it.

2.Too Many Concurrent Requests

Question: Could the issue be due to multiple parallel requests, even within quota?

Explanation: Even if you're within the quota, Azure may throttle if:

Too many requests hit the same model instance simultaneously.

There's regional congestion affecting response times.

Solution:

Reduce the number of concurrent requests temporarily.

Introduce rate-limiting mechanisms in your implementation.

Use exponential backoff retry logic if applicable.

3.Backend Issues & Throttling

Question: How can I check if this is due to backend throttling or region-specific issues?

Explanation: Azure dynamically manages capacity, and your region may be experiencing higher-than-usual demand.

Solution:

Monitor service health: Check Azure status at Azure OpenAI Service Health.

Please refer to below document:
https://learn.microsoft.com/en-us/azure/ai-foundry/model-inference/quotas-limits#quotas-and-limits-reference

Change deployment region: If your model is deployed in a busy region, try a different one.

4.Assigned Quota Showing 0

Observation: The screenshot shows an assigned quota of 0, while available quota is high.

Explanation:

Assigned quota = actual usage limits you can allocate.

Available quota = the maximum you could assign but is not yet allocated.

If assigned quota is 0, it means your deployment hasn’t used any quota yet or is not correctly assigned.

Solution:

Check your Azure subscription and quota allocation settings.

Assign the required quota to your OpenAI deployment in Azure Portal → Quotas & Limits.

Run az openai quota list in Azure CLI to verify quota assignment.

Hope this helps. Do let us know if you any further queries.

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