AWS Bedrock Error: 'ThrottlingException' When Calling AWS Bedrock

#aws#bedrock#devops#cloud

A diagnostic guide to resolving Bedrock invocation failures caused by exceeding request or token rate limits.

Problem

An AWS Bedrock invocation fails with an error similar to:

ThrottlingException: Too many requests, please wait before trying again.

Typical symptoms:

• Requests succeed intermittently
• Error rates spike under load
• Latency increases before failures appear
• IAM permissions and model access are correct

Inference is rejected before execution.

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Clarifying the Issue

This error is not a permissions failure and not a model configuration issue.

It occurs when your application exceeds on-demand capacity limits enforced by AWS Bedrock for a specific model and region.

Bedrock enforces two independent limits:

1. Request Rate (RPM) – How many InvokeModel calls you can make per minute
2. Token Rate (TPM) – How many input and output tokens you can process per minute

Exceeding either limit results in ThrottlingException.

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Why It Matters

This is the most common blocker when:

• Moving from prototype to production
• Running parallel or batch inference jobs
• Executing RAG pipelines with large documents
• Supporting multi-tenant traffic without internal rate limiting

Treating throttling as a bug leads to wasted debugging.
It is a capacity signal, not a defect.

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Key Terms

• ThrottlingException – Error returned when rate limits are exceeded
• RPM (Requests Per Minute) – Allowed API call rate
• TPM (Tokens Per Minute) – Allowed token throughput
• Service quota – Per-model, per-region limit enforced by AWS

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Steps at a Glance

1. Determine whether the limit is RPM or TPM
2. Check current Bedrock service quotas
3. Ensure retries use exponential backoff
4. Reduce burst traffic where possible
5. Request a quota increase if needed

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Detailed Steps

1. Identify the Limit Type

Examine when throttling occurs:

• Immediate throttling under concurrency → Request rate (RPM)
• Throttling with large prompts or responses → Token rate (TPM)

This distinction determines the fix.

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2. Check Bedrock Service Quotas

In the AWS console:

1. Open Service Quotas
2. Select AWS services → Amazon Bedrock
3. Locate the quota for your specific model and region
4. Note the applied RPM and TPM values

Quotas vary by:

• Model
• Provider
• Region

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3. Implement Exponential Backoff

Immediate retries will sustain throttling.

Ensure your client uses exponential backoff:

• Attempt 1 → wait ~1 second
• Attempt 2 → wait ~2 seconds
• Attempt 3 → wait ~4 seconds
• Stop and log after max attempts

Most AWS SDKs support this when retry settings are enabled.

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4. Reduce Burst Traffic

Common fixes:

• Add client-side rate limiting
• Serialize batch jobs
• Reduce prompt size where possible
• Limit concurrent inference workers

Small reductions often eliminate throttling entirely.

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5. Request a Quota Increase

If throttling occurs under legitimate production load:

1. Open Service Quotas
2. Select the relevant Bedrock quota
3. Request an increase with expected RPM/TPM

Reasonable requests are often approved within 24–48 hours.

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Pro Tips

• RPM and TPM limits are independent — fixing one may not fix the other
• Throttling is per model and per region
• Load testing against default quotas will always hit throttles
• Treat quotas as part of capacity planning, not tuning

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Conclusion

ThrottlingException in AWS Bedrock is a throughput limit, not a misconfiguration.

Once:

• Traffic respects RPM and TPM limits
• Retries use exponential backoff
• Quotas match real workload demand

AWS Bedrock inference scales predictably inside Amazon Web Services.

Check the limits.
Slow the burst.
Retry intelligently.
Move on.

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Aaron Rose is a software engineer and technology writer at tech-reader.blog and the author of Think Like a Genius.