Deep Dive into Problem: AWS Bedrock ResourceLimitExceededException – Too Many Concurrent Requests

Question

"I'm trying to use AWS Bedrock to invoke a model, but I keep getting this error: ResourceLimitExceededException: Too many concurrent requests. My application sends multiple requests, but some of them fail. How can I resolve this?"

Clarifying the Issue

You're encountering a ResourceLimitExceededException: Too many concurrent requests when calling AWS Bedrock APIs. This means that the number of requests being sent simultaneously exceeds the allowed limit for your AWS account.

Common causes of this issue include:

• Exceeding AWS Limits – Each AWS account has predefined request quotas for Bedrock models.
• High Request Volume – Too many parallel requests from your application may trigger the limit.
• AWS Throttling – AWS may temporarily restrict access based on system load.
• Default Quotas – New AWS accounts often have lower default limits, requiring a quota increase.

Why It Matters

AWS Bedrock provides scalable access to foundation models, but staying within API limits is crucial to avoid service disruptions. If requests exceed the threshold, your application may experience intermittent failures, leading to poor reliability.

Key Terms

• AWS Bedrock – A managed service providing access to foundation models via APIs.
• ResourceLimitExceededException – An error indicating that too many requests are being processed concurrently.
• Rate Limits – AWS restricts the number of API calls allowed per second or minute.
• Quota Increase – AWS allows users to request higher limits for increased usage.

Steps at a Glance

1. Check current API limits to see if you’re hitting AWS-imposed restrictions.
2. Reduce concurrent requests by implementing delays or queuing mechanisms.
3. Use exponential backoff to retry requests gradually instead of spamming the API.
4. Request a quota increase if your application needs to process a high volume of requests.
5. Monitor API usage using CloudWatch to track request patterns and optimize accordingly.

Detailed Steps

Step 1: Check Current API Limits

Use the AWS CLI to check your Bedrock request quotas:

Bash

aws service-quotas list-service-quotas --service-code bedrock --region us-east-1

Expected Output:

JSON

{
  "Quotas": [
    {
      "QuotaName": "Bedrock concurrent requests",
      "QuotaCode": "L-BEDROCK-CONCURRENT-REQUESTS",
      "Value": 10
    }
  ]
}

If your limit is low (e.g., 10 concurrent requests), you may need to optimize or request a quota increase.

Step 2: Reduce Concurrent Requests

If your application sends multiple requests simultaneously, try limiting the number of parallel requests.

Example (Python):

Python

import time
import boto3

client = boto3.client('bedrock-runtime', region_name='us-east-1')

def invoke_model(payload):
    try:
        response = client.invoke_model(
            modelId="anthropic.claude-v2",
            body=payload
        )
        return response['body'].read().decode('utf-8')
    except Exception as e:
        print(f"Error: {e}")
        time.sleep(2)  # Introduce a delay before retrying
        return None

for _ in range(5):  # Limit the number of concurrent requests
    result = invoke_model('{"prompt": "Hello, world!"}')
    print(result)

Expected Output:

The API should return a valid JSON response with model output.

If errors persist, try:

• Increasing the delay (e.g., time.sleep(5))
• Reducing the number of concurrent requests in your loop

Step 3: Implement Exponential Backoff

If repeated requests continue failing, use an exponential backoff strategy to prevent overwhelming the API.

Python

import time
import random

def exponential_backoff(attempt):
    return min(2 ** attempt + random.uniform(0, 1), 60)  # Cap at 60 seconds

attempts = 0
while attempts < 5:  # Retry up to 5 times
    try:
        response = invoke_model('{"prompt": "Hello, world!"}')
        print(response)
        break
    except Exception:
        delay = exponential_backoff(attempts)
        print(f"Retrying in {delay:.2f} seconds...")
        time.sleep(delay)
        attempts += 1

Expected Output:

The API should eventually succeed as requests are spaced out.

If errors persist, AWS may be imposing account-wide rate limits beyond what exponential backoff can handle.

Step 4: Request a Quota Increase

If your application needs to process more requests, request a limit increase via AWS CLI:

Bash

aws service-quotas request-service-quota-increase \
    --service-code bedrock \
    --quota-code L-BEDROCK-CONCURRENT-REQUESTS \
    --desired-value 20

Expected Output:

JSON

{
  "RequestedQuotaIncrease": {
    "QuotaCode": "L-BEDROCK-CONCURRENT-REQUESTS",
    "DesiredValue": 20,
    "Status": "PENDING"
  }
}

If denied, submit a support ticket in AWS explaining your use case and why you need a higher limit.

Step 5: Monitor and Optimize API Usage

Use AWS CloudWatch to track request metrics and identify potential bottlenecks:

Bash

aws cloudwatch get-metric-statistics \
    --namespace "AWS/Bedrock" \
    --metric-name "ConcurrentRequests" \
    --start-time $(date -u -d '5 minutes ago' +%Y-%m-%dT%H:%M:%SZ) \
    --end-time $(date -u +%Y-%m-%dT%H:%M:%SZ) \
    --period 60 \
    --statistics Maximum \
    --region us-east-1

Expected Output:

JSON

{
  "Datapoints": [
    {
      "Timestamp": "2025-02-21T12:00:00Z",
      "Maximum": 9.0,
      "Unit": "Count"
    }
  ]
}

If your Maximum value is close to your quota limit, optimize request handling by reducing unnecessary calls or batching requests.

Closing Thoughts

Amazon Bedrock enforces strict rate limits to ensure fair resource allocation. By following these steps, you can:

✅ Check API Limits – Identify current restrictions.

✅ Reduce Concurrent Requests – Space out API calls to avoid failures.

✅ Use Exponential Backoff – Implement retries without spamming the system.

✅ Request a Quota Increase – Scale your usage if necessary.

✅ Monitor API Usage – Track request patterns and optimize for efficiency.

Need AWS Expertise?

If you're looking for guidance on Amazon Bedrock or any cloud challenges, feel free to reach out! We'd love to help you tackle your Bedrock projects. 🚀

Email us at: info@pacificw.com

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