Problem: Amazon Bedrock Error - "ResourceLimitExceededException: Too Many Concurrent Requests" When Calling InvokeModel

Problem: 

When using the InvokeModel API in Amazon Bedrock, you may encounter this error message:

Bash

$ aws bedrock-runtime invoke-model \
    --model-id anthropic.claude-v2 \
    --body '{"prompt": "Hello, world!"}' \
    --region us-east-1

# Error:
# An error occurred (ResourceLimitExceededException) when calling the 
# InvokeModel operation: Too many concurrent requests

Issue:

This error occurs when the number of concurrent requests to Amazon Bedrock exceeds the allowed limit for your AWS account. Common reasons include:

• Exceeding AWS Limits – Each AWS account has predefined rate limits for concurrent requests to Bedrock models.
• High Request Volume – If multiple users or applications are making simultaneous requests, the total count may exceed the limit.
• Throttling by AWS – AWS may impose temporary restrictions based on system load or to prevent overuse.
• Limited Quota for Your Account – Some AWS accounts, especially new ones, have lower default quotas for Bedrock API usage.

Fix: Manage and Optimize Concurrent Requests

Bash

# Step 1: Check Current Limits
aws service-quotas list-service-quotas --service-code bedrock --region us-east-1

# Expected Output:
# {
#   "Quotas": [
#     {
#       "QuotaName": "Bedrock concurrent requests",
#       "QuotaCode": "L-BEDROCK-CONCURRENT-REQUESTS",
#       "Value": 10
#     }
#   ]
# }
# If your value is too low, you may need to request an increase.

# Step 2: Reduce Concurrent Requests
# If making multiple requests in parallel, reduce frequency using a delay.
# Example (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)  # Add a delay before retrying
        return None

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

# Expected Output:
# The API should return a valid JSON response with model output.
# If you continue seeing the "Too many concurrent requests" error,
# try increasing the delay (e.g., time.sleep(5)) or reducing the loop count.

# Step 3: Implement Exponential Backoff
# If repeated requests still fail, implement a retry strategy with backoff.
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 retries are spaced out.
# If errors persist, it may indicate an AWS-side rate limit that cannot be bypassed.

# Step 4: Request a Quota Increase
aws service-quotas request-service-quota-increase \
    --service-code bedrock \
    --quota-code L-BEDROCK-CONCURRENT-REQUESTS \
    --desired-value 20

# Expected Output:
# {
#   "RequestedQuotaIncrease": {
#     "QuotaCode": "L-BEDROCK-CONCURRENT-REQUESTS",
#     "DesiredValue": 20,
#     "Status": "PENDING"
#   }
# }
# If denied, contact AWS Support to justify the need for a higher limit.

# Step 5: Monitor and Optimize Usage
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:
# {
#   "Datapoints": [
#     {
#       "Timestamp": "2025-02-21T12:00:00Z",
#       "Maximum": 9.0,
#       "Unit": "Count"
#     }
#   ]
# }
# If `Maximum` is consistently reaching your quota limit, optimize API calls.

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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