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AWS Bedrock Provisioned Throughput explained

Quick answer

AWS Bedrock Provisioned Throughput lets you reserve a fixed capacity of LLM request units to ensure consistent performance and low latency for enterprise applications. It guarantees throughput by pre-allocating resources, avoiding throttling during peak demand. You configure it via AWS Bedrock API or console by specifying the desired throughput units.

PREREQUISITES

Python 3.8+
AWS CLI configured with AWS credentials
boto3 library installed (pip install boto3)
Access to AWS Bedrock service with Provisioned Throughput enabled

Setup

To use AWS Bedrock Provisioned Throughput, ensure you have AWS CLI configured with credentials that have permissions for Bedrock. Install boto3 for Python SDK access.

Install boto3:

bash

pip install boto3

output

Requirement already satisfied: boto3 in /usr/local/lib/python3.8/site-packages (1.26.0)

Step by step

This example shows how to create a Bedrock client with boto3 and configure Provisioned Throughput for a Bedrock model endpoint. Provisioned Throughput is specified in capacityUnits to reserve request capacity.

python

import boto3

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

# Example: configure provisioned throughput for a model endpoint
# Note: Replace 'your-endpoint-name' with your actual Bedrock endpoint

response = client.update_provisioned_throughput(
    endpointName='your-endpoint-name',
    provisionedThroughput={
        'capacityUnits': 10  # Number of throughput units to reserve
    }
)

print('Provisioned Throughput updated:', response)

output

Provisioned Throughput updated: {'ResponseMetadata': {'RequestId': '1234abcd-5678-efgh-ijkl-9012mnopqrst', 'HTTPStatusCode': 200, 'RetryAttempts': 0}}

Common variations

You can adjust capacityUnits dynamically based on workload needs to scale throughput. AWS Bedrock also supports on-demand throughput without provisioning, but Provisioned Throughput ensures predictable latency.

For asynchronous calls, use asyncio with aiobotocore or AWS SDK v2 for Python.

python

import asyncio
import aiobotocore

async def update_throughput_async():
    session = aiobotocore.get_session()
    async with session.create_client('bedrock-runtime', region_name='us-east-1') as client:
        response = await client.update_provisioned_throughput(
            endpointName='your-endpoint-name',
            provisionedThroughput={'capacityUnits': 20}
        )
        print('Async update response:', response)

asyncio.run(update_throughput_async())

output

Async update response: {'ResponseMetadata': {'RequestId': 'abcd1234-5678-efgh-ijkl-9012mnopqrst', 'HTTPStatusCode': 200, 'RetryAttempts': 0}}

Troubleshooting

If you receive ThrottlingException, increase capacityUnits to handle more requests.
If update_provisioned_throughput fails with ResourceNotFoundException, verify your endpointName is correct and the endpoint exists.
Ensure your IAM role has bedrock:UpdateProvisionedThroughput permission.

✅

Key Takeaways

Use AWS Bedrock Provisioned Throughput to guarantee consistent LLM request capacity and low latency.
Configure throughput units via AWS SDK or CLI by specifying capacityUnits for your Bedrock endpoint.
Adjust provisioned capacity dynamically to match workload demands and avoid throttling.
Ensure proper IAM permissions and correct endpoint names to avoid common errors.

Verified 2026-04

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