How do I get started with Amazon Bedrock — what are the steps to enable or access it in my AWS account?

To get started with Amazon Bedrock in your AWS account, follow these steps. First, log into the AWS Management Console and navigate to the Amazon Bedrock service page. Bedrock is region-specific, so ensure you’re in a supported region like us-east-1 or us-west-2 (check AWS documentation for the latest regions). On the Bedrock dashboard, you’ll need to enable the service for your account. This typically involves reviewing AWS’s terms of service and clicking an Enable button. After enabling Bedrock, go to the Model access section to request access to specific foundation models (e.g., Anthropic Claude, AI21 Labs Jurassic). Some models require manual approval, which AWS may grant instantly or after a brief review. Once approved, you’ll see the models listed as “Access granted” under the Model access tab.

Next, use Bedrock through the AWS Console, SDK, or API. In the console, explore the Playground to test models with prompts without writing code. For programmatic access, install the AWS SDK (e.g., Boto3 for Python) and configure credentials with permissions for bedrock:ListFoundationModels and bedrock-runtime:InvokeModel. Use the SDK to list available models:

import boto3
client = boto3.client('bedrock')
models = client.list_foundation_models(byProvider='anthropic')

To generate text, switch to the bedrock-runtime client and invoke a model:

runtime_client = boto3.client('bedrock-runtime')
response = runtime_client.invoke_model(
 modelId='anthropic.claude-v2',
 body=json.dumps({"prompt": "Explain quantum computing"}),
)

Replace anthropic.claude-v2 with your model ID and customize the input parameters. Responses are returned in JSON format, which you can parse for output.

Finally, follow best practices for security and cost. Assign IAM policies to limit Bedrock access to specific users or roles. For example, create a policy allowing only bedrock-runtime:InvokeModel on approved model IDs. Monitor usage and costs via AWS Cost Explorer, as Bedrock charges per 1,000 input/output tokens (pricing varies by model). Test models in the Playground to evaluate performance before integrating them into applications. For production workloads, enable AWS CloudTrail to audit API activity and set up error handling for rate limits or throttling. Refer to the AWS Bedrock documentation for updates, as new models and features are added regularly.