Amazon Bedrock

Amazon Bedrock is a fully managed service by Amazon Web Services (AWS) that simplifies the creation and scaling of generative AI applications. It provides access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon's own models, all through a single API.

Get Started

Step 1: Create AWS Account

1. Log into the AWS console (opens in a new tab)
2. Sign up for a new AWS account or use your existing account
3. Complete the account verification process

Step 2: Access Bedrock Service

1. Navigate to the Bedrock service (opens in a new tab) in your AWS console
2. Enable Bedrock service for your account
3. Configure necessary permissions and access

Step 3: Generate Access Credentials

1. Visit Security credentials (opens in a new tab) in your AWS console
2. Create an IAM user with Bedrock permissions
3. Generate Access Key ID and Secret Access Key
4. Copy both credentials (you'll need them for configuration)

AWS Bedrock Security Credentials Screen

Step 4: Configure in Lamatic

1. Open your Lamatic.ai studio (opens in a new tab)
2. Navigate to Models section
3. Select Amazon Bedrock from the provider list
4. Paste your Access Key ID and Secret Access Key in the designated fields
5. Save your changes

Key Features

• Multiple Model Providers: Access to models from AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon
• Fully Managed Service: AWS handles infrastructure, scaling, and maintenance
• Enterprise Security: Built on AWS security and compliance standards
• Cost Effective: Pay-per-use pricing with no upfront costs
• Scalable: Automatic scaling based on demand
• Developer Friendly: Simple API integration with comprehensive documentation
• AWS Integration: Seamless integration with other AWS services
• Compliance Ready: Meets enterprise compliance and security requirements

Available Models

Amazon Bedrock provides access to models from multiple providers:

• Anthropic Models: Claude models for advanced reasoning and creative tasks
• AI21 Labs Models: Jurassic models for text generation and analysis
• Cohere Models: Command models for text generation and embeddings
• Meta Models: Llama models for various language tasks
• Mistral AI Models: Mistral models for efficient text processing
• Stability AI Models: Models for image generation and creative tasks
• Amazon Models: Titan models for text generation and embeddings

Check the AWS Bedrock Models (opens in a new tab) documentation for the complete list of available models and their specifications.

Configuration Options

• Access Key ID: Your AWS Access Key ID for authentication
• Secret Access Key: Your AWS Secret Access Key for authentication
• Region Selection: Choose the appropriate AWS region for your use case
• Model Selection: Choose from available Bedrock models
• Custom Parameters: Configure temperature, max_tokens, top_p, and other generation parameters
• Streaming: Enable real-time text generation streaming
• IAM Permissions: Configure appropriate permissions for Bedrock access

Best Practices

• Credential Security: Keep your AWS credentials secure and never share them publicly
• IAM Best Practices: Use least-privilege access and rotate credentials regularly
• Rate Limiting: Be aware of Bedrock's rate limits and implement appropriate throttling
• Model Selection: Choose the appropriate model based on your use case and requirements
• Error Handling: Implement proper error handling for API failures and rate limits
• Cost Optimization: Monitor your usage and optimize prompts to reduce costs
• Region Selection: Choose the region closest to your users for better performance
• Security Configuration: Configure appropriate IAM roles and permissions

Troubleshooting

Invalid Credentials:

• Verify your Access Key ID and Secret Access Key are correct
• Check if your IAM user has the necessary Bedrock permissions
• Ensure your AWS account is active and verified

Access Denied:

• Verify your IAM user has Bedrock permissions
• Check if Bedrock service is enabled in your region
• Ensure proper IAM policies are attached to your user

Rate Limit Exceeded:

• Implement exponential backoff in your requests
• Consider upgrading your AWS plan for higher limits
• Monitor your usage in the AWS console

Model Not Available:

• Check if the model is available in your selected region
• Verify your account has access to the specific model
• Contact AWS support for model availability issues

Region Issues:

• Ensure Bedrock is available in your selected region
• Check if your credentials are valid for the selected region
• Verify region-specific model availability

Important Notes

• Keep your AWS credentials secure and never share them
• Check provider's pricing before generating credentials: AWS pricing (opens in a new tab)
• Regularly rotate your AWS credentials for enhanced security
• Monitor your usage and costs in the AWS console
• Test your integration after adding each credential
• Some models may require additional setup or approval
• Be aware of AWS Bedrock's terms of service and usage policies
• Consider AWS compliance and security requirements for enterprise use
• Ensure proper IAM configuration for secure access

Additional Resources

• AWS Bedrock Documentation (opens in a new tab)
• Model Documentation (opens in a new tab)
• Pricing Information (opens in a new tab)
• AWS Support (opens in a new tab)

Need help? Contact Lamatic support (opens in a new tab)