Amazon Bedrock
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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.
Provider Slug: 
bedrockSetup
Step 1: Create AWS Account
- Log into the AWS console (opens in a new tab)
 - Sign up for a new AWS account or use your existing account
 - Complete the account verification process
 
Step 2: Access Bedrock Service
- Navigate to the Bedrock service (opens in a new tab) in your AWS console
 - Enable Bedrock service for your account
 - Configure necessary permissions and access
 
Step 3: Generate Access Credentials
- Visit Security credentials (opens in a new tab) in your AWS console
 - Create an IAM user with Bedrock permissions
 - Generate Access Key ID and Secret Access Key
 - Copy both credentials (you'll need them for configuration)
 
AWS Bedrock Security Credentials Screen
Step 4: Configure in Lamatic
- Open your Lamatic.ai studio (opens in a new tab)
 - Navigate to Models section
 - Select Amazon Bedrock from the provider list
 - Paste your Access Key ID and Secret Access Key in the designated fields
 - 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)