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🔍 AWS Lambda Function Discovery

Burki Voice AI provides automatic Lambda function discovery to streamline the integration of your existing serverless functions. No more manual typing or guessing function names!

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Overview

The Lambda Function Discovery feature allows you to:
  • 🔍 Browse all Lambda functions in your AWS account
  • 📊 View detailed function metadata (runtime, memory, timeout)
  • ✅ Validate function existence before creating tools
  • ⚡ Auto-populate tool configuration forms
  • 🛡️ Prevent typos and invalid function names

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How It Works

1

Enter AWS Credentials

Provide your AWS Access Key ID and Secret Access Key in the Lambda tool configuration form.
Credentials Required
{
  "access_key": "AKIA1234567890EXAMPLE",
  "secret_key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY"
}
2

Select Region

Choose the AWS region where your Lambda functions are deployed from the dropdown menu.Supported Regions:
  • us-east-1 (N. Virginia)
  • us-west-2 (Oregon)
  • eu-west-1 (Ireland)
  • ap-southeast-1 (Singapore)
  • And more…
3

Discover Functions

Click the ”🔍 Discover Functions” button to automatically fetch all Lambda functions from your AWS account.The system will call the AWS Lambda ListFunctions API to retrieve function metadata.
4

Browse & Select

A dropdown menu appears showing all discovered functions with:
  • Function name
  • Description (if available)
  • Runtime environment
  • Memory allocation
  • Last modified date
5

Auto-populate Form

When you select a function, the form automatically fills in:
  • Function name
  • Tool description (based on Lambda description)
  • Default payload template

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Function Discovery Response

When you discover functions, you’ll see detailed metadata for each:
Example Discovery Response
{
  "success": true,
  "message": "Found 5 Lambda functions",
  "functions": [
    {
      "function_name": "customer-lookup-service",
      "description": "Look up customer data by phone number",
      "runtime": "python3.9",
      "timeout": 30,
      "memory_size": 512,
      "code_size": 1024000,
      "handler": "lambda_function.lambda_handler",
      "version": "$LATEST",
      "last_modified": "2024-01-15T10:30:00Z"
    },
    {
      "function_name": "order-processing",
      "description": "Process customer orders and payments",
      "runtime": "nodejs18.x", 
      "timeout": 60,
      "memory_size": 1024,
      "handler": "index.handler"
    },
    {
      "function_name": "inventory-check",
      "description": "Check product availability in real-time",
      "runtime": "python3.8",
      "timeout": 15,
      "memory_size": 256,
      "handler": "check.availability"
    }
  ]
}

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Required IAM Permissions

For function discovery to work, your AWS credentials need specific permissions:
Required IAM Policy
{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "lambda:ListFunctions",
        "lambda:GetFunction",
        "lambda:GetFunctionConfiguration",
        "lambda:InvokeFunction"
      ],
      "Resource": "*"
    }
  ]
}
Permission Breakdown:
  • lambda:ListFunctions - Required for discovery
  • lambda:GetFunction - Gets function code and configuration
  • lambda:GetFunctionConfiguration - Gets runtime settings
  • lambda:InvokeFunction - Required for tool execution

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Security Best Practices

✅ Recommended:
  • Create a dedicated IAM user for Burki Voice AI
  • Use minimal required permissions (principle of least privilege)
  • Rotate credentials regularly
  • Use IAM roles in production environments when possible
❌ Avoid:
  • Using root AWS account credentials
  • Overly broad permissions (* on all resources)
  • Hardcoding credentials in code
  • Sharing credentials across multiple applications
Example IAM User Setup:
  1. Create new IAM user: burkivoice-lambda-integration
  2. Attach custom policy with Lambda permissions
  3. Generate Access Key ID and Secret Access Key
  4. Use these credentials only for Burki Voice AI

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Troubleshooting

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❌ “AWS credentials not found”

Problem: Missing or invalid AWS credentials Solution:
  • Verify Access Key ID and Secret Access Key are correct
  • Ensure credentials have not expired
  • Check for typos in credential entry

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❌ “Access denied” error

Problem: Insufficient IAM permissions Solution:
  • Attach required Lambda permissions to your IAM user
  • Verify the IAM policy includes lambda:ListFunctions
  • Check AWS region permissions

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❌ “No functions found”

Problem: No Lambda functions in selected region Solution:
  • Verify you’re searching in the correct AWS region
  • Confirm Lambda functions exist in your account
  • Try a different region where functions are deployed

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❌ Connection timeout

Problem: Network or AWS service issues Solution:
  • Check your internet connection
  • Verify AWS service status
  • Try again after a few minutes
  • Ensure your IP isn’t blocked by AWS

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Alternative: Manual Entry

If function discovery isn’t suitable for your use case, you can still manually enter Lambda function details:
  • When to Use Manual Entry
  • Manual Configuration
  • Security constraints prevent credential sharing
  • Cross-account Lambda functions
  • Custom deployment processes
  • Testing with functions that don’t exist yet

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Integration Examples

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Customer Service Integration

{
  "function_name": "customer-lookup-service",
  "description": "Look up customer information by phone number",
  "use_case": "Assistant can access customer history during calls"
}

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E-commerce Order Management

{
  "function_name": "order-processing",
  "description": "Process and track customer orders",
  "use_case": "Handle order status inquiries and modifications"
}

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Inventory Management

{
  "function_name": "inventory-check",
  "description": "Check real-time product availability",
  "use_case": "Provide accurate stock information during sales calls"
}

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Payment Processing

{
  "function_name": "payment-gateway",
  "description": "Process payments and refunds securely",
  "use_case": "Handle billing inquiries and payment processing"
}

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Next Steps

After discovering and selecting your Lambda function:
  1. Configure payload template - Define how parameters are passed
  2. Set up function parameters - Specify what inputs the LLM should provide
  3. Test the integration - Use the built-in testing feature
  4. Assign to assistants - Make the tool available to your AI assistants
  5. Monitor usage - Track performance and success rates
Ready to integrate your Lambda functions? Head to the Tools Library and create your first Lambda tool with automatic function discovery!