Log Processor Implementation Guide

Part 1: Implementation Details

Function Design

• Input: A string containing log entries
• Output: A dictionary containing:
  • total_errors: Count of all error occurrences
  • unique_error_messages: List of unique error messages

Core Logic

The implementation will utilize regular expressions to parse log entries and extract error messages with the following approach:

1. Parse log entries to identify ERROR level messages
2. Count total ERROR occurrences
3. Collect and alphabetically sort unique error messages
4. Handle edge cases and malformed inputs

Implementation Steps

1. Function Development

The main function process_log_file will be implemented with these considerations:

• Regular expression pattern matching for ERROR entries
• Message extraction and counting logic
• Comprehensive error handling for:
  • Empty input validation
  • Malformed input detection
  • Input type verification
• Type hints for improved code clarity

2. Testing Strategy

Develop unit tests to verify:

• Basic functionality with valid inputs
• Edge case handling
• Error handling for invalid inputs
• Sorting and uniqueness requirements

Part 2: AWS Deployment & Demo

AWS Lambda Configuration

• Runtime: Python 3.9+
• Memory Allocation: 128 MB
• Timeout Setting: 30 seconds
• IAM Role: Basic Lambda execution role
  • Includes CloudWatch logging permissions

Lambda Function Structure

def lambda_handler(event, context):
    # Implementation details here
    pass

API Gateway Integration (Optional)

• REST API endpoint creation
• Testing procedures:
  • Postman verification
  • cURL command testing