{
  "context": "This evaluation assesses how well the engineer uses the AWS Lambda Powertools Metrics module to emit CloudWatch custom metrics using Embedded Metric Format (EMF). The focus is on proper usage of the Metrics class, decorators, dimensions, metadata, and the single_metric context manager.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Metrics initialization",
      "description": "Creates a Metrics instance with namespace='OrderProcessing' and service name configured",
      "max_score": 10
    },
    {
      "name": "Log metrics decorator",
      "description": "Uses @metrics.log_metrics decorator on the Lambda handler function to automatically serialize and publish metrics",
      "max_score": 15
    },
    {
      "name": "Metric emission",
      "description": "Calls metrics.add_metric() to emit the required metrics: processing_time_ms, order_amount, and orders_processed with appropriate values",
      "max_score": 20
    },
    {
      "name": "Metric units",
      "description": "Specifies correct MetricUnit for each metric: MetricUnit.Milliseconds for processing_time_ms, MetricUnit.Count for order_amount and orders_processed",
      "max_score": 15
    },
    {
      "name": "Default dimensions",
      "description": "Uses metrics.add_dimension() or metrics.set_default_dimensions() to set region and payment_method dimensions for all metrics",
      "max_score": 15
    },
    {
      "name": "Metadata addition",
      "description": "Uses metrics.add_metadata() to add high-cardinality data like order_id and customer_id for CloudWatch Logs Insights searchability",
      "max_score": 10
    },
    {
      "name": "Single metric context",
      "description": "Uses metrics.single_metric() context manager to emit VIP customer metrics with a unique customer_tier dimension that differs from the default dimensions",
      "max_score": 15
    }
  ]
}