Place attributes correctly

When implementing observability with OpenTelemetry, place attributes at the appropriate level in the telemetry hierarchy to ensure effective data collection and analysis:

1. Use resource attributes for static, process-level information that applies globally:

   # Good: Static information as resource attributes
   resource = Resource.create({
       "environment": "production",
       "service.name": "api-server",
       "service.version": "1.0.0"
   })
   meter_provider = MeterProvider(resource=resource)
   

2. Use baggage only for appropriate correlation use cases:

   # Good: Valid baggage usage
   processor = BaggageMeasurementProcessor(baggage_keys=["user.id", "synthetic_request"])
      
   # Bad: Don't use trace.id in baggage; use exemplars instead for trace correlation
   

3. Avoid timestamps as metric attributes - timestamps are already handled by the telemetry system:

   # Bad: Don't add timestamps to metrics
   new_attributes["processed_at"] = str(int(time.time()))  # Avoid this!
   

4. Add instrument-specific attributes using the proper API methods:

   # Good: Use proper attribute fields in API calls
   meter = meter_provider.get_meter("name", "version", schema_url="url", attributes={"component": "billing"})
   

This approach reduces cardinality issues, improves query performance, and follows OpenTelemetry best practices for attribute placement.