我们目前在应用程序中使用Datadog进行监控和可观察性，并且我们已经集成了OpenTelemetry进行分布式跟踪。
我们遇到了一个主要问题
跨度间隔：目前，我们应用程序中的所有span都在一个服务下导出到Datadog。但是，我们希望根据使用的工具类型（例如Django，Elasticsearch，requests等）将它们分为不同的服务。
Manage.py

configure_opentelemetry()
    #Auto Instrumentation of Django, Psycopg2, Pymemcache, Elasticsearch, URLLib3, Requests
    DjangoInstrumentor().instrument(request_hook=fix_django_req)
    PymemcacheInstrumentor().instrument()
    RequestsInstrumentor().instrument()
    ElasticsearchInstrumentor().instrument()
    Psycopg2Instrumentor().instrument(enable_commenter=True, commenter_options={})
    URLLib3Instrumentor().instrument()

configure_opentelemetry方法

def configure_opentelemetry():
    
    otlp_exporter = OTLPSpanExporter(endpoint=os.getenv("OTEL_COLLECTOR_URL"), insecure=True)

    # Set the global TracerProvider with the OTLP exporter
    trace.set_tracer_provider(TracerProvider(resource=Resource.create({SERVICE_NAME: os.getenv("OTEL_SERVICE_NAME"), "env": os.getenv('OTEL_ENV')})))

    # Create a BatchSpanProcessor and add the exporter to it
    span_processor = BatchSpanProcessor(otlp_exporter)
    
    trace.get_tracer_provider().add_span_processor(span_processor)

    tracer = trace.get_tracer(__name__)

收集器配置：

receivers:
  otlp:
    protocols:
      grpc:
      http:

processors:
  batch:
    # batch metrics before sending to reduce API usage
    send_batch_max_size: 100
    send_batch_size: 10
    timeout: 10s

  memory_limiter:
    # drop metrics if memory usage gets too high
    check_interval: 1s
    limit_percentage: 65
    spike_limit_percentage: 20

  resourcedetection:
    detectors: [env, gcp]
    timeout: 2s
    override: false

  transform:
    error_mode: ignore
    trace_statements:
      - context: span
        statements:
          - set(attributes["resource.name"], name)

exporters:
  datadog:
    api:
      site: ${DD_SITE}
      key: ${DD_API_KEY}

extensions:
  health_check:

service:

  extensions: [health_check]
  pipelines:
    traces:
      receivers: [otlp]
      processors: [memory_limiter, resourcedetection, batch, transform]
      exporters: [datadog]
    metrics:
      receivers: [otlp]
      processors: [memory_limiter, resourcedetection, batch]
      exporters: [datadog]
      
  telemetry:
    logs:
      level: "debug"

救命啊！