Métricas de tiempo de ejecución

Información general

Las métricas de tiempo de ejecución monitorizan el uso de memoria, la recolección de basura y la paralelización de tu aplicación. Las bibliotecas de rastreo de Datadog recopilan automáticamente estas métricas de entornos compatibles y las envían al Agent.

Estas métricas te permiten identificar cuellos de botella, solucionar problemas de rendimiento y optimizar el uso de los recursos. Al consultar las métricas de tiempo de ejecución junto con las trazas y los logs, obtendrás una visibilidad completa del estado y el rendimiento de tu aplicación.

Compatibilidad

Las métricas de tiempo de ejecución están disponibles para varios lenguajes de programación y tiempos de ejecución, con distintos niveles de compatibilidad y opciones de configuración.

  • Activado por defecto: Sí
  • Versión de la biblioteca: 0.29.0 o posterior
  • Tiempos de ejecución: Java 8 o posterior
La recopilación de métricas de JMX no es compatible con los entornos AWS Lambda.
  • Activado por defecto: No
  • Versión de la biblioteca: 0.30.0 o posterior
  • Nivel de compatibilidad: Vista previa
  • Tiempos de ejecución: Todas las versiones de Python compatibles
  • Activado por defecto: No
  • Versión de la biblioteca: 0.44.0 o posterior
  • Tiempos de ejecución: Todas las versiones de Ruby compatibles
Debes añadir la gema dogstatsd-ruby a tu aplicación.
  • Activado por defecto: No
  • Versión de la biblioteca: 1.18.0 o posterior
  • Tiempos de ejecución: Todas las versiones de Go compatibles
  • Activado por defecto: No
  • Versión de la biblioteca: 3.0.0 o posterior
  • Tiempos de ejecución: Todas las versiones de Node.js compatibles
  • Activado por defecto: No
  • Versión de la biblioteca: 1.23.0 o posterior
  • Tiempos de ejecución: .NET Framework 4.6.1 o posterior y .NET Core 3.1 o posterior (incluyendo .NET 5 y posteriores).

Permisos para Internet Information Services (IIS)

En .NET Framework, las métricas se recopilan mediante contadores de rendimiento. Los usuarios en sesiones de inicio de sesión no interactivas (que incluyen cuentas de grupos de aplicaciones IIS y algunas cuentas de servicio) deben añadirse al grupo Usuarios de monitorización de rendimiento para acceder a los datos del contador.

Los grupos de aplicaciones IIS utilizan cuentas especiales que no aparecen en lista de usuarios. Para añadirlas al grupo de usuarios de monitorización de rendimiento, busca IIS APPPOOL\<name of the pool>. Por ejemplo, el usuario para el DefaultAppPool sería IIS APPPOOL\DefaultAppPool.

Puedes hacer esto desde la interfaz de usuario “Gestión de ordenadores” o desde una acción de comando del administrador:

net localgroup "Performance Monitor Users" "IIS APPPOOL\DefaultAppPool" /add
No se admiten métricas en tiempo de ejecución para PHP.
No se admiten métricas en tiempo de ejecución para C++.

Instrucciones de instalación

Para configurar las métricas en tiempo de ejecución, debes configurar tanto el Datadog Agent como tu aplicación.

1. Configurar el Datadog Agent

Habilita DogStatsD para el Agent. Por defecto, el Datadog Agent está configurado para ingerir métricas con UDP a través del puerto 8125.

Cuando el Agent se ejecuta en entornos de contenedores, es necesaria una configuración adicional:

  1. Define dogstatsd_non_local_traffic: true en tu archivo de configuración principaldatadog.yaml, o define la variable de entorno DD_DOGSTATSD_NON_LOCAL_TRAFFIC=true.
  2. Sigue estas instrucciones de configuración específica de contenedor:
Docker
Kubernetes
Amazon ECS
ECS Fargate

  1. Define DD_SITE en el Datadog Agent como para asegurarte de que el Agent envía los datos a la localización Datadog correcta.

2. Configurar la aplicación

Configura las métricas de tiempo de ejecución en tu aplicación utilizando variables de entorno. Algunos lenguajes también permiten configurar métricas de tiempo de ejecución directamente en el código.

Variables de entorno

Utiliza las siguientes variables de entorno para configurar métricas de tiempo de ejecución en tu aplicación:

DD_RUNTIME_METRICS_ENABLED
Por defecto: true para Java, false para todos los demás lenguajes
Descripción: Activa la recopilación de métricas de tiempo de ejecución. Las métricas se envían al Datadog Agent, según lo configurado para la aplicación instrumentada.
DD_RUNTIME_METRICS_RUNTIME_ID_ENABLED
Por defecto: true para Java, false para Node.js, Ruby y Python. No existe para .NET y Go. Siempre se indica runtime_id.
Descripción: Habilita métricas en tiempo de ejecución mejoradas, proporcionando una etiqueta (tag) runtime_id junto con cada métrica. runtime_id representa el identificador de procesos de la aplicación y te permite correlacionar directamente las métricas de tiempo de ejecución con aplicaciones individuales en ejecución.
DD_AGENT_HOST
Por defecto: localhost
Descripción: Define la dirección del host para el envío de métricas de la biblioteca de rastreo. Puede ser un nombre de host o una dirección IP.
DD_DOGSTATSD_PORT
Por defecto: 8125
Descripción: Define el puerto para el envío de métricas de la biblioteca de rastreo.

Configuración basada en códigos

Además de las variables de entorno, algunos lenguajes permiten configurar métricas de tiempo de ejecución directamente en el código.

Sólo puedes activar las métricas de tiempo de ejecución con variables de entorno.

Sin embargo, puedes ampliar las métricas recopiladas añadiendo métricas JMX personalizadas. Para obtener más información, consulta la documentación de la integración JMX.

Puedes activar las métricas de tiempo de ejecución con variables de entorno o en código:

from ddtrace.runtime import RuntimeMetrics
RuntimeMetrics.enable()
Esto sólo se aplica si no estás utilizando ddtrace-run

Puedes activar las métricas de tiempo de ejecución con variables de entorno o en código:

# config/initializers/datadog.rb
require 'datadog/statsd'
require 'datadog' # Use 'ddtrace' if you're using v1.x

Datadog.configure do |c|
  c.runtime_metrics.enabled = true

  # Optionally, you can configure the DogStatsD instance used for sending runtime metrics.
  # DogStatsD is automatically configured with default settings if `dogstatsd-ruby` is available.
  # You can configure with host and port of Datadog agent; defaults to 'localhost:8125'.
  c.runtime_metrics.statsd = Datadog::Statsd.new
end

Puedes activar las métricas de tiempo de ejecución con variables de entorno o en código:

// Basic configuration
tracer.Start(tracer.WithRuntimeMetrics())

// With custom DogStatsD address
tracer.Start(
  tracer.WithRuntimeMetrics(),
  tracer.WithDogstatsdAddr("custom-host:8125")
)

La opción WithDogstatsdAddr te permite especificar una dirección personalizada para el servidor DogStatsD. Utiliza la opción WithDogstatsdAddr (o WithDogstatsdAddress v1), si tu dirección difiere de la predeterminada localhost:8125. (Disponible para la v1.18.0 o posterior)

Puedes activar las métricas de tiempo de ejecución con variables de entorno o en código:

const tracer = require('dd-trace').init({
  // Other tracer options...
  runtimeMetrics: true
})

Sólo puedes activar las métricas de tiempo de ejecución con variables de entorno.

Dashboards

Una vez finalizada la configuración, puedes ver las métricas de tiempo de ejecución en:

  • Página con información del servicio instrumentado
  • Pestaña Métricas del gráfico de llama
  • Dashboards de tiempo de ejecución por defecto
Traza de tiempo de ejecución de JVM

Solucionar problemas

  • Para asociar métricas de tiempo de ejecución dentro de los gráficos de llama, asegúrate de que la etiqueta env (que distingue entre mayúsculas y minúsculas) está configurada y coincide en todo tu entorno.
  • Para que las métricas de tiempo de ejecución aparezcan en la página del servicio al utilizar Fargate, asegúrate de que DD_DOGSTATSD_TAGS está configurado en la tarea de tu Agent y que la etiqueta env configurada coincide con la env del servicio instrumentado.

Datos recopilados

Cada lenguaje compatible recopila un conjunto de métricas de tiempo de ejecución que proporcionan información sobre el uso de la memoria, la recolección de basura, el uso de la CPU y otros indicadores de rendimiento.

jvm.heap_memory
(gauge)
The total Java heap memory used.
Shown as byte
jvm.heap_memory_committed
(gauge)
The total Java heap memory committed to be used.
Shown as byte
jvm.heap_memory_init
(gauge)
The initial Java heap memory allocated.
Shown as byte
jvm.heap_memory_max
(gauge)
The maximum Java heap memory available.
Shown as byte
jvm.loaded_classes
(gauge)
Number of classes currently loaded.
jvm.non_heap_memory
(gauge)
The total Java non-heap memory used. Non-heap memory is calculated as follows: Metaspace + CompressedClassSpace + CodeCache
Shown as byte
jvm.non_heap_memory_committed
(gauge)
The total Java non-heap memory committed to be used.
Shown as byte
jvm.non_heap_memory_init
(gauge)
The initial Java non-heap memory allocated.
Shown as byte
jvm.non_heap_memory_max
(gauge)
The maximum Java non-heap memory available.
Shown as byte
jvm.thread_count
(count)
The number of live threads.
Shown as thread
jvm.gc.cms.count
(count)
The total number of garbage collections that have occurred.
jvm.gc.major_collection_count
(gauge)
The rate of major garbage collections. Set new_gc_metrics: true to receive this metric.
jvm.gc.minor_collection_count
(gauge)
The rate of minor garbage collections. Set new_gc_metrics: true to receive this metric.
jvm.gc.parnew.time
(gauge)
The approximate accumulated garbage collection time elapsed.
Shown as millisecond
jvm.gc.major_collection_time
(gauge)
The fraction of time spent in major garbage collection. Set new_gc_metrics: true to receive this metric.
Shown as permille
jvm.gc.minor_collection_time
(gauge)
The fraction of time spent in minor garbage collection. Set new_gc_metrics: true to receive this metric.
Shown as permille
runtime.python.cpu.time.sys
(gauge)
Number of seconds executing in the kernel
Shown as second
runtime.python.cpu.time.user
(gauge)
Number of seconds executing outside the kernel
Shown as second
runtime.python.cpu.percent
(gauge)
CPU utilization percentage
Shown as percent
runtime.python.cpu.ctx_switch.voluntary
(gauge)
Number of voluntary context switches
Shown as invocation
runtime.python.cpu.ctx_switch.involuntary
(gauge)
Number of involuntary context switches
Shown as invocation
runtime.python.gc.count.gen0
(gauge)
Number of generation 0 objects
Shown as resource
runtime.python.gc.count.gen1
(gauge)
Number of generation 1 objects
Shown as resource
runtime.python.gc.count.gen2
(gauge)
Number of generation 2 objects
Shown as resource
runtime.python.mem.rss
(gauge)
Resident set memory
Shown as byte
runtime.python.thread_count
(gauge)
Number of threads
Shown as thread
runtime.ruby.class_count
(gauge)
Total number of classes loaded
Shown as resource
runtime.ruby.gc.remembered_wb_unprotected_objects
(gauge)
Number of write-barrier unprotected objects in the remembered set
Shown as resource
runtime.ruby.gc.remembered_wb_unprotected_objects_limit
(gauge)
Limit on write-barrier unprotected objects allowed in the remembered set
Shown as resource
runtime.ruby.gc.oldmalloc_increase_bytes
(gauge)
Total bytes allocated to old objects
Shown as byte
runtime.ruby.gc.oldmalloc_increase_bytes_limit
(gauge)
Bytes limit that will trigger garbage collection of old objects
Shown as byte
runtime.ruby.gc.malloc_increase_bytes
(gauge)
Total bytes allocated to objects
Shown as byte
runtime.ruby.gc.malloc_increase_bytes_limit
(gauge)
Bytes limit that will trigger garbage collection of objects
Shown as byte
runtime.ruby.gc.total_allocated_objects
(gauge)
Total number of allocated objects over the lifetime of this process
Shown as resource
runtime.ruby.gc.total_freed_objects
(gauge)
Total number of freed objects over the lifetime of this process
Shown as resource
runtime.ruby.gc.total_allocated_pages
(gauge)
Total number of allocated pages over the lifetime of this process
Shown as page
runtime.ruby.gc.total_freed_pages
(gauge)
Total number of freed pages over the lifetime of this process
Shown as page
runtime.ruby.gc.heap_live_slots
(gauge)
Number of live objects slots
Shown as resource
runtime.ruby.gc.heap_final_slots
(gauge)
Number of object slots with finalizers attached to them
Shown as resource
runtime.ruby.gc.heap_marked_slots
(gauge)
Count of old objects which survived more than 3 GC cycles and number of write-barrier unprotected objects
Shown as resource
runtime.ruby.gc.heap_available_slots
(gauge)
Total number of slots in heap pages
Shown as resource
runtime.ruby.gc.heap_free_slots
(gauge)
Number of free slots in heap pages
Shown as resource
runtime.ruby.thread_count
(gauge)
Total number of threads
Shown as thread
runtime.ruby.gc.old_objects
(gauge)
Total number of old objects
Shown as resource
runtime.ruby.gc.old_objects_limit
(gauge)
Limit on number of old objects
Shown as resource
runtime.ruby.global_constant_state
(gauge)
Global constant cache generation
Shown as event
runtime.ruby.global_method_state
(gauge)
Global method cache generation
Shown as event
runtime.ruby.constant_cache_invalidations
(gauge)
Constant cache invalidations
Shown as resource
runtime.ruby.constant_cache_misses
(gauge)
Constant cache misses
Shown as resource
runtime.go.num_cpu
(gauge)
CPUs detected by the runtime.
Shown as resource
runtime.go.num_goroutine
(gauge)
goroutines spawned.
Shown as invocation
runtime.go.num_cgo_call
(gauge)
CGO calls made.
Shown as invocation
runtime.go.mem_stats.alloc
(gauge)
Alloc is bytes of allocated heap objects.
Shown as byte
runtime.go.mem_stats.total_alloc
(gauge)
TotalAlloc is cumulative bytes allocated for heap objects.
Shown as byte
runtime.go.mem_stats.sys
(gauge)
Sys is the total bytes of memory obtained from the OS.
Shown as byte
runtime.go.mem_stats.lookups
(gauge)
Lookups is the number of pointer lookups performed by the
Shown as unit
runtime.go.mem_stats.mallocs
(gauge)
Mallocs is the cumulative count of heap objects allocated.
Shown as unit
runtime.go.mem_stats.frees
(gauge)
Frees is the cumulative count of heap objects freed.
Shown as unit
runtime.go.mem_stats.heap_alloc
(gauge)
HeapAlloc is bytes of allocated heap objects.
Shown as byte
runtime.go.mem_stats.heap_sys
(gauge)
HeapSys is bytes of heap memory obtained from the OS.
Shown as byte
runtime.go.mem_stats.heap_idle
(gauge)
HeapIdle is bytes in idle (unused) spans.
Shown as byte
runtime.go.mem_stats.heap_inuse
(gauge)
HeapInuse is bytes in in-use spans.
Shown as byte
runtime.go.mem_stats.heap_released
(gauge)
HeapReleased is bytes of physical memory returned to the OS.
Shown as byte
runtime.go.mem_stats.heap_objects
(gauge)
HeapObjects is the number of allocated heap objects.
Shown as unit
runtime.go.mem_stats.stack_inuse
(gauge)
StackInuse is bytes in stack spans.
Shown as byte
runtime.go.mem_stats.stack_sys
(gauge)
StackSys is bytes of stack memory obtained from the OS.
Shown as byte
runtime.go.mem_stats.m_span_inuse
(gauge)
MSpanInuse is bytes of allocated mspan structures.
Shown as byte
runtime.go.mem_stats.m_span_sys
(gauge)
MSpanSys is bytes of memory obtained from the OS for mspan structures.
Shown as byte
runtime.go.mem_stats.m_cache_inuse
(gauge)
MCacheInuse is bytes of allocated mcache structures.
Shown as byte
runtime.go.mem_stats.m_cache_sys
(gauge)
MCacheSys is bytes of memory obtained from the OS for
Shown as byte
runtime.go.mem_stats.buck_hash_sys
(gauge)
BuckHashSys is bytes of memory in profiling bucket hash tables.
Shown as byte
runtime.go.mem_stats.gc_sys
(gauge)
GCSys is bytes of memory in garbage collection metadata.
Shown as byte
runtime.go.mem_stats.other_sys
(gauge)
OtherSys is bytes of memory in miscellaneous off-heap
Shown as byte
runtime.go.mem_stats.next_gc
(gauge)
NextGC is the target heap size of the next GC cycle.
Shown as byte
runtime.go.mem_stats.last_gc
(gauge)
LastGC is the time the last garbage collection finished, as nanoseconds since 1970 (the UNIX epoch).
Shown as nanosecond
runtime.go.mem_stats.pause_total_ns
(gauge)
PauseTotalNs is the cumulative nanoseconds in GC
Shown as nanosecond
runtime.go.mem_stats.num_gc
(gauge)
NumGC is the number of completed GC cycles.
Shown as unit
runtime.go.mem_stats.num_forced_gc
(gauge)
NumForcedGC is the number of GC cycles that were forced by the application calling the GC function.
Shown as unit
runtime.go.mem_stats.gc_cpu_fraction
(gauge)
GCCPUFraction is the fraction of this program’s available CPU time used by the GC since the program started.
Shown as fraction
runtime.go.gc_stats.pause_quantiles.min
(gauge)
Distribution of GC pause times: minimum values
Shown as nanosecond
runtime.go.gc_stats.pause_quantiles.25p
(gauge)
Distribution of GC pause times: 25th percentile
Shown as nanosecond
runtime.go.gc_stats.pause_quantiles.75p
(gauge)
Distribution of GC pause times: 50th percentile
Shown as nanosecond
runtime.go.gc_stats.pause_quantiles.95p
(gauge)
Distribution of GC pause times: 75th percentile
Shown as nanosecond
runtime.go.gc_stats.pause_quantiles.max
(gauge)
Distribution of GC pause times: maximum values
Shown as nanosecond
runtime.node.cpu.user
(gauge)
CPU usage in user code
Shown as percent
runtime.node.cpu.system
(gauge)
CPU usage in system code
Shown as percent
runtime.node.cpu.total
(gauge)
Total CPU usage
Shown as percent
runtime.node.mem.rss
(gauge)
Resident set size
Shown as byte
runtime.node.mem.heap_total
(gauge)
Total heap memory
Shown as byte
runtime.node.mem.heap_used
(gauge)
Heap memory usage
Shown as byte
runtime.node.mem.external
(gauge)
External memory
Shown as byte
runtime.node.heap.total_heap_size
(gauge)
Total heap size
Shown as byte
runtime.node.heap.total_heap_size_executable
(gauge)
Total executable heap size
Shown as byte
runtime.node.heap.total_physical_size
(gauge)
Total physical heap size
Shown as byte
runtime.node.heap.used_heap_size
(gauge)
Used heap size
Shown as byte
runtime.node.heap.heap_size_limit
(gauge)
Heap size limit
Shown as byte
runtime.node.heap.malloced_memory
(gauge)
Malloced memory
Shown as byte
runtime.node.heap.peak_malloced_memory
(gauge)
Peak allocated memory
Shown as byte
runtime.node.heap.size.by.space
(gauge)
Heap space size
Shown as byte
runtime.node.heap.used_size.by.space
(gauge)
Heap space used size
Shown as byte
runtime.node.heap.available_size.by.space
(gauge)
Heap space available size
Shown as byte
runtime.node.heap.physical_size.by.space
(gauge)
Heap space physical size
Shown as byte
runtime.node.process.uptime
(gauge)
Process uptime
Shown as second
runtime.node.event_loop.delay.max
(gauge)
Maximum event loop delay
Shown as nanosecond
runtime.node.event_loop.delay.min
(gauge)
Minimum event loop delay
Shown as nanosecond
runtime.node.event_loop.delay.avg
(gauge)
Average event loop delay
Shown as nanosecond
runtime.node.event_loop.delay.sum
(rate)
Total event loop delay
Shown as nanosecond
runtime.node.event_loop.delay.median
(gauge)
Median event loop delay
Shown as nanosecond
runtime.node.event_loop.delay.95percentile
(gauge)
95th percentile event loop delay
Shown as nanosecond
runtime.node.event_loop.delay.count
(rate)
Event loop iteration count where a delay is detected
Shown as execution
runtime.node.gc.pause.max
(gauge)
Maximum garbage collection pause
Shown as nanosecond
runtime.node.gc.pause.min
(gauge)
Minimum garbage collection pause
Shown as nanosecond
runtime.node.gc.pause.avg
(gauge)
Average garbage collection pause
Shown as nanosecond
runtime.node.gc.pause.sum
(rate)
Total garbage collection pause
Shown as nanosecond
runtime.node.gc.pause.median
(gauge)
Median garbage collection pause
Shown as nanosecond
runtime.node.gc.pause.95percentile
(gauge)
95th percentile garbage collection pause
Shown as nanosecond
runtime.node.gc.pause.count
(rate)
Number of garbage collections
Shown as garbage collection
runtime.node.gc.pause.by.type.max
(gauge)
Maximum garbage collection pause by type
Shown as nanosecond
runtime.node.gc.pause.by.type.min
(gauge)
Minimum garbage collection pause by type
Shown as nanosecond
runtime.node.gc.pause.by.type.avg
(gauge)
Average garbage collection pause by type
Shown as nanosecond
runtime.node.gc.pause.by.type.sum
(rate)
Total garbage collection pause by type
Shown as nanosecond
runtime.node.gc.pause.by.type.median
(gauge)
Median garbage collection pause by type
Shown as nanosecond
runtime.node.gc.pause.by.type.95percentile
(gauge)
95th percentile garbage collection pause by type
Shown as nanosecond
runtime.node.gc.pause.by.type.count
(rate)
Number of garbage collections by type
Shown as garbage collection
runtime.dotnet.cpu.system
(gauge)
The number of milliseconds executing in the kernel
Shown as millisecond
runtime.dotnet.cpu.user
(gauge)
The number of milliseconds executing outside the kernel
Shown as millisecond
runtime.dotnet.cpu.percent
(gauge)
The percentage of total CPU used by the application
Shown as percent
runtime.dotnet.mem.committed
(gauge)
Memory usage
Shown as byte
runtime.dotnet.threads.count
(gauge)
The number of threads
Shown as thread
runtime.dotnet.threads.workers_count
(gauge)
The number of workers in the threadpool (.NET Core 3.1+ only)
Shown as thread
runtime.dotnet.threads.contention_time
(gauge)
The cumulated time spent by threads waiting on a lock (.NET Core 3.1+ only)
Shown as millisecond
runtime.dotnet.threads.contention_count
(count)
The number of times a thread stopped to wait on a lock
runtime.dotnet.exceptions.count
(count)
The number of first-chance exceptions
Shown as exception
runtime.dotnet.gc.size.gen0
(gauge)
The size of the gen 0 heap
Shown as byte
runtime.dotnet.gc.size.gen1
(gauge)
The size of the gen 1 heap
Shown as byte
runtime.dotnet.gc.size.gen2
(gauge)
The size of the gen 2 heap
Shown as byte
runtime.dotnet.gc.size.loh
(gauge)
The size of the large object heap
Shown as byte
runtime.dotnet.gc.memory_load
(gauge)
The percentage of the total memory used by the process. The GC changes its behavior when this value gets above 85. (.NET Core 3.1+ only)
Shown as percent
runtime.dotnet.gc.pause_time
(gauge)
The amount of time the GC paused the application threads (.NET Core 3.1+ only)
Shown as millisecond
runtime.dotnet.gc.count.gen0
(count)
The number of gen 0 garbage collections
Shown as garbage collection
runtime.dotnet.gc.count.gen1
(count)
The number of gen 1 garbage collections
Shown as garbage collection
runtime.dotnet.gc.count.gen2
(count)
The number of gen 2 garbage collections
Shown as garbage collection
runtime.dotnet.aspnetcore.requests.total
(gauge)
The total number of HTTP requests received by the server (.NET Core 3.1+ only)
Shown as request
runtime.dotnet.aspnetcore.requests.failed
(gauge)
The number of failed HTTP requests received by the server (.NET Core 3.1+ only)
Shown as request
runtime.dotnet.aspnetcore.requests.current
(gauge)
The total number of HTTP requests that have started but not yet stopped (.NET Core 3.1+ only)
Shown as request
runtime.dotnet.aspnetcore.requests.queue_length
(gauge)
The current length of the server HTTP request queue (.NET 5+ only)
Shown as request
runtime.dotnet.aspnetcore.connections.total
(gauge)
The total number of HTTP connections established to the server (.NET 5+ only)
Shown as connection
runtime.dotnet.aspnetcore.connections.current
(gauge)
The current number of active HTTP connections to the server (.NET 5+ only)
Shown as connection
runtime.dotnet.aspnetcore.connections.queue_length
(gauge)
The current length of the HTTP server connection queue (.NET 5+ only)
Shown as connection

Referencias adicionales