Nvidia NIM インテグレーションのメトリクス

Nvidia NIM の監視に使う Datadog の公式インテグレーションです。収集するメトリクスは 34 件あります。

公式の紹介文 (英語)

NVIDIA NIM integration with Datadog enables real-time GPU observability by collecting Prometheus metrics for monitoring.

種別の内訳

  • count (集計間隔内の発生回数): 24 件
  • gauge (その時点の値): 10 件

メトリクスの一覧

説明は公式の定義の英文をそのまま載せています。

メトリクス種別単位
nvidia_nim.e2e_request_latency.seconds.bucketThe observations of end to end request latency bucketed by seconds.count-
nvidia_nim.e2e_request_latency.seconds.countThe total number of observations of end to end request latency.count-
nvidia_nim.e2e_request_latency.seconds.sumThe sum of end to end request latency in seconds.countsecond
nvidia_nim.generation_tokens.countNumber of generation tokens processed.counttoken
nvidia_nim.gpu_cache_usage_percentGPU KV-cache usage. 1 means 100 percent usage.gaugefraction
nvidia_nim.num_request.maxThe max number of concurrently running requests.gaugerequest
nvidia_nim.num_requests.runningNumber of requests currently running on GPU.gaugerequest
nvidia_nim.num_requests.waitingNumber of requests waiting.gaugerequest
nvidia_nim.process.cpu_seconds.countTotal user and system CPU time spent in seconds.countsecond
nvidia_nim.process.max_fdsMaximum number of open file descriptors.gaugefile
nvidia_nim.process.open_fdsNumber of open file descriptors.gaugefile
nvidia_nim.process.resident_memory_bytesResident memory size in bytes.gaugebyte
nvidia_nim.process.start_time_secondsTime in seconds since process started.gaugesecond
nvidia_nim.process.virtual_memory_bytesVirtual memory size in bytes.gaugebyte
nvidia_nim.prompt_tokens.countNumber of prefill tokens processed.counttoken
nvidia_nim.python.gc.collections.countNumber of times this generation was collected.count-
nvidia_nim.python.gc.objects.collected.countObjects collected during GC.count-
nvidia_nim.python.gc.objects.uncollectable.countUncollectable objects found during GC.count-
nvidia_nim.python.infoPython platform information.gauge-
nvidia_nim.request.failure.countThe count of failed requests.countrequest
nvidia_nim.request.finish.countThe count of finished requests.countrequest
nvidia_nim.request.generation_tokens.bucketNumber of generation tokens processed.count-
nvidia_nim.request.generation_tokens.countNumber of generation tokens processed.count-
nvidia_nim.request.generation_tokens.sumNumber of generation tokens processed.counttoken
nvidia_nim.request.prompt_tokens.bucketNumber of prefill tokens processed.count-
nvidia_nim.request.prompt_tokens.countNumber of prefill tokens processed.count-
nvidia_nim.request.prompt_tokens.sumNumber of prefill tokens processed.counttoken
nvidia_nim.request.success.countCount of successfully processed requests.count-
nvidia_nim.time_per_output_token.seconds.bucketThe observations of time per output token bucketed by seconds.count-
nvidia_nim.time_per_output_token.seconds.countThe total number of observations of time per output token.count-
nvidia_nim.time_per_output_token.seconds.sumThe sum of time per output token in seconds.countsecond
nvidia_nim.time_to_first_token.seconds.bucketThe observations of time to first token bucketed by seconds.count-
nvidia_nim.time_to_first_token.seconds.countThe total number of observations of time to first token.count-
nvidia_nim.time_to_first_token.seconds.sumThe sum of time to first token in seconds.countsecond

公式ドキュメント

Nvidia NIM インテグレーションの公式ドキュメント

メトリクスの名前と説明は Datadog の公式インテグレーションの定義 (Copyright Datadog, Inc.・BSD-3-Clause) を英文のまま載せています。利用条件の全文は サイトについてにあります。