This module collects worker resources from TorchServe periodically and export as Prometheus format. An exported data could be collected by Prometheus server and used for monitoring TorchServe model worker if you make up dashboard on Grafana.
Metrics:
ts_worker_cpu_usage: TorchServe model worker CPU usagets_worker_memory_usage: TorchServe model worker memory usagets_worker_memory_mib: TorchServe model worker memory mebi-bytes
- Get each of model worker information from TorchServe management API. This information includes PID, GPU usage and so on.
- Get additional information that not included in information (e.g. CPU percentage) from management API and append them
to previously gathered one. This is acquired by running process resource monitor command (e.g.
top) to TorchServe server pod with K8s client. - Expose data as Prometheus metrics.
This repository contains Kubernetes resources to deploy this service on Kubernetes cluster.
Deployment could be done with Helm:
helm install ts-metric-exporter -n metric-exporter chart \
--set metric_exporter.namespace=metric-exporter \
--set torchserve.namespace=ns-ml-serve-c8cdbd7c \
--set torchserve.address=torchserve.ml-serve.svc.cluster.localDatasource Prometheus and Loki is required to get a TorchServe worker resource and request log by query. Each of
service need to be installed and set on Datasource from Grafana configuration if not set before.
A sample grafana dashboard file is located at grafana/torchserve_metric_dashboard.json.