Metrics API

Metrics API is a http API that is used to fetch metrics in the prometheus format. It is listening on port 8082 and only accessible from localhost by default. To change the default setting, see TorchServe Configuration. The metrics endpoint is enabled by default and returns Prometheus formatted metrics when metrics_mode configuration is set to prometheus. You can query metrics using curl requests or point a Prometheus Server to the endpoint and use Grafana for dashboards.

By default these APIs are enabled however it can be disabled by setting enable_metrics_api=false in torchserve config.properties file. For details refer Torchserve config docs.

Note This is not to be confused with torch serve’s custom metrics API. The custom metrics API is used to collect custom backend metrics based on the configured metrics_mode (log or prometheus). More information on this api can be found here.

curl http://127.0.0.1:8082/metrics

# HELP Requests5XX Torchserve prometheus counter metric with unit: Count
# TYPE Requests5XX counter
# HELP DiskUsage Torchserve prometheus gauge metric with unit: Gigabytes
# TYPE DiskUsage gauge
DiskUsage{Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 20.054508209228516
# HELP GPUUtilization Torchserve prometheus gauge metric with unit: Percent
# TYPE GPUUtilization gauge
# HELP PredictionTime Torchserve prometheus gauge metric with unit: ms
# TYPE PredictionTime gauge
PredictionTime{ModelName="resnet18",Level="Model",Hostname="88665a372f4b.ant.amazon.com",} 83.13
# HELP WorkerLoadTime Torchserve prometheus gauge metric with unit: Milliseconds
# TYPE WorkerLoadTime gauge
WorkerLoadTime{WorkerName="W-9000-resnet18_1.0",Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 4593.0
WorkerLoadTime{WorkerName="W-9001-resnet18_1.0",Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 4592.0
# HELP MemoryAvailable Torchserve prometheus gauge metric with unit: Megabytes
# TYPE MemoryAvailable gauge
MemoryAvailable{Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 5829.7421875
# HELP GPUMemoryUsed Torchserve prometheus gauge metric with unit: Megabytes
# TYPE GPUMemoryUsed gauge
# HELP ts_inference_requests_total Torchserve prometheus counter metric with unit: Count
# TYPE ts_inference_requests_total counter
ts_inference_requests_total{model_name="resnet18",model_version="default",hostname="88665a372f4b.ant.amazon.com",} 3.0
# HELP GPUMemoryUtilization Torchserve prometheus gauge metric with unit: Percent
# TYPE GPUMemoryUtilization gauge
# HELP HandlerTime Torchserve prometheus gauge metric with unit: ms
# TYPE HandlerTime gauge
HandlerTime{ModelName="resnet18",Level="Model",Hostname="88665a372f4b.ant.amazon.com",} 82.93
# HELP ts_inference_latency_microseconds Torchserve prometheus counter metric with unit: Microseconds
# TYPE ts_inference_latency_microseconds counter
ts_inference_latency_microseconds{model_name="resnet18",model_version="default",hostname="88665a372f4b.ant.amazon.com",} 290371.129
# HELP CPUUtilization Torchserve prometheus gauge metric with unit: Percent
# TYPE CPUUtilization gauge
CPUUtilization{Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 0.0
# HELP MemoryUsed Torchserve prometheus gauge metric with unit: Megabytes
# TYPE MemoryUsed gauge
MemoryUsed{Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 8245.62109375
# HELP QueueTime Torchserve prometheus gauge metric with unit: Milliseconds
# TYPE QueueTime gauge
QueueTime{Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 0.0
# HELP ts_queue_latency_microseconds Torchserve prometheus counter metric with unit: Microseconds
# TYPE ts_queue_latency_microseconds counter
ts_queue_latency_microseconds{model_name="resnet18",model_version="default",hostname="88665a372f4b.ant.amazon.com",} 365.21
# HELP DiskUtilization Torchserve prometheus gauge metric with unit: Percent
# TYPE DiskUtilization gauge
DiskUtilization{Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 5.8
# HELP Requests2XX Torchserve prometheus counter metric with unit: Count
# TYPE Requests2XX counter
Requests2XX{Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 8.0
# HELP Requests4XX Torchserve prometheus counter metric with unit: Count
# TYPE Requests4XX counter
# HELP WorkerThreadTime Torchserve prometheus gauge metric with unit: Milliseconds
# TYPE WorkerThreadTime gauge
WorkerThreadTime{Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 1.0
# HELP DiskAvailable Torchserve prometheus gauge metric with unit: Gigabytes
# TYPE DiskAvailable gauge
DiskAvailable{Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 325.05113983154297
# HELP MemoryUtilization Torchserve prometheus gauge metric with unit: Percent
# TYPE MemoryUtilization gauge
MemoryUtilization{Level="Host",Hostname="88665a372f4b.ant.amazon.com",} 64.4

curl "http://127.0.0.1:8082/metrics?name[]=ts_inference_latency_microseconds&name[]=ts_queue_latency_microseconds" --globoff

# HELP ts_queue_latency_microseconds Torchserve prometheus counter metric with unit: Microseconds
# TYPE ts_queue_latency_microseconds counter
ts_queue_latency_microseconds{model_name="resnet18",model_version="default",hostname="88665a372f4b.ant.amazon.com",} 365.21
# HELP ts_inference_latency_microseconds Torchserve prometheus counter metric with unit: Microseconds
# TYPE ts_inference_latency_microseconds counter
ts_inference_latency_microseconds{model_name="resnet18",model_version="default",hostname="88665a372f4b.ant.amazon.com",} 290371.129

Prometheus server

To view these metrics on a Prometheus server, download and install using the instructions here. Create a minimal prometheus.yml config file as below and run ./prometheus --config.file=prometheus.yml.

global:
  scrape_interval:     15s
  evaluation_interval: 15s

scrape_configs:
  - job_name: 'prometheus'
    static_configs:
    - targets: ['localhost:9090']
  - job_name: 'torchserve'
    static_configs:
    - targets: ['localhost:8082'] #TorchServe metrics endpoint

Navigate to http://localhost:9090/ on a browser to execute queries and create graphs

Grafana

Once you have the Torchserve and Prometheus servers running, you can further setup Grafana, point it to Prometheus server and navigate to http://localhost:3000/ to create dashboards and graphs.

You can use command given below to start Grafana - sudo systemctl daemon-reload && sudo systemctl enable grafana-server && sudo systemctl start grafana-server