Metrics¶

dstack automatically tracks essential metrics, which you can access via the CLI and UI. You can also configure the dstack server to export metrics to Prometheus—this is required to access advanced metrics such as those from DCGM.

UI¶

To access metrics via the UI, open the page of the corresponding run or job and switch to the Metrics tab:

This tab displays key CPU, memory, and GPU metrics collected during the last hour of the run or job.

CLI¶

As an alternative to the UI, you can track real-time essential metrics via the CLI. The dstack metrics command displays the most recently tracked CPU, memory, and GPU metrics.

dstack metrics gentle-mayfly-1

 NAME             STATUS  CPU  MEMORY          GPU
 gentle-mayfly-1  done    0%   16.27GB/2000GB  gpu=0 mem=72.48GB/80GB util=0%
                                               gpu=1 mem=64.99GB/80GB util=0%
                                               gpu=2 mem=580MB/80GB util=0%
                                               gpu=3 mem=4MB/80GB util=0%
                                               gpu=4 mem=4MB/80GB util=0%
                                               gpu=5 mem=4MB/80GB util=0%
                                               gpu=6 mem=4MB/80GB util=0%
                                               gpu=7 mem=292MB/80GB util=0%

Prometheus¶

To enable exporting metrics to Prometheus, set the DSTACK_ENABLE_PROMETHEUS_METRICS environment variable and configure Prometheus to scrape metrics from <dstack server URL>/metrics.

In addition to the essential metrics available via the CLI and UI, dstack exports additional metrics to Prometheus, including data on fleets, runs, jobs, and DCGM metrics.

NVIDIA DCGM

NVIDIA DCGM metrics are automatically collected for aws, azure, gcp, and oci backends, as well as for SSH fleets.

To ensure NVIDIA DCGM metrics are collected from SSH fleets, ensure the datacenter-gpu-manager-4-core, datacenter-gpu-manager-4-proprietary, and datacenter-gpu-manager-exporter packages are installed on the hosts.

Fleets¶

Fleet metrics include metrics for each instance within a fleet. This includes information such as the instance's running time, price, GPU name, and more.

MetricsLabels

Name	Type	Description	Examples
`dstack_instance_duration_seconds_total`	counter	Total instance runtime in seconds	`1123763.22`
`dstack_instance_price_dollars_per_hour`	gauge	Instance price, USD/hour	`16.0`
`dstack_instance_gpu_count`	gauge	Instance GPU count	`4.0`, `0.0`

Name	Type	Description	Examples
`dstack_project_name`	string	Project name	`main`
`dstack_fleet_name`	string?	Fleet name	`my-fleet`
`dstack_fleet_id`	string?	Fleet ID	`51e837bf-fae9-4a37-ac9c-85c005606c22`
`dstack_instance_name`	string	Instance name	`my-fleet-0`
`dstack_instance_id`	string	Instance ID	`8c28c52c-2f94-4a19-8c06-12f1dfee4dd2`
`dstack_instance_type`	string?	Instance type	`g4dn.xlarge`
`dstack_backend`	string?	Backend	`aws`, `runpod`
`dstack_gpu`	string?	GPU name	`H100`

Runs¶

Run metrics include run counters for each user in each project.

MetricsLabels

Name	Type	Description	Examples
`dstack_run_count_total`	counter	The total number of runs	`537`
`dstack_run_count_terminated_total`	counter	The number of terminated runs	`118`
`dstack_run_count_failed_total`	counter	The number of failed runs	`27`
`dstack_run_count_done_total`	counter	The number of successful runs	`218`

Name	Type	Description	Examples
`dstack_project_name`	string	Project name	`main`
`dstack_user_name`	string	User name	`alice`

Jobs¶

A run consists of one or more jobs, each mapped to an individual container. For distributed workloads or auto-scalable services, a run spans multiple jobs.

Job metrics provide detailed insights into each job within a run, including execution time, cost, GPU model, DCGM telemetry, and more.

MetricsLabels

Name	Type	Description	Examples
`dstack_job_duration_seconds_total`	counter	Total job runtime in seconds	`520.37`
`dstack_job_price_dollars_per_hour`	gauge	Job instance price, USD/hour	`8.0`
`dstack_job_gpu_count`	gauge	Job GPU count	`2.0`, `0.0`
`dstack_job_cpu_count`	gauge	Job CPU count	`32.0`
`dstack_job_cpu_time_seconds_total`	counter	Total CPU time consumed by the job, seconds	`11.727975`
`dstack_job_memory_total_bytes`	gauge	Total memory allocated for the job, bytes	`4009754624.0`
`dstack_job_memory_usage_bytes`	gauge	Memory used by the job (including cache), bytes	`339017728.0`
`dstack_job_memory_working_set_bytes`	gauge	Memory used by the job (not including cache), bytes	`147251200.0`
`DCGM_FI_DEV_GPU_UTIL`	gauge	GPU utilization (in %)
`DCGM_FI_DEV_MEM_COPY_UTIL`	gauge	Memory utilization (in %)
`DCGM_FI_DEV_ENC_UTIL`	gauge	Encoder utilization (in %)
`DCGM_FI_DEV_DEC_UTIL`	gauge	Decoder utilization (in %)
`DCGM_FI_DEV_FB_FREE`	gauge	Framebuffer memory free (in MiB)
`DCGM_FI_DEV_FB_USED`	gauge	Framebuffer memory used (in MiB)
`DCGM_FI_PROF_GR_ENGINE_ACTIVE`	gauge	The ratio of cycles during which a graphics engine or compute engine remains active
`DCGM_FI_PROF_SM_ACTIVE`	gauge	The ratio of cycles an SM has at least 1 warp assigned
`DCGM_FI_PROF_SM_OCCUPANCY`	gauge	The ratio of number of warps resident on an SM
`DCGM_FI_PROF_PIPE_TENSOR_ACTIVE`	gauge	Ratio of cycles the tensor (HMMA) pipe is active
`DCGM_FI_PROF_PIPE_FP64_ACTIVE`	gauge	Ratio of cycles the fp64 pipes are active
`DCGM_FI_PROF_PIPE_FP32_ACTIVE`	gauge	Ratio of cycles the fp32 pipes are active
`DCGM_FI_PROF_PIPE_FP16_ACTIVE`	gauge	Ratio of cycles the fp16 pipes are active
`DCGM_FI_PROF_PIPE_INT_ACTIVE`	gauge	Ratio of cycles the integer pipe is active
`DCGM_FI_PROF_DRAM_ACTIVE`	gauge	Ratio of cycles the device memory interface is active sending or receiving data
`DCGM_FI_PROF_PCIE_TX_BYTES`	counter	The number of bytes of active PCIe tx (transmit) data including both header and payload
`DCGM_FI_PROF_PCIE_RX_BYTES`	counter	The number of bytes of active PCIe rx (read) data including both header and payload
`DCGM_FI_DEV_SM_CLOCK`	gauge	SM clock frequency (in MHz)
`DCGM_FI_DEV_MEM_CLOCK`	gauge	Memory clock frequency (in MHz)
`DCGM_FI_DEV_MEMORY_TEMP`	gauge	Memory temperature (in C)
`DCGM_FI_DEV_GPU_TEMP`	gauge	GPU temperature (in C)
`DCGM_FI_DEV_POWER_USAGE`	gauge	Power draw (in W)
`DCGM_FI_DEV_TOTAL_ENERGY_CONSUMPTION`	counter	Total energy consumption since boot (in mJ)
`DCGM_FI_DEV_PCIE_REPLAY_COUNTER`	counter	Total number of PCIe retries
`DCGM_FI_DEV_XID_ERRORS`	gauge	Value of the last XID error encountered
`DCGM_FI_DEV_POWER_VIOLATION`	counter	Throttling duration due to power constraints (in us)
`DCGM_FI_DEV_THERMAL_VIOLATION`	counter	Throttling duration due to thermal constraints (in us)
`DCGM_FI_DEV_SYNC_BOOST_VIOLATION`	counter	Throttling duration due to sync-boost constraints (in us)
`DCGM_FI_DEV_BOARD_LIMIT_VIOLATION`	counter	Throttling duration due to board limit constraints (in us)
`DCGM_FI_DEV_LOW_UTIL_VIOLATION`	counter	Throttling duration due to low utilization (in us)
`DCGM_FI_DEV_RELIABILITY_VIOLATION`	counter	Throttling duration due to reliability constraints (in us)
`DCGM_FI_DEV_ECC_SBE_VOL_TOTAL`	counter	Total number of single-bit volatile ECC errors
`DCGM_FI_DEV_ECC_DBE_VOL_TOTAL`	counter	Total number of double-bit volatile ECC errors
`DCGM_FI_DEV_ECC_SBE_AGG_TOTAL`	counter	Total number of single-bit persistent ECC errors
`DCGM_FI_DEV_ECC_DBE_AGG_TOTAL`	counter	Total number of double-bit persistent ECC errors
`DCGM_FI_DEV_RETIRED_SBE`	counter	Total number of retired pages due to single-bit errors
`DCGM_FI_DEV_RETIRED_DBE`	counter	Total number of retired pages due to double-bit errors
`DCGM_FI_DEV_RETIRED_PENDING`	counter	Total number of pages pending retirement
`DCGM_FI_DEV_UNCORRECTABLE_REMAPPED_ROWS`	counter	Number of remapped rows for uncorrectable errors
`DCGM_FI_DEV_CORRECTABLE_REMAPPED_ROWS`	counter	Number of remapped rows for correctable errors
`DCGM_FI_DEV_ROW_REMAP_FAILURE`	gauge	Whether remapping of rows has failed
`DCGM_FI_DEV_NVLINK_CRC_FLIT_ERROR_COUNT_TOTAL`	counter	Total number of NVLink flow-control CRC errors
`DCGM_FI_DEV_NVLINK_CRC_DATA_ERROR_COUNT_TOTAL`	counter	Total number of NVLink data CRC errors
`DCGM_FI_DEV_NVLINK_REPLAY_ERROR_COUNT_TOTAL`	counter	Total number of NVLink retries
`DCGM_FI_DEV_NVLINK_RECOVERY_ERROR_COUNT_TOTAL`	counter	Total number of NVLink recovery errors
`DCGM_FI_DEV_NVLINK_BANDWIDTH_TOTAL`	counter	Total number of NVLink bandwidth counters for all lanes
`DCGM_FI_DEV_NVLINK_BANDWIDTH_L0`	counter	The number of bytes of active NVLink rx or tx data including both header and payload
`DCGM_FI_PROF_NVLINK_RX_BYTES`	counter	The number of bytes of active PCIe rx (read) data including both header and payload
`DCGM_FI_PROF_NVLINK_TX_BYTES`	counter	The number of bytes of active NvLink tx (transmit) data including both header and payload

Label	Type	Description	Examples
`dstack_project_name`	string	Project name	`main`
`dstack_user_name`	string	User name	`alice`
`dstack_run_name`	string	Run name	`nccl-tests`
`dstack_run_id`	string	Run ID	`51e837bf-fae9-4a37-ac9c-85c005606c22`
`dstack_job_name`	string	Job name	`nccl-tests-0-0`
`dstack_job_id`	string	Job ID	`8c28c52c-2f94-4a19-8c06-12f1dfee4dd2`
`dstack_job_num`	integer	Job number	`0`
`dstack_replica_num`	integer	Replica number	`0`
`dstack_run_type`	string	Run configuration type	`task`, `dev-environment`
`dstack_backend`	string	Backend	`aws`, `runpod`
`dstack_gpu`	string?	GPU name	`H100`

Server health metrics¶

These are operational metrics to monitor the health of the dstack server. For now, these only include HTTP metrics, but more will be added later.

MetricsLabels

Name	Type	Description	Examples
`dstack_server_requests_total`	counter	Total number of HTTP requests	`100.0`
`dstack_server_request_duration_seconds`	histogram	HTTP request duration in seconds	`1.0`

Name	Type	Description	Examples
`method`	string	HTTP method	`POST`
`endpoint`	string	Endpoint path	`/api/project/main/repos/get`
`http_status`	string	HTTP status code	`200`
`project_name`	string?	Project name	`main`