Viewing All ModelArts Monitoring Metrics on the AOM Console

ModelArts periodically collects the usage of key metrics (such as GPUs, NPUs, CPUs, and memory) of each node in a resource pool as well as the usage of key metrics of the development environment, training jobs, and inference services, and reports the data to AOM. You can view the information on AOM.

1. Log in to the console and search for AOM to go to the AOM console.
2. Choose Monitoring > Metric Monitoring. On the Metric Monitoring page that is displayed, click Add Metric.

   

3. Add metrics and click Confirm.

   

   • Add By: Select Dimension.
   • Metric Name: Click Custom Metrics. Select the desired ones for query. For details, see Table 1, Table 2, and Table 3.
   • Dimension: Enter the tag for filtering the metric. For details, see Table 4. The following shows an example.

   

4. View the metrics.

   

   Table 1 Container metrics

   Category	Name	Metric	Description	Unit	Value Range
   CPU	CPU Usage	ma_container_cpu_util	CPU usage of a measured object	%	0%–100%
   	Used CPU Cores	ma_container_cpu_used_core	Number of CPU cores used by a measured object	Cores	≥ 0
   	Total CPU Cores	ma_container_cpu_limit_core	Total number of CPU cores that have been applied for a measured object	Cores	≥ 1
   Memory	Total Physical Memory	ma_container_memory_capacity_megabytes	Total physical memory that has been applied for a measured object	MB	≥ 0
   	Physical Memory Usage	ma_container_memory_util	Percentage of the used physical memory to the total physical memory	%	0%–100%
   	Used Physical Memory	ma_container_memory_used_megabytes	Physical memory that has been used by a measured object (container_memory_working_set_bytes in the current working set) (Memory usage in a working set = Active anonymous page and cache, and file-baked page ≤ container_memory_usage_bytes)	MB	≥ 0
   Storage	Disk Read Rate	ma_container_disk_read_kilobytes	Volume of data read from a disk per second	KB/s	≥ 0
   	Disk Write Rate	ma_container_disk_write_kilobytes	Volume of data written into a disk per second	KB/s	≥ 0
   GPU memory	Total GPU Memory	ma_container_gpu_mem_total_megabytes	Total GPU memory of a training job	MB	> 0
   	GPU Memory Usage	ma_container_gpu_mem_util	Percentage of the used GPU memory to the total GPU memory	%	0%–100%
   	Used GPU Memory	ma_container_gpu_mem_used_megabytes	GPU memory used by a measured object	MB	≥ 0
   GPU	GPU Usage	ma_container_gpu_util	GPU usage of a measured object	%	0%–100%
   	GPU Memory Bandwidth Usage	ma_container_gpu_mem_copy_util	GPU memory bandwidth usage of a measured object For example, the maximum memory bandwidth of GP Vnt1 is 900 GB/s. If the current memory bandwidth is 450 GB/s, the memory bandwidth usage is 50%.	%	0%–100%
   	GPU Encoder Usage	ma_container_gpu_enc_util	GPU encoder usage of a measured object	%	%
   	GPU Decoder Usage	ma_container_gpu_dec_util	GPU decoder usage of a measured object	%	%
   	GPU Temperature	DCGM_FI_DEV_GPU_TEMP	GPU temperature	°C	Natural number
   	GPU Power	DCGM_FI_DEV_POWER_USAGE	GPU power	Watt (W)	> 0
   	GPU Memory Temperature	DCGM_FI_DEV_MEMORY_TEMP	GPU memory temperature	°C	Natural number
   Network I/O	Downlink Rate (BPS)	ma_container_network_receive_bytes	Inbound traffic rate of a measured object	Bytes/s	≥ 0
   	Downlink Rate (PPS)	ma_container_network_receive_packets	Number of data packets received by a NIC per second	Packets/s	≥ 0
   	Downlink Error Rate	ma_container_network_receive_error_packets	Number of error packets received by a NIC per second	Packets/s	≥ 0
   	Uplink Rate (BPS)	ma_container_network_transmit_bytes	Outbound traffic rate of a measured object	Bytes/s	≥ 0
   	Uplink Error Rate	ma_container_network_transmit_error_packets	Number of error packets sent by a NIC per second	Packets/s	≥ 0
   	Uplink Rate (PPS)	ma_container_network_transmit_packets	Number of data packets sent by a NIC per second	Packets/s	≥ 0
   Notebook service metrics	Notebook Cache Directory Size	ma_container_notebook_cache_dir_size_bytes	A high-speed local disk is attached to the /cache directory for GPU notebook instances. This metric indicates the total size of the directory.	Bytes	≥ 0
   	Notebook Cache Directory Utilization	ma_container_notebook_cache_dir_util	A high-speed local disk is attached to the /cache directory for GPU notebook instances. This metric indicates the utilization of the directory.	%	0%–100%

   Table 2 Node metrics (collected only in dedicated resource pools)

   Category	Name	Metric	Description	Unit	Value Range
   CPU	Total CPU Cores	ma_node_cpu_limit_core	Total number of CPU cores that have been applied for a measured object	Cores	≥ 1
   	Used CPU Cores	ma_node_cpu_used_core	Number of CPU cores used by a measured object	Cores	≥ 0
   	CPU Usage	ma_node_cpu_util	CPU usage of a measured object	%	0%–100%
   	CPU I/O Wait Time	ma_node_cpu_iowait_counter	Disk I/O wait time accumulated since system startup	jiffies	≥ 0
   Memory	Physical Memory Usage	ma_node_memory_util	Percentage of the used physical memory to the total physical memory	%	0%–100%
   	Total Physical Memory	ma_node_memory_total_megabytes	Total physical memory that has been applied for a measured object	MB	≥ 0
   Network I/O	Downlink Rate (BPS)	ma_node_network_receive_rate_bytes_seconds	Inbound traffic rate of a measured object	Bytes/s	≥ 0
   	Uplink Rate (BPS)	ma_node_network_transmit_rate_bytes_seconds	Outbound traffic rate of a measured object	Bytes/s	≥ 0
   Storage	Disk Read Rate	ma_node_disk_read_rate_kilobytes_seconds	Volume of data read from a disk per second (Only data disks used by containers are collected.)	KB/s	≥ 0
   	Disk Write Rate	ma_node_disk_write_rate_kilobytes_seconds	Volume of data written into a disk per second (Only data disks used by containers are collected.)	KB/s	≥ 0
   	Total Cache	ma_node_cache_space_capacity_megabytes	Total cache of the Kubernetes space	MB	≥ 0
   	Used Cache	ma_node_cache_space_used_capacity_megabytes	Used cache of the Kubernetes space	MB	≥ 0
   	Total Container Space	ma_node_container_space_capacity_megabytes	Total container space	MB	≥ 0
   	Used Container Space	ma_node_container_space_used_capacity_megabytes	Used container space	MB	≥ 0
   	Disk Information	ma_node_disk_info	Basic disk information	N/A	≥ 0
   	Total Reads	ma_node_disk_reads_completed_total	Total number of successful reads	N/A	≥ 0
   	Merged Reads	ma_node_disk_reads_merged_total	Number of merged reads	N/A	≥ 0
   	Bytes Read	ma_node_disk_read_bytes_total	Total number of bytes that are successfully read	Bytes	≥ 0
   	Read Time Spent	ma_node_disk_read_time_seconds_total	Time spent on all reads	Seconds	≥ 0
   	Total Writes	ma_node_disk_writes_completed_total	Total number of successful writes	N/A	≥ 0
   	Merged Writes	ma_node_disk_writes_merged_total	Number of merged writes	N/A	≥ 0
   	Written Bytes	ma_node_disk_written_bytes_total	Total number of bytes that are successfully written	Bytes	≥ 0
   	Write Time Spent	ma_node_disk_write_time_seconds_total	Time spent on all write operations	Seconds	≥ 0
   	Ongoing I/Os	ma_node_disk_io_now	Number of ongoing I/Os	N/A	≥ 0
   	I/O Execution Duration	ma_node_disk_io_time_seconds_total	Time spent on executing I/Os	Seconds	≥ 0
   	I/O Execution Weighted Time	ma_node_disk_io_time_weighted_seconds_tota	The weighted number of seconds spent doing I/Os	Seconds	≥ 0
   GPU	GPU Usage	ma_node_gpu_util	GPU usage of a measured object	%	0%–100%
   	Total GPU Memory	ma_node_gpu_mem_total_megabytes	Total GPU memory of a measured object	MB	> 0
   	GPU Memory Usage	ma_node_gpu_mem_util	Percentage of the used GPU memory to the total GPU memory	%	0%–100%
   	Used GPU Memory	ma_node_gpu_mem_used_megabytes	GPU memory used by a measured object	MB	≥ 0
   	Tasks on a Shared GPU	node_gpu_share_job_count	Number of tasks running on a shared GPU	Number	≥ 0
   	GPU Temperature	DCGM_FI_DEV_GPU_TEMP	GPU temperature	°C	Natural number
   	GPU Power	DCGM_FI_DEV_POWER_USAGE	GPU power	Watt (W)	> 0
   	GPU Memory Temperature	DCGM_FI_DEV_MEMORY_TEMP	GPU memory temperature	°C	Natural number
   InfiniBand or RoCE network	Total Amount of Data Received by a NIC	ma_node_infiniband_port_received_data_bytes_total	The total number of data octets, divided by 4, (counting in double words, 32 bits), received on all VLs from the port.	(counting in double words, 32 bits)	≥ 0
   	Total Amount of Data Sent by a NIC	ma_node_infiniband_port_transmitted_data_bytes_total	The total number of data octets, divided by 4, (counting in double words, 32 bits), transmitted on all VLs from the port.	(counting in double words, 32 bits)	≥ 0
   NFS mounting status	NFS Getattr Congestion Time	ma_node_mountstats_getattr_backlog_wait	Getattr is an NFS operation that retrieves the attributes of a file or directory, such as size, permissions, owner, etc. Backlog wait is the time that the NFS requests have to wait in the backlog queue before being sent to the NFS server. It indicates the congestion on the NFS client side. A high backlog wait can cause poor NFS performance and slow system response times.	ms	≥ 0
   	NFS Getattr Round Trip Time	ma_node_mountstats_getattr_rtt	Getattr is an NFS operation that retrieves the attributes of a file or directory, such as size, permissions, owner, etc. RTT stands for Round Trip Time and it is the time from when the kernel RPC client sends the RPC request to the time it receives the reply34. RTT includes network transit time and server execution time. RTT is a good measurement for NFS latency. A high RTT can indicate network or server issues.	ms	≥ 0
   	NFS Access Congestion Time	ma_node_mountstats_access_backlog_wait	Access is an NFS operation that checks the access permissions of a file or directory for a given user. Backlog wait is the time that the NFS requests have to wait in the backlog queue before being sent to the NFS server. It indicates the congestion on the NFS client side. A high backlog wait can cause poor NFS performance and slow system response times.	ms	≥ 0
   	NFS Access Round Trip Time	ma_node_mountstats_access_rtt	Access is an NFS operation that checks the access permissions of a file or directory for a given user. RTT stands for Round Trip Time and it is the time from when the kernel RPC client sends the RPC request to the time it receives the reply34. RTT includes network transit time and server execution time. RTT is a good measurement for NFS latency. A high RTT can indicate network or server issues.	ms	≥ 0
   	NFS Lookup Congestion Time	ma_node_mountstats_lookup_backlog_wait	Lookup is an NFS operation that resolves a file name in a directory to a file handle. Backlog wait is the time that the NFS requests have to wait in the backlog queue before being sent to the NFS server. It indicates the congestion on the NFS client side. A high backlog wait can cause poor NFS performance and slow system response times.	ms	≥ 0
   	NFS Lookup Round Trip Time	ma_node_mountstats_lookup_rtt	Lookup is an NFS operation that resolves a file name in a directory to a file handle. RTT stands for Round Trip Time and it is the time from when the kernel RPC client sends the RPC request to the time it receives the reply34. RTT includes network transit time and server execution time. RTT is a good measurement for NFS latency. A high RTT can indicate network or server issues.	ms	≥ 0
   	NFS Read Congestion Time	ma_node_mountstats_read_backlog_wait	Read is an NFS operation that reads data from a file. Backlog wait is the time that the NFS requests have to wait in the backlog queue before being sent to the NFS server. It indicates the congestion on the NFS client side. A high backlog wait can cause poor NFS performance and slow system response times.	ms	≥ 0
   	NFS Read Round Trip Time	ma_node_mountstats_read_rtt	Read is an NFS operation that reads data from a file. RTT stands for Round Trip Time and it is the time from when the kernel RPC client sends the RPC request to the time it receives the reply34. RTT includes network transit time and server execution time. RTT is a good measurement for NFS latency. A high RTT can indicate network or server issues.	ms	≥ 0
   	NFS Write Congestion Time	ma_node_mountstats_write_backlog_wait	Write is an NFS operation that writes data to a file. Backlog wait is the time that the NFS requests have to wait in the backlog queue before being sent to the NFS server. It indicates the congestion on the NFS client side. A high backlog wait can cause poor NFS performance and slow system response times.	ms	≥ 0
   	NFS Write Round Trip Time	ma_node_mountstats_write_rtt	Write is an NFS operation that writes data to a file. RTT stands for Round Trip Time and it is the time from when the kernel RPC client sends the RPC request to the time it receives the reply34. RTT includes network transit time and server execution time. RTT is a good measurement for NFS latency. A high RTT can indicate network or server issues.	ms	≥ 0

   Table 3 Diagnosis (InfiniBand, collected only in dedicated resource pools)

   Category	Name	Metric	Description	Unit	Value Range
   InfiniBand or RoCE network	PortXmitData	infiniband_port_xmit_data_total	The total number of data octets, divided by 4, (counting in double words, 32 bits), transmitted on all VLs from the port.	Total count	Natural number
   	PortRcvData	infiniband_port_rcv_data_total	The total number of data octets, divided by 4, (counting in double words, 32 bits), received on all VLs from the port.	Total count	Natural number
   	SymbolErrorCounter	infiniband_symbol_error_counter_total	Total number of minor link errors detected on one or more physical lanes.	Total count	Natural number
   	LinkErrorRecoveryCounter	infiniband_link_error_recovery_counter_total	Total number of times the Port Training state machine has successfully completed the link error recovery process.	Total count	Natural number
   	PortRcvErrors	infiniband_port_rcv_errors_total	Total number of packets containing errors that were received on the port including: Local physical errors (ICRC, VCRC, LPCRC, and all physical errors that cause entry into the BAD PACKET or BAD PACKET DISCARD states of the packet receiver state machine) Malformed data packet errors (LVer, length, VL) Malformed link packet errors (operand, length, VL) Packets discarded due to buffer overrun (overflow)	Total count	Natural number
   	LocalLinkIntegrityErrors	infiniband_local_link_integrity_errors_total	This counter indicates the number of retries initiated by a link transfer layer receiver.	Total count	Natural number
   	PortRcvRemotePhysicalErrors	infiniband_port_rcv_remote_physical_errors_total	Total number of packets marked with the EBP delimiter received on the port.	Total count	Natural number
   	PortRcvSwitchRelayErrors	infiniband_port_rcv_switch_relay_errors_total	Total number of packets received on the port that were discarded when they could not be forwarded by the switch relay for the following reasons: DLID mapping VL mapping Looping (output port = input port)	Total count	Natural number
   	PortXmitWait	infiniband_port_transmit_wait_total	The number of ticks during which the port had data to transmit but no data was sent during the entire tick (either because of insufficient credits or because of lack of arbitration).	Total count	Natural number
   	PortXmitDiscards	infiniband_port_xmit_discards_total	Total number of outbound packets discarded by the port because the port is down or congested.	Total count	Natural number

   Table 4 Metric names

   Classification	Metric	Description
   Container metrics	modelarts_service	Service to which a container belongs, which can be notebook, train, or infer
   	instance_name	Name of the pod to which the container belongs
   	service_id	Instance or job ID displayed on the page, for example, cf55829e-9bd3-48fa-8071-7ae870dae93a for a development environment 9f322d5a-b1d2-4370-94df-5a87de27d36e for a training job
   	node_ip	IP address of the node to which the container belongs
   	container_id	Container ID
   	cid	Cluster ID
   	container_name	Name of the container
   	project_id	Project ID of the account to which the user belongs
   	user_id	User ID of the account to which the user who submits the job belongs
   	pool_id	ID of a resource pool corresponding to a physical dedicated resource pool
   	pool_name	Name of a resource pool corresponding to a physical dedicated resource pool
   	logical_pool_id	ID of a logical subpool
   	logical_pool_name	Name of a logical subpool
   	gpu_uuid	UUID of the GPU used by the container
   	gpu_index	Index of the GPU used by the container
   	gpu_type	Type of the GPU used by the container
   	account_name	Account name of the creator of a training, inference, or development environment task
   	user_name	Username of the creator of a training, inference, or development environment task
   	task_creation_time	Time when a training, inference, or development environment task is created
   	task_name	Name of a training, inference, or development environment task
   	task_spec_code	Specifications of a training, inference, or development environment task
   	cluster_name	CCE cluster name
   Node metrics	cid	ID of the CCE cluster to which the node belongs
   	node_ip	IP address of the node
   	host_name	Hostname of a node
   	pool_id	ID of a resource pool corresponding to a physical dedicated resource pool
   	project_id	Project ID of the user in a physical dedicated resource pool
   	gpu_uuid	UUID of a node GPU
   	gpu_index	Index of a node GPU
   	gpu_type	Type of a node GPU
   	device_name	Device name of an InfiniBand or RoCE network NIC
   	port	Port number of the InfiniBand NIC
   	physical_state	Status of each port on the InfiniBand NIC
   	firmware_version	Firmware version of the InfiniBand NIC
   	filesystem	NFS-mounted file system
   	mount_point	NFS mount point
   Diagnos	cid	ID of the CCE cluster to which the node with the GPU equipped belongs
   	node_ip	IP address of the node where the GPU resides
   	pool_id	ID of a resource pool corresponding to a physical dedicated resource pool
   	project_id	Project ID of the user in a physical dedicated resource pool
   	gpu_uuid	GPU UUID
   	gpu_index	Index of a node GPU
   	gpu_type	Type of a node GPU
   	device_name	Name of a network device or disk device
   	port	Port number of the InfiniBand NIC
   	physical_state	Status of each port on the InfiniBand NIC
   	firmware_version	Firmware version of the InfiniBand NIC