Datastore Metrics

Capacity metrics can be calculated for datastore objects. See Capacity Analytics Generated Metrics.

Capacity Metrics for Datastores

Capacity metrics provide information about datastore capacity.


Metric Name	Description
Capacity\|Available Space (GB)	This metric shows the amount of free space that a datastore has available. Use this metric to know how much storage space is unused on the datastore. Try to avoid having too little free disk space in order to accommodate unexpected storage growth on the datastore. The exact size of the datastore is based on company policy. Key: capacity\|available_space
Capacity\|Provisioned (GB)	This metric shows the amount of storage that was allocated to the virtual machines. Use this metric to know how much storage space is being used on the datastore. Check the metric trend to identify spikes or abnormal growth. Key: capacity\|provisioned
Capacity\|Total Capacity (GB)	This metric shows the overall size of the datastore. Use this metric to know the total capacity of the datastore. Typically the size of the datastore should not be too small. VMFS datastore size has grown over the years as virtualization matures and larger virtual machines are now onboard. Ensure that the size can handle enough virtual machines to avoid datastore sprawl. A best practice is to use 5 TB for VMFS and more for vSAN. Key: capacity\|total_capacity
Capacity\|Used Space (GB)	This metric shows the amount of storage that is being used on the datastore. Key: capacity\|used_space
Capacity\|Workload (%)	Capacity workload. Key: capacity\|workload
Capacity\|Uncommitted Space (GB)	Uncommitted space in gigabytes. Key: capacity\|uncommitted
Capacity\|Total Provisioned Consumer Space	Total Provisioned Consumer Space. Key: capacity\|consumer_provisioned
Capacity\|Used Space (%)	This metric shows the amount of storage that is being used on the datastore. Use this metric to know the percentage of storage space being used on the datastore. When using this metric, verify that you have at least 20% of free storage. Less than this, and you might experience problems when a snapshot is not deleted. If you have more than 50% free storage space, you are not utilizing your storage in the best possible way. Key: capacity\|usedSpacePct

Device Metrics for Datastores

Device metrics provide information about device performance.


Metric Name	Description
Devices\|Bus Resets	This metric shows the number of bus resets in the performance interval. Key: devices\|busResets_summation
Devices\|Commands Aborted	This metric shows the number of disk commands canceled in the performance interval. Key: devices\|commandsAborted_summation
Devices\|Commands Issued	This metric shows the number of disk commands issued in the performance interval. Key: devices\|commands_summation
Devices\|Read Latency (ms)	This metric shows the average time taken for a read from the perspective of a guest operating system. This metric is the sum of the Kernel Disk Read Latency and Physical Device Read Latency metrics. Key: devices\|totalReadLatency_averag
Devices\|Kernel Disk Read Latency (ms)	Average time spent in ESX host VM Kernel per read. Key: devices\|kernelReadLatency_average
Devices\|Kernel Write Latency (ms)	Average time spent in ESX Server VM Kernel per write. Key: devices\|kernelWriteLatency_average
Devices\|Physical Device Read Latency (ms)	Average time taken to complete a read from the physical device. Key: devices\|deviceReadLatency_average
Devices\|Queue Write Latency (ms)	Average time spent in the ESX Server VM Kernel queue per write. Key: devices\|queueWriteLatency_average
Devices\|Physical Device Write Latency (ms)	Average time taken to complete a write from the physical disk. Key: devices\|deviceWriteLatency_average

Datastore Metrics for Datastores

Datastore metrics provide information about datastore use.


Metric Name	Description
Datastore\|Total Latency (ms)	This metric shows the adjusted read and write latency at the datastore level. Adjusted means that the latency is taking into account the number of IOs. If your IO is read-dominated, the combined value is influenced by the reads. This is the average of all the VMs running in the datastore. Because it is an average, some VMs logically experience higher latency that the value shown by this metric. To see the worst latency experienced by any VM, use the Maximum VM Disk Latency metric. Use this metric to see the performance of the datastore. It is one of two key performance indicators for a datastore, the other being the Max Read Latency. The combination of Maximum and Average gives better insight into how well the datastore is coping with the demand. The number should be lower than the performance you expect. Key: datastore\|totalLatency_average
Datastore\|Total Throughput (KBps)	Average use in kilobytes per second. Key: datastore\|usage_average
Datastore\|Read Latency (ms	Average amount of time for a read operation from the datastore. Total latency = kernel latency + device latency. Key: datastore\|totalReadLatency_average
Datastore\|Write Latency (ms)	Average amount of time for a write operation to the datastore. Total latency = kernel latency + device latency. Key: datastore\|totalWriteLatency_average
Datastore\|Demand	Demand. Key: datastore\|demand
Datastore\|Outstanding IO requests	OIO for datastore. Key: datastore\|demand_oio
Datastore\|Read IOPS	This metric displays the average number of read commands issued per second during the collection interval. Use this metric when the total IOPS is higher than expected. See if the metric is read or write dominated. This helps determine the cause of the high IOPS. Certain workloads such as backups, anti-virus scans, and Windows updates carry a Read/Write pattern. For example, an anti-virus scan is heavy on read since it is mostly reading the file system. Key: datastore\|numberReadAveraged_average
Datastore\|Write IOPS	This metric displays the average number of write commands issued per second during the collection interval. Use this metric when the total IOPS is higher than expected. Drill down to see if the metric is read or write dominated. This helps determine the cause of the high IOPS. Certain workloads such as backups, anti-virus scans, and Windows updates carry a Read/Write pattern. For example, an anti-virus scan is heavy on read since it is mostly reading the file system. Key: datastore\|numberWriteAveraged_average
Datastore\|Read Throughput (KBps)	This metric displays the amount of data read in the performance interval. Key: datastore\|read_average
Datastore\|Write Throughput (KBps)	This metric displays the amount of data written to disk in the performance interval. Key: datastore\|write_average

About Datastore Metrics for Virtual SAN

The metric named datastore|oio|workload is not supported on Virtual SAN datastores. This metric depends on datastore|demand_oio, which is supported for Virtual SAN datastores.

The metric named datastore|demand_oio also depends on several other metrics for Virtual SAN datastores, one of which is not supported.

The metrics named devices|numberReadAveraged_average and devices|numberWriteAveraged_average are supported.
The metric named devices|totalLatency_average is not supported.

As a result, vRealize Operations Manager does not collect the metric named datastore|oio|workload for Virtual SAN datastores.

Disk Space Metrics for Datastores

Disk space metrics provide information about disk space use.


Metric Name	Description
Diskspace\|Number of Virtual Disk	Number of virtual disks. Key: diskspace\|numvmdisk
Diskspace\|Provisioned Space (GB)	Provisioned space in gigabytes. Key: diskspace\|provisioned
Diskspace\|Shared Used (GB)	Shared used space in gigabytes. Key: diskspace\|shared
Diskspace\|Snapshot Space (GB)	This metric shows the amount of space taken by snapshots on a given database. Use this metric to know how much storage space is being used by virtual machine snapshots on the datastore. Check that the snapshot is using 0 GB or minimal space. Anything over 1 GB should trigger a warning. The actual value depends on how IO intensive the virtual machines in the datastore are. Run a DT on them to detect anomaly. Clear the snapshot within 24 hours, preferably when you have finished backing up, or patching. Key: diskspace\|snapshot
Diskspace\|Virtual Disk Used (GB)	Virtual disk used space in gigabytes. Key: diskspace\|diskused
Diskspace\|Virtual machine used (GB)	Virtual machine used space in gigabytes. Key: diskspace\|used
Diskspace\|Total disk space used	Total disk space used on all datastores visible to this object. Key: diskspace\|total_usage
Diskspace\|Total disk space	Total disk space on all datastores visible to this object. Key: diskspace\|total_capacity
Diskspace\|Total used (GB)	Total used space in gigabytes. Key: diskspace\|disktotal
Diskspace\|Swap File Space (GB)	Swap file space in gigabytes. Key: diskspace\|swap
Diskspace\|Other VM Space (GB)	Other virtual machine space in gigabytes. Key: diskspace\|otherused
Diskspace\|Freespace (GB)	Unused space available on datastore. Key: diskspace\|freespace
Diskspace\|Capacity (GB)	Total capacity of datastore in gigabytes. Key: diskspace\|capacity
Diskspace\|Overhead	Amount of disk space that is overhead. Key: diskspace\|overhead

Summary Metrics for Datastores

Summary metrics provide information about overall performance.


Metric Name	Description
Summary\|Number of Hosts	This metric shows the number of hosts that the datastore is connected to. Use this metric to know how many clusters the datastore is attached to. The number should not be too high, as a datastore should not be mounted by every host. The datastore and cluster should be paired to keep operations simple. Key: summary\|total_number_hosts
Summary\|Total Number of VMs	This metric shows the number of virtual machines which save their VMDK files on the datastore. If a VM has four VMDKs stored in four datastores, the VM is counted on each datastore. Use this metric to know how many VMs have at least one VMDK on a specific datastore. The number of VMs should be within your Concentration Risk policy. You should also expect the datastore to be well used. If only a few VMs are using the datastore, this is not considered a good use. Key: summary\|total_number_vms
Summary\|Maximum Number of VMs	Maximum number of virtual machines. Key: summary\|max_number_vms
Summary\|Workload Indicator	Workload indicator. Key: summary\|workload_indicator
Summary\|Number of Clusters	This metric shows the number of clusters that the datastore is connected to. Key: summary\|total_number_clusters
Summary\|Number of VM Templates	Number of VM Templates. Key: Summary\|Number of VM Templates

Template Metrics for Datastores


Metric Name	Description
Template\|Virtual Machine used	Space used by virtual machine files. Key: template\|used
Template\|Access Time	Last access time. Key: template\|accessTime

Cost Metrics for Datastores

Cost metrics provides information about the cost.


Metric Name	Description
Monthly Disk Space Base Rate	Disk space base rate for datastore displays the cost of 1 GB storage. Key: cost\|storageRate
Monthly Total Cost	Monthly total cost, computed by multiplying datastore capacity with monthly storage rate. Key: cost\|totalCost
Cost\|Allocation\|Disk Space Base Rate (Currency)	Monthly storage rate for datastore displays the cost of 1 GB storage when the overcommit ratio is set in policy. cost\|storageRate
Cost\|Allocation\|Monthly Datastore Allocated Cost(Currency/Month)	Monthly allocated cost as compared to the total cost of the datastore
Cost\|Allocation\|Monthly Datastore Unallocated Cost(Currency/Month)	Monthly unallocated cost as compared to the total cost of the datastore.

Reclaimable Metrics

Reclaimable metrics provide information about reclaimable resources.


Metric Name	Description
Reclaimable\|Orphaned Disks\|Disk Space (GB)	Summary of storage used by all orphaned VMDKs on the datastore. Key: reclaimable\|orphaned_disk\|diskspace
Reclaimable\|Orphaned Disks\|Potential Savings (Currency)	Potential saving after reclamation of storage by removing orphaned VMDks from the datastore. Key: reclaimable\|orphaned_disk\|cost

Disabled Instanced Metrics

The instance metrics created for the following metrics are disabled in this version of vRealize Operations . This means that these metrics collect data by default but all the instanced metrics created for these metrics, do not collect data by default.


Metric Name
Devices\|Kernel Latency (ms)
Devices\|Number of Running Hosts
Devices\|Number of Running VMs
Devices\|Physical Device Latency (ms)
Devices\|Queue Latency (ms)
Devices\|Queue Read Latency (ms)
Devices\|Read IOPS
Devices\|Read Latency (ms)
Devices\|Read Requests
Devices\|Read Throughput (KBps)
Devices\|Total IOPS
Devices\|Total Latency (ms)
Devices\|Total Throughput (KBps)
Devices\|Write IOPS
Devices\|Write Latency (ms)
Devices\|Write Requests
Devices\|Write Throughput (KBps)

Disabled Metrics

The following metrics are disabled in this version of vRealize Operations . This means that they do not collect data by default.

You can enable these metrics in the Policy workspace. For more information, in VMware Docs search for Collect Metrics and Properties Details.


Metric Name	Key
Capacity\|Data Store Capacity Contention (%)	capacity\|contention
Datastore I/O\|Demand Indicator	datastore\|demand_indicator
Datastore I/O\|Max Observed Number of Outstanding IO Operations	datastore\|maxObserved_OIO
Datastore I/O\|Max Observed Read Latency (msec)	datastore\|maxObserved_Read
Datastore I/O\|Max Observed Read Latency (msec)	datastore\|maxObserved_ReadLatency
Datastore I/O\|Max Observed	datastore\|maxObserved_NumberRead
Datastore I/O\|Max Observed Write Latency (msec)	datastore\|maxObserved_Write
Datastore I/O\|Max Observed Write Latency (msec)	datastore\|maxObserved_WriteLatency
Datastore I/O\|Max Observed Writes per second	datastore\|maxObserved_NumberWrite
Datastore\|Demand Indicator	Demand Indicator. Key: datastore\|demand_indicator
Diskspace\|Not Shared (GB)	Unshared space in gigabytes. Key: diskspace\|notshared

Metric Name	Description
Capacity\|Available Space (GB)	This metric shows the amount of free space that a datastore has available. Use this metric to know how much storage space is unused on the datastore. Try to avoid having too little free disk space in order to accommodate unexpected storage growth on the datastore. The exact size of the datastore is based on company policy. Key: capacity\|available_space
Capacity\|Provisioned (GB)	This metric shows the amount of storage that was allocated to the virtual machines. Use this metric to know how much storage space is being used on the datastore. Check the metric trend to identify spikes or abnormal growth. Key: capacity\|provisioned
Capacity\|Total Capacity (GB)	This metric shows the overall size of the datastore. Use this metric to know the total capacity of the datastore. Typically the size of the datastore should not be too small. VMFS datastore size has grown over the years as virtualization matures and larger virtual machines are now onboard. Ensure that the size can handle enough virtual machines to avoid datastore sprawl. A best practice is to use 5 TB for VMFS and more for vSAN. Key: capacity\|total_capacity
Capacity\|Used Space (GB)	This metric shows the amount of storage that is being used on the datastore. Key: capacity\|used_space
Capacity\|Workload (%)	Capacity workload. Key: capacity\|workload
Capacity\|Uncommitted Space (GB)	Uncommitted space in gigabytes. Key: capacity\|uncommitted
Capacity\|Total Provisioned Consumer Space	Total Provisioned Consumer Space. Key: capacity\|consumer_provisioned
Capacity\|Used Space (%)	This metric shows the amount of storage that is being used on the datastore. Use this metric to know the percentage of storage space being used on the datastore. When using this metric, verify that you have at least 20% of free storage. Less than this, and you might experience problems when a snapshot is not deleted. If you have more than 50% free storage space, you are not utilizing your storage in the best possible way. Key: capacity\|usedSpacePct

Metric Name	Description
Devices\|Bus Resets	This metric shows the number of bus resets in the performance interval. Key: devices\|busResets_summation
Devices\|Commands Aborted	This metric shows the number of disk commands canceled in the performance interval. Key: devices\|commandsAborted_summation
Devices\|Commands Issued	This metric shows the number of disk commands issued in the performance interval. Key: devices\|commands_summation
Devices\|Read Latency (ms)	This metric shows the average time taken for a read from the perspective of a guest operating system. This metric is the sum of the Kernel Disk Read Latency and Physical Device Read Latency metrics. Key: devices\|totalReadLatency_averag
Devices\|Kernel Disk Read Latency (ms)	Average time spent in ESX host VM Kernel per read. Key: devices\|kernelReadLatency_average
Devices\|Kernel Write Latency (ms)	Average time spent in ESX Server VM Kernel per write. Key: devices\|kernelWriteLatency_average
Devices\|Physical Device Read Latency (ms)	Average time taken to complete a read from the physical device. Key: devices\|deviceReadLatency_average
Devices\|Queue Write Latency (ms)	Average time spent in the ESX Server VM Kernel queue per write. Key: devices\|queueWriteLatency_average
Devices\|Physical Device Write Latency (ms)	Average time taken to complete a write from the physical disk. Key: devices\|deviceWriteLatency_average

Metric Name	Description
Datastore\|Total Latency (ms)	This metric shows the adjusted read and write latency at the datastore level. Adjusted means that the latency is taking into account the number of IOs. If your IO is read-dominated, the combined value is influenced by the reads. This is the average of all the VMs running in the datastore. Because it is an average, some VMs logically experience higher latency that the value shown by this metric. To see the worst latency experienced by any VM, use the Maximum VM Disk Latency metric. Use this metric to see the performance of the datastore. It is one of two key performance indicators for a datastore, the other being the Max Read Latency. The combination of Maximum and Average gives better insight into how well the datastore is coping with the demand. The number should be lower than the performance you expect. Key: datastore\|totalLatency_average
Datastore\|Total Throughput (KBps)	Average use in kilobytes per second. Key: datastore\|usage_average
Datastore\|Read Latency (ms	Average amount of time for a read operation from the datastore. Total latency = kernel latency + device latency. Key: datastore\|totalReadLatency_average
Datastore\|Write Latency (ms)	Average amount of time for a write operation to the datastore. Total latency = kernel latency + device latency. Key: datastore\|totalWriteLatency_average
Datastore\|Demand	Demand. Key: datastore\|demand
Datastore\|Outstanding IO requests	OIO for datastore. Key: datastore\|demand_oio
Datastore\|Read IOPS	This metric displays the average number of read commands issued per second during the collection interval. Use this metric when the total IOPS is higher than expected. See if the metric is read or write dominated. This helps determine the cause of the high IOPS. Certain workloads such as backups, anti-virus scans, and Windows updates carry a Read/Write pattern. For example, an anti-virus scan is heavy on read since it is mostly reading the file system. Key: datastore\|numberReadAveraged_average
Datastore\|Write IOPS	This metric displays the average number of write commands issued per second during the collection interval. Use this metric when the total IOPS is higher than expected. Drill down to see if the metric is read or write dominated. This helps determine the cause of the high IOPS. Certain workloads such as backups, anti-virus scans, and Windows updates carry a Read/Write pattern. For example, an anti-virus scan is heavy on read since it is mostly reading the file system. Key: datastore\|numberWriteAveraged_average
Datastore\|Read Throughput (KBps)	This metric displays the amount of data read in the performance interval. Key: datastore\|read_average
Datastore\|Write Throughput (KBps)	This metric displays the amount of data written to disk in the performance interval. Key: datastore\|write_average

Metric Name	Description
Diskspace\|Number of Virtual Disk	Number of virtual disks. Key: diskspace\|numvmdisk
Diskspace\|Provisioned Space (GB)	Provisioned space in gigabytes. Key: diskspace\|provisioned
Diskspace\|Shared Used (GB)	Shared used space in gigabytes. Key: diskspace\|shared
Diskspace\|Snapshot Space (GB)	This metric shows the amount of space taken by snapshots on a given database. Use this metric to know how much storage space is being used by virtual machine snapshots on the datastore. Check that the snapshot is using 0 GB or minimal space. Anything over 1 GB should trigger a warning. The actual value depends on how IO intensive the virtual machines in the datastore are. Run a DT on them to detect anomaly. Clear the snapshot within 24 hours, preferably when you have finished backing up, or patching. Key: diskspace\|snapshot
Diskspace\|Virtual Disk Used (GB)	Virtual disk used space in gigabytes. Key: diskspace\|diskused
Diskspace\|Virtual machine used (GB)	Virtual machine used space in gigabytes. Key: diskspace\|used
Diskspace\|Total disk space used	Total disk space used on all datastores visible to this object. Key: diskspace\|total_usage
Diskspace\|Total disk space	Total disk space on all datastores visible to this object. Key: diskspace\|total_capacity
Diskspace\|Total used (GB)	Total used space in gigabytes. Key: diskspace\|disktotal
Diskspace\|Swap File Space (GB)	Swap file space in gigabytes. Key: diskspace\|swap
Diskspace\|Other VM Space (GB)	Other virtual machine space in gigabytes. Key: diskspace\|otherused
Diskspace\|Freespace (GB)	Unused space available on datastore. Key: diskspace\|freespace
Diskspace\|Capacity (GB)	Total capacity of datastore in gigabytes. Key: diskspace\|capacity
Diskspace\|Overhead	Amount of disk space that is overhead. Key: diskspace\|overhead

Metric Name	Description
Summary\|Number of Hosts	This metric shows the number of hosts that the datastore is connected to. Use this metric to know how many clusters the datastore is attached to. The number should not be too high, as a datastore should not be mounted by every host. The datastore and cluster should be paired to keep operations simple. Key: summary\|total_number_hosts
Summary\|Total Number of VMs	This metric shows the number of virtual machines which save their VMDK files on the datastore. If a VM has four VMDKs stored in four datastores, the VM is counted on each datastore. Use this metric to know how many VMs have at least one VMDK on a specific datastore. The number of VMs should be within your Concentration Risk policy. You should also expect the datastore to be well used. If only a few VMs are using the datastore, this is not considered a good use. Key: summary\|total_number_vms
Summary\|Maximum Number of VMs	Maximum number of virtual machines. Key: summary\|max_number_vms
Summary\|Workload Indicator	Workload indicator. Key: summary\|workload_indicator
Summary\|Number of Clusters	This metric shows the number of clusters that the datastore is connected to. Key: summary\|total_number_clusters
Summary\|Number of VM Templates	Number of VM Templates. Key: Summary\|Number of VM Templates