eG Monitoring
 

Measures reported by XenPoolGuestTest

This test monitors the amount of the physical server's resources that each guest on an XenServer is taking up. Using the metrics reported by this test, administrators can determine which virtual guest is taking up most CPU, which guest is generating the most network traffic, which guest is taking up the maximum memory utilization, which guest has the maximum disk activity, etc. Note that the amount of resources taken up by a virtual guest will be limited by the resource allocations that have been made by administrators. For example, an administrator could cap the amount of memory that a specific guest may take. Also, virtual guests can be organized into resource pools, and allocation of resources can be made at the resource-pool level. In this case, virtual guests allocated to the same resource pool contend for the resources allocated to the resource pool.

Measurement Description Measurement Unit Interpretation
Powered_on Whether the virtual machine is currently running on the XenServer host or no.   While the test reports a wide variety of other metrics too for virtual machines that are alive, only the Powered_on status is indicated for virtual machines that are currently not available.

If this measure reports the value Yes, it indicates that the guest is up and running. The value No could indicate that the guest has been powered-off; it could also indicate that XenMotion® has moved the guest to a different server.

The numeric values that correspond to each of the powered-on states discussed above are listed in the table below:

State Value
Yes 1
No 0

Note:

By default, this measure reports the values Yes or No to indicate the status of a VM. The graph of this measure however, represents the status of a VM using the numeric equivalents - 0 or 1.

Cpu_util Indicates the percentage of physical CPU used by the guest Percent A high value for this measure indicates a virtual machine that is using a lot of the processor - possibly because one or more processes on this VM are taking a lot of CPU.
Total_memory Indicates the amount of physical memory currently allocated to the guest MB  
Free_memory Indicates the amount of memory available for use with the guest MB Ideally, this value should be high. A low or consistent decrease in this value denotes that the application(s) executing on the guest are consuming memory excessively. You might want to consider increasing the memory allocated to the guest. XenServer Enterprise and XenServer Standard allow that a Linux/Windows VM can use up to 32GB of memory. Moreover, Xen has implemented a balloon driver concept for each domain, enabled independently, that allows the operating system to adjust its current memory allocation up to the maximum limit configured. This allows “unused” allocation to be consumed in other areas, potentially allowing for stable over-commitment of memory resources. Because of this constantly changing memory allocation, memory is allocated and freed dynamically at a granularity of the page-level.
Used_memory Indicates the amount of memory used by the guest MB  
Memory_usage Indicates the percentage of allocated memory that is being used by the guest Percent High memory consumption over long periods can deplete the free memory on the guest, causing prolonged delays in the execution of the application(s) hosted by the guests. Comparison of the memory usage across guests indicates the guest(s) that could be causing a memory bottleneck on the host.
Disk_reads Indicates the rate at which the guest read from the disk KBytes/Sec  
Disk_writes Indicates the rate at which the guest wrote data to the disk Mbps  

Network_reads Indicates the network I/O reads performed by the guest Mbps  
Network_writes Indicates the network I/O writes performed by the guest Mbps  
Total_capacity Indicates the total allocated disk size to guest VM MB  
Virtual_cpu_used The percentage of allocated CPU resources that this VM is currently using Percent Comparing the value of this measure across VMs will enable you to accurately identify the VMs on which CPU-intensive applications are executing.