eG Monitoring
 

Measures reported by RHEVGuestTest

This test monitors the amount of the physical server's resources that each guest on an RHEV server 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 over-utilizing memory, 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. The measures made by this test are as follows:

Measurement Description Measurement Unit Interpretation
Status Indicates whether this VM is currently powered-on or off.   This measure reports the value Up if the VM is currently powered-on, and the value Down if the VM is currently powered-off.

The numeric values that correspond to the measure values mentioned above are as follows:

Numeric Value Measure Value
1 Up
0 Down

Note:

By default, this measure reports the above-mentioned Measure Values while indicating the status of this VM. However, the graph of this measure powered-on states will be represented using the corresponding numeric equivalents only.
Statless Indicates whether this VM is currently stateless or not.   A stateless VM is not a VM that has its own local data. More often than not, it does require some local data or a local cache for better performance. But these data don’t need to be persisted. In some cases, a stateless VM can have additional software installed or data pulled in from a known repository. This process should be fully automated with self-starter scripts, or managed by an external installer.

Once a stateless VM goes live, it should discover all the related services to persistent data. The stateless VM has to rely on the environment to work effectively. It includes directory services, data services, and so on.

With stateless VMs, you can improve mobility inside an enterprise and external transfer to the public cloud. For one thing, you just need to transfer a VM image once and only once. When your application runs into problems, instead of diagnosing the problem you just remove the problematic VMs and add new virtual machines. With this capability, you can also easily scale out your applications by adding new VM instances as you need them.

Last but not least, the software upgrade and patch. It has been a big pain to upgrade and patch software in large deployments. You have to do it with each individual machine despite virtual or not. With stateless VM, you only need to patch the template and new virtual machines will pick it up seamlessly.

This measure reports the value Yes if the VM is a stateless VM, and the value No if it is not a stateless VM.

The numeric values that correspond to these measure values are discussed in the table below:

Numeric Value Measure Value
1 Yes
0 No

Note:

By default, this measure reports the above-mentioned Measure Values while indicating the VM is a stateless VM or not. However, in the graph of this measure this will be represented using the corresponding numeric equivalents only.
Cpu_core Indicates the number of virtual CPUs allocated to this VM. Number  
Vcpu Indicates the percentage of virtual CPU resources this VM utilized. % Compare the value of this measure across VMs to identify the VM that is consuming CPU excessively. A high value for this measure could indicate that one/more CPU-intensive processes are executing on the VM.
Phy_cpu Indicates the percentage of physical CPU resources this VM utilized for system-level processing. % A high value could indicate that the VM is executing too many system-level tasks simultaneously.
Tot_cpu_use Indicates the percent of virtual CPU that is currently in use in this VM. %  
Phy_cpu_util Indicates the percentage of physical CPU used by this VM. % A high value for this measure indicates that this VM is using a lot of the processor - possibly because one or more processes on this VM are taking a lot of CPU.
Mem_installed Indicates the amount of memory that is allocated to this VM. MB  
Mem_used Indicates the amount of physical memory that consumed by this VM. MB  
pct_mem Indicates the percentage of physical memory consumed by this VM. % A high value for this measure is indicative of high memory usage by a VM. Compare the value of this measure across VMs to know which VMs are eroding the physical memory of the hypervisor. Once the resource-hungry VMs are isolated, you need to investigate why those VMs are consuming memory excessively and see how the resource usage can be controlled. If the issue is allowed to persist, then very soon you may not have adequate physical memory to support hypervisor and VM operations.
Gurant_mem Indicates the amount of memory resources that is guaranteed available to this VM - i.e., the minimum amount of memory that will always be available to this VM. MB  
Disk_state Indicates the status of the virtual disk of this VM. MB The value of this measure can be OK or Not ok, depending upon the current status of the disk.

The numeric values that correspond to these measure values are as follows:

Numeric Value Measure Value
1 Ok
0 Not ok

Note:

By default, this measure reports the Measure Values listed in the table above to indicate the status of the disk. However, in the graph of this measure, the disk status will be represented using the numeric equivalents of the measure values only.
Disk_capacity Indicates the current disk capacity of this VM. GB  
Data_reads Indicates the rate at which data is read from the virtual disks of this VM. MB/sec  
Data_writes Indicates the rate at which data is written to the virtual disks of this VM. MB/sec  
Data_throput Indicates the rate at which I/O operations are performed on the virtual disks of this VM. MB/sec The value of this measure indicates the level of I/O activity on every VM. Compare this value across VMs to identify which VM is experiencing abnormally high disk I/O. Zooming into the internal operations of that VM can shed light on the I/O-intensive processes that may be executing in that VM.
Net_data_trans Indicates the rate at which data is transmitted from this VM. Mbps Comparing the data transmitted across all the VMs provides an indicator of the VM that is generating most out-bound network traffic.
Net_data_receive Indicates the rate at which data was received by this VM. Mbps Comparing the data transmitted across all the VMs provides an indicator of the VM that is generating most in-bound network traffic.
Net_data_throput Indicates the rate at which the network data is accessed by this VM. Mbps For every VM, the value of this measure indicates the level of network traffic flowing into and from that VM. Compare this value across VMs to identify which VM is experiencing abnormally high traffic.