Jump to: navigation, search

Difference between revisions of "Zabbix-agent-adoption"

(Introduction)
(Introduction)
Line 6: Line 6:
 
== Introduction ==
 
== Introduction ==
 
Currently, Ceilometer collects instance data via compute agents installed on every OpenStack compute nodes. PollingTasks<br />
 
Currently, Ceilometer collects instance data via compute agents installed on every OpenStack compute nodes. PollingTasks<br />
in a compute agent invoke multiple pollsters, which then call hypervisor-dependent inspectors for metering various metrics. <br />
+
in a compute agent invoke multiple pollsters, which then call hypervisor-dependent inspectors for metering various metrics. <br />
 
Such pollsters work well for data visible to a hypervisor (http://www.mirantis.com/blog/openstack-metering-using-ceilometer/), <br />
 
Such pollsters work well for data visible to a hypervisor (http://www.mirantis.com/blog/openstack-metering-using-ceilometer/), <br />
 
while ignoring some detailed and precise guest system metrics.  
 
while ignoring some detailed and precise guest system metrics.  
  
As an example, the CPUPollster calls the inspect_cpus() method of a hypervisor-dependent inspector object to get VCPU data.
+
As an example, the CPUPollster calls the inspect_cpus() method of a hypervisor-dependent inspector object to get VCPU data.<br />
If the hypervisor is KVM, inspect_cpus() calls the info() method of the virDomain class of libvirt, then returns a struct consisting
+
If the hypervisor is KVM, inspect_cpus() calls the info() method of the virDomain class of libvirt, then returns a struct consisting<br />
 
of VCPU number and running time since booting this instance up.
 
of VCPU number and running time since booting this instance up.
  
However, those guest system metrics, in practice, are highly valuable for both OpenStack Admins and tenants, according to our own operating experiences and feedback from other companies using OpenStack. Therefore, Zabbix has been deployed in many product-oriented OpenStack clouds to achieve detailed and precise monitoring. Other popular 3rd-party monitoring tools include Nagios, Ganglia, etc.
+
However, those guest system metrics, in practice, are highly valuable for both OpenStack Admins and tenants, according to our<br />
 +
own operating experiences and feedback from other companies using OpenStack. Therefore, Zabbix has been deployed in many<br />
 +
product-oriented OpenStack clouds to achieve detailed and precise monitoring. Other popular 3rd-party monitoring tools include<br />
 +
Nagios, Ganglia, etc.
  
This blueprint aims at leveraging existing monitoring assets and expertises in system administration teams to the best extent, instead of removing or replacing them with efforts. An adoption mechanism between Zabbix agents in instances and Ceilometer compute agents in compute nodes will be added, therefore Ceilometer can poll data from Zabbix agents to enhance its capability of monitoring instances. The feasibility for adopting agents of other 3rd-party monitoring tools, e.g. Nagios and Ganglia, will also be considered in the machanism design.
+
This blueprint aims at leveraging existing monitoring assets and expertises in system administration teams to the best extent, instead<br />
 +
of removing or replacing them with efforts. An adoption mechanism between Zabbix agents in instances and Ceilometer compute agents<br />
 +
in compute nodes will be added, therefore Ceilometer can poll data from Zabbix agents to enhance its capability of monitoring instances.<br />
 +
The feasibility for adopting agents of other 3rd-party monitoring tools, e.g. Nagios and Ganglia, will also be considered in the machanism design.
  
 
== Design and implementation ==
 
== Design and implementation ==
  
 
To be added
 
To be added

Revision as of 06:59, 1 November 2013

  • Launchpad Entry: CeilometerSpec:Zabbix-agent-adoption
  • Created: Oct. 25, 2013
  • Contributors: Yu Zhang

Introduction

Currently, Ceilometer collects instance data via compute agents installed on every OpenStack compute nodes. PollingTasks
in a compute agent invoke multiple pollsters, which then call hypervisor-dependent inspectors for metering various metrics.
Such pollsters work well for data visible to a hypervisor (http://www.mirantis.com/blog/openstack-metering-using-ceilometer/),
while ignoring some detailed and precise guest system metrics.

As an example, the CPUPollster calls the inspect_cpus() method of a hypervisor-dependent inspector object to get VCPU data.
If the hypervisor is KVM, inspect_cpus() calls the info() method of the virDomain class of libvirt, then returns a struct consisting
of VCPU number and running time since booting this instance up.

However, those guest system metrics, in practice, are highly valuable for both OpenStack Admins and tenants, according to our
own operating experiences and feedback from other companies using OpenStack. Therefore, Zabbix has been deployed in many
product-oriented OpenStack clouds to achieve detailed and precise monitoring. Other popular 3rd-party monitoring tools include

Nagios, Ganglia, etc.

This blueprint aims at leveraging existing monitoring assets and expertises in system administration teams to the best extent, instead
of removing or replacing them with efforts. An adoption mechanism between Zabbix agents in instances and Ceilometer compute agents
in compute nodes will be added, therefore Ceilometer can poll data from Zabbix agents to enhance its capability of monitoring instances.
The feasibility for adopting agents of other 3rd-party monitoring tools, e.g. Nagios and Ganglia, will also be considered in the machanism design.

Design and implementation

To be added