Difference between revisions of "Zabbix-agent-adoption"
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== Introduction == | == Introduction == | ||
| + | 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 /> | ||
| + | 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. | ||
| − | + | 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. | ||
| − | This blueprint aims at leveraging existing monitoring assets and expertises to the best extent, instead of removing or replacing them with efforts. An adoption mechanism between Zabbix agents in instances and Ceilometer agents in compute nodes will be added, therefore Ceilometer can poll data from Zabbix to enhance its capability of monitoring | + | 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 == | == Design and implementation == | ||
To be added | To be added | ||
Revision as of 06:58, 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
