This is my new idea on improve distributed system management leveraging OpenStack.

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System management
framework leveraging
OpenStack
Gary Duan

2. © Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.2
Agenda
Problem Statement
Our Solution
Competitive Approaches
Next Steps

3. © Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.3
Problem Statements
 For physical machines in data center
Deployment:
Install/upgrade/re-install using PXE/chef/puppet
System management: Vendor-specific solutions, Not compatible with other vendors’ hard wares
HP’s OneView, Cisco’s UCS Mgmt System
Enterprise Customized scripts/tools to monitor/control via SNMP, IPMI, etc
Hardware diagnostics
Vendor-specific solutions with their specific UI
Scattered, vendor-specific, no unified interface
 In OpenStack, hosts want being managed in a convennient way

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Our Solution
 Converged Management Framework
 Deployment
 Monitor/Management
 Diagnostics
 Is it possible to manage physical machines leveraging OpenStack?
 OpenStack existing utilities
Glance(Image Management) +Heat(Collaboration):
Automation of Install/upgrade/re-install
Ironic:
Manage bare-metal: IPMI, SSH, PXE
Ceilometer:
Obtain info and status of target and notify upon events

5. © Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.5
Our Solution(Cont’d)
 To be Done
Framework
Monitoring, Visibility, Alert, Failure Remediation, Management, Report, Deployment, Diagnostics
Converged user interface and REST API
display software/hardware info/status;
manage physical machines, etc
Plugin mechanism allow vendor to implement their specific features
Obtain info/status to feed ceilometer-agent
Allow vendors to implement their drivers for storage/switches, and even servers, besides WBEM;
Customer can also define their monitor target/policies
Management: power management, plan for down
Online diagnostics: Define plugin interface; leverage WBEM/Heat
Offline diagnostics: Define plugin interface; leverage EFI, leverage Heat
(nice to have) Preventive hardware failure with big-data thinking:
Failure probability curve of specific hardwares based on their use pattern, vendors’ data and datacenter’s data
Failure probability of servers/hardwares based on datacenter’s data(public database or enterprise own database)
Other popular preventive features

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Competitive Approaches
 Current Manage Softwares
o Nagios(GPLv2): http://www.nagios.com/products/nagioscore
o GoundWork: http://www.gwos.com/
o Zabbix: http://www.zabbix.com/
o Cacti: http://www.cacti.net/
o OpenNMS (GPL): http://www.opennms.org/wiki/Main_Page
 Compare with Our solution
o Brand, owned by small company V.S. OpenStack: vendors support, enterprise use
o Just management, no deploy/diag V.S. Includes mgmt, deployment, diagnostics
o Not easy to customize V.S. REST API, Plugin for monitor target and policy
o Not include vendors’ specific hardware V.S. Plugin mechanism, allows vendor implement
diagnostics

7. © Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.7
Next Steps
 Tasks
 Investigate enterprise’s system management solution more deeply
 Make proto and PoC
1) First, targeted for hosts management in OpenStack
2) Then, extend to manage all machines in datacenters
 Initiate an Open Source project for this
 incubated/formal project of OpenStack

8. © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Restricted.
Thank you

9. © Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.
Backup Slides

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Puppet

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Ceilometer