Orange's data centers consume 500 GWh annually, equivalent to the energy use of 75,000 French households, with future increases expected due to rising data usage. The company aims to reduce its greenhouse gas emissions by 20% from 2006 to 2020, highlighting the importance of energy efficiency in the context of growing data traffic. An energy audit project within OPNFV is underway to monitor and optimize power consumption through real-time data collection and analysis.

2. Energy Audit aaS with OPNFV
B.Hérard, Orange
M.Richomme, Orange

4. Note that studies showed that virtualization could lead to an increase of power consumption and is still a matter of debate

5. Src: https://www.orange.com/en/Commitments/Responsibility/Environment/Folder/Climate-change/Folder/Orange-and-the-COP/Folder/Green-ITN
https://www.orange.com/en/Commitments/Responsibility/Environment/Folder/Climate-change/Folder/Orange-and-the-COP/Folder/Data-centres
500 GWh. That’s how much energy Orange’s data centres consume in a year. The
average annual consumption of 75,000 French households. That figure is not
alarming in itself. Yet. But it will increase in years to come as pressure from data usage
grows. More than ever, the “greening” of data centres is a strategic issue.
Today, the Orange ITN (Information Technologies & Networks) factory is made up of around
100,000 mobile access points, dozens of data centres, and service platforms. Together,
they generate 75% of the Group’s total CO2 emissions and account for 80% of its energy
consumption. The potential for improvements is huge.
Orange has committed to reduce its greenhouse gas emissions by 20% between 2006
and 2020. This is a real challenge within the context of rapidly growing usage and the
relentless increase in data traffic.

7. Energy Efficiency is a key driver….
However it is poorly covered by Open
Source communities…

8. Energy Audit aaS in OPNFV
• Collect: get real time Power consumption of Pharos PODs (all
the nodes)
• Corelate: leverage determinist CI runs to establish Energy
profiles
• Optimize: implement policy or placement rules to optimize
power consumption

11. Power collection
• IPMI
• Redfish
Src: tests done in Orange Labs on DELL server, to be confirmed on other servers

12. • Build the collector
• Install it on your jumphost
• Need access to IPMI/Redfish
• Need Internet access to push measures to InfluxDB
Power collection

13. Functest Yardstick
Pull Down
Functest Image
Pull Down
Yardstick Image
Docker
Hub
Docker
Hub
Pharos POD
(SUT) Collector
Energy API
During CI Run
Instructions trigger
• Energy measurement
• Push result to Influx DB

14. • Python Power consumption SDK
• Indicate (using decorators) the cases you want to monitor
• You can precise start/stop or intermediate events (e.g. onap
deployed)
@energy.enable_recording
def run(self):
self.do_some_stuff1()
self.do_some_stuff2()
@energy.enable_recording
def run(self):
Energy.energy.step("step1")
self.do_some_stuff1()
Energy.energy.step("step2")
self.do_some_stuff2()

15. Vizualization

16. Vizualization

17. Next steps
• Opportunity for a dedicated « Energy » project? (initial work triggered
during the Plugfest in Paris + bootstrap with Functest)
• https://wiki.opnfv.org/display/testing/Power+consumption+monitoring
• Understand the different phases, and use the event API to visualize steps
• Get Data, get data, get data ….need data to validate test/VNF profiling =>
sync with Bamboo

18. Next steps
• Statistics & big Data….
https://git.opnfv.org/qtip/tree/contrib/TOM
• Link with Bamboo (OPNFV
implementation of PNDA)
Src: post processing on yardstick results done by Alassane Samba (PHD student in Orange)

19. Conclusions
• Power consumption monitoring initiated with an end to
end prototype up&running
• Exciting but still challenging (not sure the profiles we
are collecting will be consistent/acurate)…empiric
way…
• New area for POD optimization study (inputs for
watcher?)
• contact benoit.herard AT orange.com

20. 谢谢 - Thank you - Merci