This document discusses energy goals and metrics for cloud services. It proposes two goals: 1) assessing the effectiveness of a software's energy consumption behavior under different deployment configurations and workloads, and 2) characterizing a software's energy efficiency by identifying the energy used by different components and features. It also provides templates for questions to evaluate these goals, such as comparing the energy used by virtual machines running different software configurations and processing various workloads. The overall aim is to help cloud service providers optimize their software's energy usage.

1. Energy related Goals and Questions
for Cloud Services
Measurement and Metrics for Green and
Sustainable Software (MeGSuS '14)
IWS Mensura – Rotterdam, the Netherlands
Jean-Christophe<dot>DEPREZ<at>CETIC<dot>be
Scientific Coordinator
&
Christophe<dot>PONSARD<at>CETIC<dot>be

2. CETIC Presentation
• Accredited Research Centre
~40 researcher in 3 departments Created in 2001
• Applied Research at EU and Reginal level
• Technology Transfert Agent to (inter-)Regional Industry Mission
• SotA/Techno Evaluation and Coaching (HW/SW)
• Trusted Third Party
• Connect Industry to latest research results
Serving Industry
• EU: FP7 – Coordinator and Participants
• EraNets and Interreg
• Regional Research project (Plan Marshall 2.vert)
International Involment
• Technological Checks
• Feasibility Studies
• R&D 1-1 Projects
Regional Funding for
Contract Research
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3. Software &
System
Engineering
Futur
Internet
Internet of
Things
Overall Expertise
• Process & Product Quality
• Optimization
• Modelling
• Security
• Cloud Computing
• Semantic Web
• Big Data
• Open Source & Open Data
• Programmable Systems
• Smart Objects
• Wireless Sensor Network
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4. Positioning
ICT INDUSTRY
• Technology transfer
• Proof-of-Concept
• Feasibility studies
• Applied Research
ACADEMICS
Technology Readiness Level
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5. A bit of History
• Beginning – late 80’s
– Hardware was consuming
– Software did the best it could with the little it had
• From 90’s
– Hardware keeps improving
– Software developers started neither to care about
optimizing their algorithms nor their code
hacks for better time and space efficiency became
things of the past .
• From 2010’s
– Even less worries since applications run in the Cloud
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6. Should the Software Industry care?
• Organisations and corporate responsibility
– Cloud consumption augment
– Once eScience and other HPC lead their way to Cloud,
Providers will likely come up with pricing according to
consumption
• People slightly modify their behaviour to preserve
the climate
– Soft Developers are no better or worst than majority
– But as others, the effort should be moderate and
guidance and assistance is needed
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7. ASCETIC Business Requirements
• 17 interviews with
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8. ASCETIC Business Requirements
• 17 interviews with
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9. Resulted in 7 Business Requirements
• BG1 - Support EU organisations to achieve ICT decarbonisation
progress. (Lisbon Treaty)
• BG2 - Ecological and Economical balance
• BG3 - Support organisations to achieve social responsible behavior
• BG4 - Provide ASCETiC users with means to properly control and
monitor pricing models based on energy consumption
• BG5 - Provide ASCETiC users with means to properly monitor and
optimise energy consumption
• BG6 – Server side computing and data handling have lacked focus
• BG7 - Provide ASCETiC stakeholders with a sustainable solution
based on recognized standards
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10. Goal Question Metrics (GQM)
• A pragmatic approach to self-evaluate
• Assisting in
– Identify Generic Goals with clear definitions whose
evaluation is based on
– Patterns of Interesting Questions
– Associated to measurable KPI or Metrics
(= whose measurements can be obtained without
much change in working habits)
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11. Goals
• ISO 25000 – SQuaRE (replaces ISO9126)
– 25010 – Quality Models
• Software Product Quality Model (Developer view)
• (System) Quality in Use Model (Operator & User view)
• Not much about Energy … hidden behind
– Performance Efficiency … Resource Utilisation
Resources can be many things and indirectly some resources
consume energy
– Freedom from risk … environmental risk mitigation
Unless we believe energy shortage is likely …
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12. Goal 1 – SaaS Energy Consumption
Behaviour Effectiveness
• In short
– Do the best we can with what we have
– Address BG2 (eco balance) and BG3 (corp. respons.)
• Energy Consumption Behaviour Effectiveness
is the degree to which a software product is deployed
and configured in a way to reduce the operating cost for
the software product operator (or SaaS provider) taking
the energy cost into account.
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13. Goal Template – SaaS Energy
Consumption Behaviour Effectiveness
SaaS Energy Consumption Behaviour Effectiveness
Object Server-side software of a Cloud application
Purpose (Qualitative) characterization of the energy consumption
behavior effectiveness on representative workload
Quality Focus Effectiveness of Energy Consumption Behaviour
Point of View Providers of a Cloud Application (SaaS Provider)
Context Identify the different deployment alternatives with the most
effective energy consumption behavior according to various
representative workloads
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14. Goal 2 – SaaS Energy Efficiency
• In short
– Learn about energy leaks to improve in next versions
– Address BG5 (monitor) and BG6 (comp & data)
• SaaS Energy Efficiency
is the degree to which energy expanded by a software
system in operation is in relation to the software tasks
executed and the results achieved.
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15. Goal Template – SaaS Energy Efficiency
SaaS Energy Efficiency
Object Server-side software features or components of a Cloud
application
Purpose (Qualitative) characterization of the energy efficiency on
representative workloads
Quality Focus Energy Efficiency
Point of View Development team and Project Manager of a Cloud
Application
Context Identify the energy consumption of various features or
components of an application to be provided as a service in
the Cloud to facilitate later refactoring activities to improve the
application code with regards to energy consumption.
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16. Industry Use Case - News Asset
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17. NewsAsset Deployment Alternatives
• Moving to a SaaS model
• Alternative 1: Isolate customer
1 VM per customer with NewsAsset server
• Alternative 2: Multitenant
1 load balancer,
n VM each with a NewsAsset server instance
m VM with file and database servers
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18. Template of Questions for Energy
Consumption Behaviour Effectiveness
What can we play with
– VM have technical characteristics
• CPU frequency, memory and disk size, …
– Modular Applications have sub systems Si made of
components cij
• Components can be co-located on same VM (vmk) or not
Both together define Deployment Alternatives (Dm)
– Representative Workloads (for typical classes of
customers) wl
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19. Template of Questions for Energy
Consumption Behaviour Effectiveness
• How much energy is consumed by a vmk deployed
with a set of cij’s (from a deployment alternative
Dm) installed when the workload wl is applied?
– Energy consumed can be
• Total
• Chronological (evolution of energy consumption over time)
• Comparative (to other measures that influence energy
consumption)
– Question can be asked for VMs with different
characteristics with different set of components
installed on them and for different customer
workloads
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20. Conclusion
• Similar question template can be defined for
Energy Efficiency
– Nightly builds – only select 1 or 2 alternative
deployments
– Focus analysis on variability between workloads
• A first release of Papyrus and Acceleo projects
– Papyrus project – Profile to augment UML with
stereotypes with KPI monitoring information
– Acceleo project – To extract KPI monitoring information
from UML models and transform it in a textual format
(human readable and to come: OVF fragments)
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21. Future Work
• Migrate to Eclipse Luna and new version of
Papyrus and Acceleo
• Include monitoring for additional KPIs (on quality
of service, protection, experience, etc.)
• Handle monitoring for trade-off KPIs
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22. Energy related Goals and Questions
for Cloud Services
Measurement and Metrics for Green and
Sustainable Software (MeGSuS '14)
IWS Mensura – Rotterdam, the Netherlands
Jean-Christophe<dot>DEPREZ<at>CETIC<dot>be
Scientific Coordinator
&
Christophe<dot>PONSARD<at>CETIC<dot>be