Sustainability Insights
draft-almprs-sustainability-insights-00
| Document | Type | Active Internet-Draft (individual) | |
|---|---|---|---|
| Authors | Per Andersson , Jan Lindblad , Snezana Mitrovic , Marisol Palmero , Esther Roure , Gonzalo Salgueiro | ||
| Last updated | 2023-03-13 | ||
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draft-almprs-sustainability-insights-00
Network Working Group P. Andersson
Internet-Draft J. Lindblad
Intended status: Informational S. Mitrovic
Expires: 14 September 2023 M. Palmero
E. Roure
G. Salgueiro
Cisco Systems
13 March 2023
Sustainability Insights
draft-almprs-sustainability-insights-00
Abstract
This document motivates the collection and aggregation of
sustainability environmental related metrics. It describes the
motivation and requirements to collect asset centric metrics
including but not limited to power consumption and energy efficiency,
circular economy properties, and more general metrics useful in
environmental impact analysis. It provides foundations for building
an industry-wide, open-source framework for the reduction of
greenhouse gas emissions, enabling measurement and optimization of
the overall impact on the environment of networking devices, software
applications, services, and solutions across the lifecycle journey.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
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Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on 14 September 2023.
Copyright Notice
Copyright (c) 2023 IETF Trust and the persons identified as the
document authors. All rights reserved.
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This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents (https://trustee.ietf.org/
license-info) in effect on the date of publication of this document.
Please review these documents carefully, as they describe your rights
and restrictions with respect to this document. Code Components
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provided without warranty as described in the Revised BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. The Sustainability Telemetry Standard Specification . . . 4
1.2. Requirements language . . . . . . . . . . . . . . . . . . 7
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 7
3. Motivation . . . . . . . . . . . . . . . . . . . . . . . . . 7
4. Next Steps . . . . . . . . . . . . . . . . . . . . . . . . . 8
4.1. The Sustainability Framework . . . . . . . . . . . . . . 8
4.2. Further Development . . . . . . . . . . . . . . . . . . . 9
5. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . . 9
5.1. Use Case I . . . . . . . . . . . . . . . . . . . . . . . 9
5.1.1. Scenario . . . . . . . . . . . . . . . . . . . . . . 9
5.1.2. Sustainability Insights Added Value . . . . . . . . . 10
5.2. Use Case II . . . . . . . . . . . . . . . . . . . . . . . 10
5.2.1. Scenario . . . . . . . . . . . . . . . . . . . . . . 10
5.2.2. Sustainability Insights Added Value . . . . . . . . . 10
5.3. Use Case III . . . . . . . . . . . . . . . . . . . . . . 10
5.3.1. Scenario . . . . . . . . . . . . . . . . . . . . . . 10
5.3.2. Sustainability Insights Added Value . . . . . . . . . 11
5.4. Use Case IV . . . . . . . . . . . . . . . . . . . . . . . 11
5.4.1. Scenario . . . . . . . . . . . . . . . . . . . . . . 11
5.4.2. Sustainability Insights Added Value . . . . . . . . . 11
5.5. Use Case V . . . . . . . . . . . . . . . . . . . . . . . 11
5.5.1. Scenario . . . . . . . . . . . . . . . . . . . . . . 11
5.5.2. Sustainability Insights Added Value . . . . . . . . . 12
6. Deployment Considerations . . . . . . . . . . . . . . . . . . 12
7. Security Considerations . . . . . . . . . . . . . . . . . . . 13
8. References . . . . . . . . . . . . . . . . . . . . . . . . . 13
8.1. Normative References . . . . . . . . . . . . . . . . . . 13
8.2. Informative References . . . . . . . . . . . . . . . . . 14
Change log . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 14
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 15
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1. Introduction
To answer questions about how sustainable equipment and operational
practices are, various key performance indicators (KPIs) produced by
network devices, management systems, and networking solutions are
necessary. While such KPIs are abundantly produced and collected
today there are quite a few issues with their usability and
commonality. Without a common definition of metrics across the
industry and widespread adoption, we will be left with ill-defined,
potentially redundant, and proprietary metrics.
An aspect lacking today is the precise definitions of the collected
metrics. This leads to KPIs that are not comparable to each other,
as it is unknown what is included in the outcomes and what is not.
It makes it challenging to sum or compare numbers from different
manufacturers and organizations without investing in data
normalization and a high number of assumptions.
To produce aggregate data, it is also important to consider how the
component inputs are combined. Different vendors and operators might
do this aggregation differently, yet again producing values that are
hard to combine or compare when also using different units of
measurement. In many cases, one might suspect the actual numbers are
underestimated, since there is competitive pressure to produce small
numbers to report on the environmental impact of Internet
communications and applications in contrast with the benefit of using
it. The aim shall not be to "produce the numbers" but to find
quantitative measures, when possible, that give a fair assessment of
Sustainability related metrics vs. useful work.
It may be tempting to define the useful work in networking equipment
as simply as the number of bits that are passing through the device.
For some types of equipment, that might be appropriate, but clearly a
video system that is sending a video stream with better video
compression is not necessarily less sustaiable just because it sends
fewer bits per Joule. There are also many kinds of networking
equipment where measuring the end user value in number of passed bits
is obviously ridiculous, and other metrics have to be defined.
Monitoring or management systems are examples of this.
Another important and key aspect, when referring to environmental
impact metrics is what needs to be considered as part of the
lifecycle. Life cycle assessment, also known as LCA, of networks and
services, is defined by ISO 14040 as the compilation and evaluation
of the inputs, outputs, and potential environmental impacts
throughout its lifecycle.
LCA is based on four main phases:
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* Goal and Scope
* Inventory Analysis
* Impact Assessment
* Interpretation
This document is setting up the stage to identify data quality
requirements, under the information and communications technology
(ICT) category. Following product Lifecycle Accounting (LCA), this
document focuses on using the five product lifecycle stages defined
by the GHG Protocol Accounting and Reporting Standard, which is in
accordance with the ISO 14040:44 standards:
1. Use
2. Manufacturing
3. Material Acquisition / Processing
4. Transport
5. End of Life
Impact and interpretation will be briefly covered under the
document's motivation and use cases sections.
There is reason to suspect that nebulous definitions combined with
the competitive pressure might produce greenwashing. Greenwashing
involves making an unsubstantiated claim to deceive consumers into
believing that a vendor's product or solution is environmentally
friendly or has a greater positive environmental impact than it does.
This document proposes the following initiative to counter these
effects.
1.1. The Sustainability Telemetry Standard Specification
As an industry, we need to cooperate and agree on a set of core KPIs
that are measured, including the definition of terms, units, and
measurement procedures. What is included, and what is not included.
Sustainability metrics require a broad diversity of data sources that
need to be combined.
* Static information. Data coming from manufacturing, including
reference values on how the assets have been designed if they
enable reuse and recycling, and which materials have been used
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during manufacturing and packaging; normally this information is
defined once and it is part of data sheets provided by the
vendors.
* Dynamic data. Information measured in real-time or close to real-
time from the networking equipment or application. For instance,
metrics should consider current inventory and current source and
amount of consumed power, as well as what hardware and software
features are enabled and used by the specific network equipment.
* Best practices. Recommendations for optimizing the use of the
network equipment, throughout its complete lifecycle.
* Local context. Country-specific regulations, corporate policy,
and social aspects.
To enable the exchange of sustainability data among all interested
parties, deployment considerations that are out of the scope of this
document will need to include:
* Data models. The model definition can be implemented in different
forms. This document proposes YANG as part of the Specification
Data Model. YANG can be used independently of the transport and
can be converted into any encoding format supported by the network
configuration protocol. YANG models are decoupled from the
management protocol layer.
* Sustainability framework. To drive adoption, we propose an open-
source aggregation framework for sustainability data. This
framework should be seen as a reference architecture for a
sustainability monitoring mechanism. While each implementation
may be (and will be) different, the basic framework shall remain
constant. The framework must account for vendor-specific
calculations and enhacements in a plug-in architecture.
YANG data models as part of the Sustainability Telemetry
Specification, which will follow this document, have been classified
as follows:
* Identification of the assets. Assets include hardware (physical
as well as virtual), software, applications, and services. The
asset concept is defined in the Data Model for Lifecycle
Management and Operations (DMLMO)
[I-D.draft-palmero-opsawg-dmlmo-09] IETF draft.
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* Power and Efficiency. To measure power consumption and energy
efficiency, common methods, attributes, and units are needed to
define metrics. The approach needs to cover the different
networking domains, starting with hardware focus, but including
software and protocols attributes and metrics.
* Circular Economy attributes. Collecting circularity data (such as
materials used, or the embedded emissions footprint) is expensive
and difficult because of confidentiality and the non-standardized
approach to reporting and exchanging circularity data. The flow
of circularity data is typically lost at each step throughout the
supply chain, as goods are passed through suppliers,
manufacturers, system integrators, distributors, customers, and
consumers into reuse and recycling.
* Context metrics. Without understanding the context of the use,
none of the metrics listed above will provide much value. The
carbon intensity of the power used, for example, is key to
assessing the sustainability of a given application. An
efficiency number needs to be interpreted differently at peak
hours and night. A given user may be considered less sustainable
if someone demonstrates the ability to deliver the same end-user
value to a smaller footprint. A system that is transported a
shorter distance or using a more sustainable mode of
transportation from the factory to the installation site may also
be assessed more positively. Or if it has a longer economic life
or comes with less single-use packaging.
The model definition can be implemented in different forms. We would
like to propose a specific YANG model for the sustainability metrics,
which intrinsically allows for a variety of collection protocols.
YANG can be used independently of the transport protocol, and lends
itself well to be converted into a variety of encoding formats
supported by popular network configuration protocols.
The rest of this document is organized as follows. Section 2
establishes the terminology and abbreviations. Section 3 outlines
the goals and motivation of Sustainability metrics. Section 4
discusses Use Cases that lay out the groundwork for the
Sustainability Telemetry Specification, to address new business needs
introduced by the Circular Economy and to avoid excessive climate
change.
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1.2. Requirements language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in
BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all
capitals, as shown here.
2. Terminology
Terminology and abbreviations used in this document:
Asset Hardware, software, applications, or services. An asset can
be physical or virtual.
Greenwashing Marketing (intentionally or not) an asset as being
green (i.e. fitting well into the circular economy) by selectively
omitting less green aspects of the asset.
Circular economy An economic paradigm in which the full lifecycle
cost of resource use and emissions are included.
Climate change The disruption of ecological processes caused by
excessive resource use or emissions.
3. Motivation
Aside from the need for consistency on metrics to be considered as
part of the ICT sector, to reduce environmental impact and increase
benefit; this document and future work related, aim to support the
Digital Product Passport initiative under the European Union's (EU's)
Circular Economy Action Plan (CEAP) and the Ecodesign for Sustainable
Products Regulation (ESPR). There is not much time for businesses to
prepare and for IETF work to influence this development.
The Digital Product Passport (DPP) is key to the EU's transition to a
circular economy and will provide information about assets'
environmental sustainability. It aims to improve traceability and
transparency along the entire value chain of an asset and to improve
the management and sharing of product-related data which are critical
to ensuring their sustainable use, prolonged life, and circularity.
There is a need to:
* Track raw materials extraction/production, supporting due
diligence efforts
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* Enable manufacturers to increase transparency in the value chain,
better compliance, increased circularity, and sustainability
* Enabling services related to its remanufacturing, reparability,
second-life, and recyclability, enabling sustainable business
models.
In the case of upgrading, repairing, repurposing, or remanufacturing
a product, it should be clear the responsibility to update the
information is transferred to the installer, repairer, or
remanufacturer who will be putting the product into service or
placing it on the EU market.
The three main target groups of the passport are:
* Public authorities and policymakers: reliable information on
compliance of products with EU legislation
* Economic operators (such as recyclers): information on proper
dismantling and waste treatment of products; the presence of
Substances of Very High Concern (SVHCs) through a link to the SCIP
database; etc.
* Consumers: instructions for use, information on repair centers,
sorting instructions, and other information as required by
existing EU legislation (e.g. CLP regulations), more information
about products would be made available to consumers and customers
to enable informed choices.
The DPP will help business planners and consumers make informed
choices when purchasing assets, and should also help local and public
authorities to better perform checks and controls.
4. Next Steps
To enable the exchange of sustainability data among all interested
parties at each step of the value supply chain, a technical
sustainability framework for how this data is queried, transported,
and visualized will be required.
4.1. The Sustainability Framework
To drive quick adoption, we propose to build an open-source
aggregation framework for sustainability data. This framework should
be seen as a reference architecture for a sustainability monitoring
mechanism. The reference implementation will be based on the IETF
standards mentioned before. The architecture would supply a few base
components, but otherwise, allow vendors or standards bodies to
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plugin their applications that fit in the general framework. One
example of such an application that we would like to propose is a
model to calculate the Total Sustainability Cost of Ownership (TSCO)
for network solutions based on the Environmental, Social, and
Governance (ESG) Materiality Matrix. This matrix model is open to
adding any implementation that takes into consideration
Sustainability objectives at a point in time, but it also evolves
with the needs of the business and the stakeholders. The initial
scope proposes to investigate the top four most important ESG
Materiality issues as a base to grow the TCO to a TSCO that matches
the Company's priorities and issues.
4.2. Further Development
Items that are not in the scope of this edition of this document, but
could be addressed in future revisions, include:
* How to relate Sustainability Telemetry Specification to
sustainability Scopes 1, 2, and 3,
* Circular Economy Business models,
* Recommendations,
* Scope 4, i.e. metrics for avoided footprints (sometimes called
handprint). For instance, to reduce GHG emissions, automation
activities like Zero Touch, or certain technologies like Routed
Optical Networking, can replace other higher emitting activities.
Another example would be the positive impact arising from video
conferencing as opposed to international travel by airplane.
5. Use Cases
5.1. Use Case I
5.1.1. Scenario
An organization is running a large and complex network with many
types of devices. By looking at the utility bills, it is clear that
the organization is consuming rather more energy per transported bit
than many other organizations. Exactly which devices or network
functions are at the root of the situation is unclear, however.
The product LCA in this scenario applies to the stage of "Use".
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5.1.2. Sustainability Insights Added Value
By providing near-real-time data that is broken down at least to an
individual hardware device, and ideally considerably deeper than
that, it will be possible to attribute energy and environmental
footprint costs to different device types, service types, and
individual customers.
If one customer is altering its behavior or load on the network, a
monitoring application could detect this quickly. It would also be
possible to try several implementations or configurations for a given
service and get quick feedback on the operations cost of that change.
5.2. Use Case II
5.2.1. Scenario
An organization is running a network with a variety of managed
services and applications. Some of the devices are getting old, and
have lower energy efficiency than more modern devices. Replacing old
devices with new ones might improve efficiency, but has an economical
as well as environmental cost. Without specific performance data, it
is difficult to make informed decisions about upgrades.
The product LCA stage applies to "Use".
5.2.2. Sustainability Insights Added Value
By providing KPIs for reading sustainability parameters that pertain
to actual usage, rather than numbers from data sheets, the accuracy
of upgrade decisions is enhanced. Such data can make the case for an
upgrade very clear and easy to make, or it may show that it's not a
good idea at this time. In both cases improving the sustainability
of the operations.
5.3. Use Case III
5.3.1. Scenario
Recycling and reuse are major drivers of the circular economy.
Companies must put high efforts in this direction and transparency.
This is a qualitative KPI, passed if percentages of recycled and
reused goods given the manufacturing options, as well as reports
listing how many units have been recycled.
The product LCA applies to the stage of "Material Acquisition /
Processing".
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5.3.2. Sustainability Insights Added Value
The trend seems to be to report on the percentage of recycled user
devices and the eco-design and refurbishment efforts. Sustainability
Insights can enable the data sources to report comprehensive
reporting of recycling efforts.
5.4. Use Case IV
5.4.1. Scenario
An organization is running a network with a variety of managed
services and applications. The network and application performance
is continuously monitored, and there are even some automatic
remediation actions that may trigger when certain conditions are
detected.
In this scenario, the product LCA applies to the stage of "Use".
5.4.2. Sustainability Insights Added Value
By providing KPIs for sustainability parameters such as power
consumption and power efficiency, the monitoring system can access
relevant data and perform actions that reduce the power consumption
or sustainability footprint of the delivered services.
For example, some overly redundant links or systems may be powered
off at night, or enter into a low-power mode. A highly available
application may be configured to take more load in the data center
with a lower price of energy, lower outside temperatures, or an
environmentally superior energy mix.
5.5. Use Case V
5.5.1. Scenario
IT solutions are currently analyzed from two main perspectives:
technological and economical. When looking at environmental, social,
and corporate governance (ESG) impact topics, sustainability metrics
in the context of digital transformation, deliver insights into
opportunities and risks that emerge from a rapidly growing
stakeholder demand for sustainable, digitally advanced products and
services.
The product LCA applies to all stages under the product LCA.
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5.5.2. Sustainability Insights Added Value
From an application point of view, this use case proposes to include
Sustainability factors in the Total Cost of Ownership (TCO)
calculation, where there is a need to add Environmental, Social, and
Governmental Key Performance Indicators (KPIs) to the analysis.
However, adding Sustainability metrics comes with challenges and
trades-off. Future work considers a model to calculate the Total
Sustainability Cost of Ownership (TSCO) for network solutions based
on the ESG Materiality Matrix. This model is open to adding any
implementation that takes into consideration Sustainability
objectives at a point in time, but it also evolves with the needs of
the business and the stakeholders. The initial scope proposes to
investigate the top four most important ESG Materiality issues as a
base to grow the TCO to a TSCO that matches the Company's priorities
and issues.
Future work might include use cases that will cover "Manufacturing",
"Transport" and "End of Life" examples.
6. Deployment Considerations
Sustainability Data Models defines the data schemas for
Sustainability Insights data. Sustainability Insights Data Models
are based on YANG. YANG data models can be used independently of the
transport protocols and can be converted into any encoding format
supported by the network configuration protocol. YANG is protocol
independent.
To enable the exchange of Sustainability Insights data among all
interested parties, deployment considerations that are out of the
scope of this document will need to include:
* The data model definition
* The data structure to describe all metrics and quantify relevant
data consistently, i.e. specific formats like XML or JSON encoded
messages would be deemed valid or invalid based on Sustainability
Insights models.
* The process to share and collect Sustainability Insights data
across the consumers consistently, including the transport
mechanism. The Sustainability Insights YANG models can be used
with network management protocols such as NETCONF [RFC6241],
RESTCONF [RFC8040], streaming telemetry, etc. OpenAPI
specifications might also help to consume Sustainability Insights
metrics.
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* How the configuration of assets to implement Sustainability
Insights telemetry should be done.
It will be important to consider where, when, and how often the data
will need to be collected. As per the specification of the data,
data might need to be collected from different data sources: network
devices, and different databases where manufacturing information is
stored and maintained. Ideally all this information can be extracted
via a well-defined API. The frequency to collect the data will also
vary, for instance, comparing manufacturing data with runtime data.
For example, it might be a good practice to collect inventory data
once per day, while "environmental" data might need to be updated
hourly or even more frequently. It will also be important to
consider the platform from where data might be collected, and the
need to properly correlate all the information.
7. Security Considerations
The security considerations mentioned in section 17 of [RFC7950]
apply.
Sustainability Insights brings several security and privacy
implications because of the various components and attributes of the
information model. For example, each functional component can be
tampered with to give manipulated data. Sustainability Insights when
used alone or with other relevant data, can identify an individual,
revealing Personal Identifiable Information (PII). Misconfigurations
can lead to data being accessed by unauthorized entities.
Methods exist to secure the communication of management information.
The transport entity of the functional model MUST implement methods
for secure transport. This document also contains an Information
model and Data-Model in which none of the objects defined are
writable. If the objects are deemed sensitive in a particular
environment, access to them MUST be restricted using appropriately
configured security and access control rights. The information model
contains several optional elements which can be enabled or disabled
for the sake of privacy and security. Proper authentication and
audit trail MUST be included for all the users/processes that access
Sustainability Insights Telemetry Data.
8. References
8.1. Normative References
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[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
May 2017, <https://www.rfc-editor.org/info/rfc8174>.
8.2. Informative References
[I-D.draft-palmero-opsawg-dmlmo-09]
Palmero, M., Brockners, F., Kumar, S., Bhandari, S.,
Cardona, C., and D. Lopez, "Data Model for Lifecycle
Management and Operations", Work in Progress, Internet-
Draft, draft-palmero-opsawg-dmlmo-09, 17 January 2023,
<https://datatracker.ietf.org/doc/html/draft-palmero-
opsawg-dmlmo-09>.
[RFC6241] Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
and A. Bierman, Ed., "Network Configuration Protocol
(NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,
<https://www.rfc-editor.org/info/rfc6241>.
[RFC7950] Bjorklund, M., Ed., "The YANG 1.1 Data Modeling Language",
RFC 7950, DOI 10.17487/RFC7950, August 2016,
<https://www.rfc-editor.org/info/rfc7950>.
[RFC8040] Bierman, A., Bjorklund, M., and K. Watsen, "RESTCONF
Protocol", RFC 8040, DOI 10.17487/RFC8040, January 2017,
<https://www.rfc-editor.org/info/rfc8040>.
Change log
RFC Editor Note: This section is to be removed during the final
publication of the document.
version 00
* Initial version of the draft.
Acknowledgments
This document was created by meaningful contributions from Jeff
Apcar, Klaus Verschure and Suresh Krishnan.
The authors wish to thank them and many others for their helpful
comments and suggestions.
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Authors' Addresses
Per Andersson
Cisco Systems
Email: perander@cisco.com
Jan Lindblad
Cisco Systems
Email: jlindbla@cisco.com
Snezana Mitrovic
Cisco Systems
Email: snmitrov@cisco.com
Marisol Palmero
Cisco Systems
Email: mpalmero@cisco.com
Esther Roure
Cisco Systems
Email: erourevi@cisco.com
Gonzalo Salgueiro
Cisco Systems
Email: gsalguei@cisco.com
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