2024.10.24

[seanmcilroy29]

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2024.10.24 Agenda/Minutes

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Time 1600 (BST) - See the time in your timezone

• Co-Chair - Henry Richards (WattTime)
• Co-Chair - Naveen Balani - (Accenture)
• Convener – Sean Mcilroy (Linux Foundation)

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Recordings

WG agreed to record all Meetings. This meeting recording will be available until the next scheduled meeting.

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Roll Call

Please add 'Attended' to this issue during the meeting to denote attendance.

Any untracked attendees will be added by the GSF team below:

• Full Name, Affiliation, (optional) GitHub username

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Agenda

• Approve agenda
• Approve previous Meeting Minutes

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Use Case Review (20 Mins presentation with Q&A)

• Amadeus - Carman Use Case - Florent Morel & Robin Castellon

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SCI for AI - Defining the workshop - Navveen and Henry

• Workshop framework
• What issues do we want to address?
• What are the desired outcomes?
• What are the key deliverables?
• What would success look like?
• Who needs to be involved?

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Project Review updates

• Real-Time Cloud
  - Next Steps:
  • Reach out to the EU database project to follow up on the European Union's Energy Efficiency Directive plan to be published.
  • Project members are to review the project in six months with the objective of submitting it to ISO.
• Software Carbon Efficiency Rating Chris Xie (Futurewei) - Chris (Futurewei)
• New baseline under review
• Transforming Organisational Software Sustainability
  • Last meeting workshop members joined to review updates - Pindy (UBS)/ Sean (Microsoft)
  • 22nd Oct - Project members review implementation pillar.
  • 02nd Nov - Review updates to the implementation pillar with the invited Workshop members
• sci-guide - Navveen (Accenture)

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Articles

• nothing to review

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For Review

• Nothing to review

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Note:
WG use case template submission - After submitting this issue, your use case will be submitted to the WG Agenda for discussion.
Article submission—Once you submit this issue, it will be assigned to the GSF Editor for review.

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Future meeting Agenda submissions

• If you have any Agenda submissions, please let Sean know via email at [email protected] or open an Issue

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Next Meeting

• 07th Nov
• Agenda submission for next meeting - Amadeus - Carman Use Case - Beniot Faurie

Reminder Note:
Eur - Daylight saving ends on 27th Oct 2024
US - Daylight saving ends on 3rd Nov 2024

Adjourn

• Motion to adjourn

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Standing Agenda / Future Agenda submissions

• Standing Agenda Item: The First meeting of each month is a member Introduction / Buddy-buddy meeting to help new members understand the work in the SWG.
• Standing Agenda Item - First meeting of each month - 5 - 10 min round up of what is happening across the other WG

[GadhuNTTDATA]

Attended

[Henry-WattTime]

Attended

[jmcook1186]

Attended

[navveenb]

Attended

[filga]

Attended

[sami-gharbi]

Attended

[PindyBhullar]

Attended

[sasthana-tw]

Attended.

[seanmcilroy29]

MoM

Henry opens the meeting at 1600 (BST)

Summary Notes

The meeting focused on Amadeus' implementation of the Impact Framework for green IT, highlighting their MVP for carbon emissions measurement in Microsoft Azure. They manage 10,000 software engineers across ten countries, with 200 applications and 200 clusters. Their solution, Carmen, leverages the Impact Framework to compute CO2 and energy consumption, with a 15-second granularity for application telemetries and hourly for infrastructure. Challenges include handling shared resources and allocating costs to services. The team discussed future steps, including a potential AI emissions measurement and collaboration with the GSF for a workshop to develop the SCI standard for AI.

Minutes

Amadeus' Green IT Implementation
Speaker 2 describes Amadeus' transition from a private data centre to the cloud, primarily using Microsoft Azure and Google Cloud. The organization has hundreds of clusters in 10 countries and 10,000 software engineers. The challenge is to adopt green IT practices at a large scale, to have an SEI for each application. An MVP was implemented to present carbon emissions for applications deployed in Microsoft Azure.

Introduction to Carmen
The Amadeus team introduces Carmen, a branded solution leveraging the impact framework to centralize carbon measurement services. Carmen consumes application telemetries and infrastructure data to compute CO2 and energy. The solution includes monitoring carbon as a service and reporting use cases. Carmen aims to avoid re-implementing the impact framework for each application, focusing on reusability and efficiency.

Carmen's Use Cases and Demonstration
Amadeus's team explains the three use cases: monitoring, carbon as a service, and reporting. The monitoring use case is based on real-time data, while the reporting use case focuses on long-term decision-making. A demo shows the pipeline for infrastructure-based reporting, which involves gathering data, computing energy and carbon, and reallocating to services. The demo highlights the scale of the data involved, with over 30,000 virtual machines and 1.6 million lines of impact framework output.

Challenges and Future Steps
Amadeus's team outlines the following steps, including taking the MVP dashboard towards a product and implementing non-functional requirements. The Finops use case and measurement as a service are discussed, with plans to integrate carbon intensity APIs. The goal is to implement a carbon-aware scheduler for time and spatial shifting by 2025. Amadeus requests collaboration with the GSF to pilot the impact framework integration and share feedback.

Discussion and Questions
Asim congratulates the team on their work and asks about the time granularity for computing emissions. Amadeus's team explains the granularity, with hourly data for infrastructure and 15-second data for application telemetries. Henry inquires about user feedback, and Amadeus's team mentions that users are eager to use the tool despite it being an MVP. Naveen asks if AI emissions are being measured, and Amadeus's team clarifies that they focus on machine learning for their processes.

Scalability and Allocation Challenges
Gadhu asks about handling shared resources, and the Amadeus team explains the reallocation process from infrastructure to service level. Asim questions the allocation methodology, and Amadeus's team describes using the Finops library for reallocation. The discussion discusses the challenges of allocating costs and emissions to customers and the need for a technical solution. Joseph offers to help Amadeus migrate to the latest version of the impact framework for better performance.

Key considerations and challenges in allocating carbon emissions to customers and services:

• Shared resources: When a single resource (e.g., a VM, database) is used by multiple applications or services, it can be challenging to accurately allocate the associated carbon emissions to each individual user or service.
• Granularity of data: The level of granularity in the carbon emissions data (e.g., hourly, daily) can impact the accuracy and usefulness of the allocation to customers and services.
• Complexity of commercial models: The commercial models and pricing structures used to sell managed services to customers may not align neatly with the carbon emission allocation, making it difficult to pass on the emissions to customers directly.
• Lack of standardized approaches: There is currently no widely adopted standard or best practice for how to allocate carbon emissions to customers and services. Organizations may use different methodologies, making it difficult to compare or aggregate across the industry.
• Technical limitations: The ability to accurately measure and attribute carbon emissions to specific applications, services, or customers may be limited by the available data and tooling.
• Organizational challenges: Allocating carbon emissions may require coordination and alignment across different teams and business units, which can be organizationally complex.

The Amadeus team highlighted that they are currently facing these challenges and are working to find technical and organizational solutions to address them, potentially in collaboration with the broader community.

Workshop Planning and Next Steps
Due to time constraints, Henry suggests postponing the AI SCI workshop discussion to the next meeting. Asim proposes that the GAIC and standards working group jointly decide on workshop participants and selection criteria. The overarching goal of the workshop is to define the scope and functional unit for the SCI standard for AI. Russ shares a document with questions and suggestions for the workshop, and Henry suggests sharing it with the standards working group for feedback.

SCI workshop to define the scope and functional unit for the SCI standard for AI:

• Clearly define the problem statement and critical challenges the SCI standard for AI aims to address. This will help focus the workshop discussions.
• Determine whether there should be a single functional unit for AI in general or if multiple functional units are needed for different classes or archetypes of AI systems. This decision should consider factors like model size, accuracy, and other relevant parameters.
• Ensure the workshop has AI and standards experts representation. This cross-pollination of expertise will be crucial for defining the appropriate scope and functional unit.
• Prioritize high-level consensus on the key elements rather than getting bogged down in detailed wordsmithing. The baseline specification can be iteratively refined after the workshop.
  Leverage existing work, such as the base SCI specification and the previous discussions from the Green AI Committee, as a starting point to build upon.
• Prepare pre-read materials and research papers to help inform the workshop discussions and ensure participants are aligned on the field's current state.

The goal should be to produce a baseline SCI specification for AI that can serve as the community's foundation for further development and refinement.

Action Items

• Collaborate with the GSF on piloting the Amadeus Impact Framework integration and provide feedback.
• Share the document with meeting notes and proposed workshop plan with the Standards Working Group chairs and a representative from the Green AI Committee.
• Condense the notes from today's meeting and the previous session into a single document as the source of truth.