2024.11.19

[seanmcilroy29]

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2024.11.19 Agenda/Minutes

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Time 0800 (PT) / 1600 (BST) - See the time in your timezone

• Chair – Adrian Cockcroft
• Chair - Pindy Bhullar (UBS)
• Convener – Sean Mcilroy (Linux Foundation)

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Antitrust Policy

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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

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Discussion

• Finalize the approach and accurately represent data regarding renewable energy procurement and on-site generation.
• Review the Python script and provide feedback in the dev branch.
• Investigate updating the 2023 data in the baseline using the new WattTime data.

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Issues

Nothing to review

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Next Steps

• Key areas for the project to focus on.

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Ref Material

• GSF Real-Time Cloud Renewable Energy Percentage spreadsheet
• RTC Cloud Region Impact Framework Documentation
• miro dataflow in detail
  • Continue to review and approve the proposed Scope.

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AOB

• Topics added during the meeting

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Next Meeting

• 03rd Dec

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Action Items

• @sean Mcilroy - Organize a discussion with representatives from Google and Microsoft to help define a standardized approach for representing the data.
• Review the Python script and provide feedback in the dev branch.
• Investigate updating the 2023 data in the baseline using the new WattTime data.

[seanmcilroy29]

Attended

[PindyBhullar]

Attended

[seanmcilroy29]

Next Year Data Estimation -
https://chatgpt.com/share/6726127b-3274-8009-a387-a3d80ba653f1

Changes Made:
Sorting: The script now sorts next_year_df by cloud-provider and cloud-region using sort_values before saving it to a CSV file.
Order Preservation: This sorting step ensures that the output file is ordered according to cloud-provider first and then cloud-region.
How It Works:
next_year_df.sort_values(by=['cloud-provider', 'cloud-region']) ensures that the data is organized, making it easier to analyze or further process.

[seanmcilroy29]

Summary Meeting Notes

The team discussed the importance of ensuring data accuracy for renewable energy procurement and generating predictions for 2024 and 2025. Adrian shared his code generation process and emphasized the need for validation to maintain data integrity. Chris highlighted the significance of public datasets for assessing regional sustainability metrics.

Mintues

Discussion on Renewable Energy Data and Python Script Review
Sean recaps the previous week's discussions, including finalizing the approach and accuracy for renewable energy procurement data. Adrian suggests waiting until next year to update the 2023 baseline data to include 2024 predictions.
Adrian discusses generating a 2025 data set based on predictions and the importance of collective wisdom in estimating data. Chris raises concerns about interpolation issues leading to negative values and suggests adding validation to ensure data stays within expected ranges.

Discussion and Data Validation
Adrian shares his code for linear interpolation and highlights the need to refine it for more accurate data representation. Chris suggests creating a transcript to enhance understanding and validation. Adrian explains how to share discussions from ChatGPT and promises to create an issue for it.

European Data Sources and AWS Sustainability Efforts
Chris provided updates on European data sources, noting that some countries are slower than others in publishing their data. Sean and Adrian discussed reaching out to a presenter who had shared a presentation on European data, but they have not yet received a response. Adrian mentioned his blog post criticizing AWS for not releasing new data since 2021 and for the lack of recent sustainability-related announcements. Sean and Adrian also talked about the possibility of having someone attending the AWS conference provide updates on new data.

Future Data Releases and GPU Data Collection
Adrian discusses the process for generating estimates for the 2024 and 2025 data, emphasizing the importance of properly marking these estimates. Chris asks about how to merge new data with existing CSV files and confirms that this can be done without formal approval. Adrian also highlights the potential for collecting GPU data from VISTA and stresses the need to monitor energy consumption related to GPUs. Additionally, Sean and Adrian talk about the significance of public data sets for regional information and the opportunity to share this data with the Green Web Foundation.

Meeting Conclusion and Personal Updates
Sean summarizes the key discussion points and expresses anticipation for upcoming data releases. Chris confirms that the CSV data will be publicly available and highlights its potential benefits for the Green Web Foundation's work. Adrian proposes discussing the project on a podcast in the upcoming year. Pindy agrees to assist with the summary for GSF and shares updates on her family's health as well as the weather conditions in Weymouth and California.

Action Items

• Adrian - Share the transcript of the discussion with ChatGPT to get feedback on the code generation approach

See - #72