00 - Green Software Foundation Principles: Carbon Efficiency for Devs
Green Software Foundation core principles: carbon efficiency, energy efficiency and carbon awareness for developers.
Green Software Engineering
Green software: carbon-aware computing, energy-efficient algorithms, SCI (Software Carbon Intensity), sustainable cloud architecture e strumenti per misurare l'impatto ambientale del codice.
10Articles
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Titres et sous-titres
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Chapitres
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Annexes
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Bibliographie236 minLecture totaleIntermedioNiveau
Green Softwarecarbon-awaresustainabilitySCIenergy efficiency
Articoli de la Série XPHX0XPHX Les articles de la série XPHX1XPHX sont les suivants :
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01 - Measuring Your Code's Carbon Footprint with CodeCarbon
Using CodeCarbon to measure code CO2 emissions: setup, tracking, dashboard and optimization.
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02 - Integrating the Climatiq API: Carbon Calculations in Your Backend
Integrating Climatiq REST API for GHG Protocol emissions calculations: Scope 1-3, activity-based estimation and reporting.
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03 - Carbon Aware SDK: Time-Shift & Location-Shift Compute Workloads
Using the Carbon Aware SDK to shift workloads to low carbon intensity times and regions.
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04 - Scope 1, 2 & 3 Emissions: Data Modeling for ESG Software
Data modeling for Scope 1, 2, 3 emissions: data structure, calculations, aggregation and compliant ESG reporting.
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05 - GreenOps: Carbon-Aware Infrastructure with Kubernetes
Implementing GreenOps with Kubernetes: carbon-aware scheduling, emission-based scaling and real-time monitoring.
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06 - Building a Scope 3 Value Chain Emissions Pipeline
Building pipelines for Scope 3 value chain emissions tracking: supplier data collection, calculation and audit trail.
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07 - ESG Reporting APIs: Integrating with CSRD Compliance Workflows
APIs for CSRD-compliant ESG reporting: workflow integration, report automation and European directive compliance.
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08 - Sustainable Architecture Patterns: Storage, Caching & Batch Jobs
Architecture patterns for sustainable software: storage optimization, smart caching and carbon-aware batch scheduling.
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09 - AI & Carbon: Measuring and Reducing ML Training Footprint
Quantifying and reducing ML training carbon footprint: measurement tools, optimization techniques and best practices.
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