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View All on GitHubEnrichment pipeline for CUR / FOCUS reports which adds energy, water and carbon estimates
AI Summary: Implement carbon emission calculations for cloud storage (HDD and SSD) in the Carbonara project, using energy consumption data and formulas provided by CloudCarbonFootprint. This involves adding new logic to the existing Apache Spark job to process storage usage data from AWS CUR reports and calculate corresponding CO2 emissions.
Enrichment pipeline for CUR / FOCUS reports which adds energy, water and carbon estimates
AI Summary: Add SPDX license headers (specifically `// SPDX-License-Identifier: Apache-2.0`) to all source code files within the Carbonara project to ensure proper license attribution.
Enrichment pipeline for CUR / FOCUS reports which adds energy, water and carbon estimates
AI Summary: Implement a new module in the Carbonara project to estimate Power Usage Effectiveness (PUE) values. This module should integrate data from the Green Software Foundation's Real-time Cloud dataset (specifically, Cloud_Region_Metadata.csv) to provide accurate PUE estimates for enriching AWS CUR reports. The module should be designed to seamlessly integrate into the existing Apache Spark-based pipeline.
Enrichment pipeline for CUR / FOCUS reports which adds energy, water and carbon estimates
Enrichment pipeline for CUR / FOCUS reports which adds energy, water and carbon estimates
AI Summary: Implement a configuration mechanism for the Carbonara project's enrichment modules, allowing users to specify which modules to use, their order, and their parameters via a YAML configuration file. The configuration should be easily accessible within the Spark job and ideally leverage existing configuration management techniques.
Enrichment pipeline for CUR / FOCUS reports which adds energy, water and carbon estimates