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Expand Up @@ -17,8 +17,10 @@ We provide the traces as they are, but are willing to help researchers understan
* Traces ([2019](https://github.com/Azure/AzurePublicDataset/blob/master/AzureFunctionsDataset2019.md)) for the paper "Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider" (ATC'19)
* Traces ([2020](https://github.com/Azure/AzurePublicDataset/blob/master/AzureTracesForPacking2020.md)) for the paper "Protean: VM Allocation Service at Scale" (OSDI'20)
* Traces ([2020](https://github.com/Azure/AzurePublicDataset/blob/master/AzureFunctionsBlobDataset2020.md)) for the paper "Faa$T: A Transparent Auto-Scaling Cache for Serverless Applications" (SoCC'21)
* Traces ([2022](https://github.com/Azure/AzurePublicDataset/blob/master/AzureFunctionsDataset2019.md)) for the paper "INFless: A native serverless system for low-latency, high-Throughput inference" (ASPLOS'22)
* Traces ([2023](https://github.com/Azure/AzurePublicDataset/blob/master/AzureLLMInferenceDataset2023.md)) for the paper "Splitwise: Efficient generative LLM inference using phase splitting" (ISCA'24)
* Dataset and code ([2023](AzureGreenSKUFramework2023.md)) for the paper "Designing Cloud Servers for Lower Carbon" (ISCA'24)
* Traces ([2024](https://github.com/Azure/AzurePublicDataset/blob/master/AzureFunctionsDataset2019.md)) for the paper "Flame: A Centralized Cache Controller for Serverless Computing" (ASPLOS'24)
* Traces ([2024](https://github.com/Azure/AzurePublicDataset/blob/master/AzureLLMInferenceDataset2024.md)) for the paper "DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency" (HPCA'25)
* Cloud Benchmarks ([2024](https://github.com/Azure/AzurePublicDataset/blob/master/AzureVMNoiseDataset2024.md)) for the paper "TUNA: Tuning Unstable and Noisy Cloud Applications" (EuroSys'25)

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