| license: cc-by-nc-4.0 | |
| tags: | |
| - root cause analysis | |
| - microservice system | |
| - multi-modal learning | |
| - time series analysis | |
| - log analysis | |
| pretty_name: Cloud Computing Data | |
| size_categories: | |
| - 100M<n<1B | |
| task_categories: | |
| - time-series-forecasting | |
| ## Data Description: | |
| Preprocessed system metrics and log data from Cloud Computing Platform. | |
| Constructed the metric time series (as npy format) from the original metrics data (Json format). | |
| Extracted the log messages from the original log data (Json format). Parsed the log messages into log event templates. | |
| Note: 20240207 data does not contain EKS log data; it solely comprises CloudTrail log data in CSV format. Consequently, this dataset does not require preprocessing with a log parser. | |
| ## Timezone Note (Important) | |
| PPTX scenario slides use Japan Standard Time (JST) for measurement periods and failure timestamps, because the real testbed is located in Japan and failures were recorded locally. | |
| All metric and log data are timestamped in UTC. | |
| This means there is a 9-hour offset between the PPTX timestamps and the data files. | |
| For example: | |
| 11:30 JST → 02:30 UTC | |
| When aligning ground truth with the metric/log data, please convert all PPTX times from JST to UTC. | |
| ## Citation: | |
| Lecheng Zheng, Zhengzhang Chen, Dongjie Wang, Chengyuan Deng, Reon Matsuoka, and Haifeng Chen: LEMMA-RCA: A Large Multi-modal Multi-domain Dataset for Root Cause Analysis. CoRR abs/2406.05375 (2024) | |
| ## License: | |
| cc-by-nd-4.0: NoDerivatives. |