| --- |
| 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. |
