## Dataset Description This dataset includes system metrics (anonymised) such as CPU and memory utilisation, as well as hard drive metrics from [SMART (Self-Monitoring, Analysis, and Reporting Technology)](https://en.wikipedia.org/wiki/S.M.A.R.T.). The dataset contains 20 feature columns, details of which are provided in Table below. | SN | Metrics Name | Description | | ---- | ------------------ | ----------------------------------- | | 1 | CPU utilisation | Host CPU usage in %. | | 2 | Memory utilisation | Memory usage in bytes | | 3 | IO utilisation | IO usage in time | | 4 | Network overhead | Network usage in bytes | | 5 | Bits read | Data written out from disk in bytes | | 6 | Bits write | Data written into disk in bytes | | 7 | Smart 188 | Command time out | | 8 | Smart 197 | Current pending sector count | | 9 | Smart 198 | Uncorrectable sector count | | 10 | Smart 9 | Power-on hours | | 11 | Smart 1 | Read error Rate | | 12 | Smart 5 | Reallocated sectors count | | 13 | Smart 187 | Reported uncorrectable errors | | 14 | Smart 7 | Seek error rate | | 15 | Smart 3 | Spin up time | | 16 | Smart 4 | Start/stop count | | 17 | Smart 194 | Temperature | | 18 | Smart 199 | UltraDMA CRC error count | | 19 | Time | Timestamp | | 20 | id | Anonymised server | ------ #### Directory structure - Root - README.md - anonymised.py - The code used for anonymisation. - *data* - The directory that contains the actual data (total 101 files). ------ #### Data distribution The table below provides the overall summary of the data (i.e., the data distribution in terms of mean and standard deviation). ![data_distribution](/Users/tekrajchhetri/Downloads/anonymised data/data_distribution.png) ------ #### Citing If you find this data useful, please consider citing: ~~~latex ``` @article{chhetri2021combined, title={A Combined Metrics Approach to Cloud Service Reliability using Artificial Intelligence}, author={Chhetri, Tek and Dehury, Chinmaya Kumar and Lind, Artjom and Srirama, Satish Narayana and Fensel, Anna}, year={2021}, publisher={Preprints} doi={\url{https://www.preprints.org/manuscript/202111.0548/v1}} } ``` ~~~