# de-p1st-monitor ## Research See [./research](./research). - HDD temp: - Modern hard drives will throttle their read and write speeds when the drive reaches a critical pre-set temperature (usually around 60°C) - 20-50°C (short-term) - 20-40°C (long-term usage) - SSD temp: - Most SSDs implement thermal throttling as a safety feature if a drive gets too hot. As the driver approaches the 70ºC limit that most manufacturers set, the more likely it is that the drive will start to slow itself down to prevent failure. - 30-50°C ## Keep it simple! Lines of code including docstrings and comments: ```shell find ./src -name '*.py' | xargs wc -l #=> 1625 total ``` ## Configuration See [yodaTux.ini](src/de/p1st/monitor/data/yodaTux.ini) for a configuration file covering all config options. ## Installation The package is available on [PyPI](https://pypi.org/project/de.p1st.monitor). There are two system dependencies which are required for some config options: `smartmontools` and `digitemp`. Furthermore, the kernel module `drivetemp` is required: `sudo modprobe drivetemp` ## Installation with cron entry Install dependencies on Ubuntu: ```shell sudo apt-get install python3-pip # Ubuntu 18.04 and below sudo apt-get install python3-setuptools sudo apt-get install python3-wheel sudo apt-get install python3-psutil # Ubuntu 18.04 and below: psutil < 5.6.2 sudo apt-get install python3-dev sudo apt-get install build-essential # Ubuntu 20.04 and below: psutil < 5.6.2 sudo python3 -m pip install psutil --upgrade ``` Install: - Arch Linux: `make install-pkgbuild` - pip: `make install-pip` ## Usage ### Command line interface ``` usage: de-p1st-monitor [-h] [--config CONFIG] [--export] Iterates over all config sections. For each section the current sensor data is read and logged to a .csv file. options: -h, --help show this help message and exit --config CONFIG, -c CONFIG Path to .ini configuration file. --export, -e If `True`, export .csv files and print their paths to stdout. No sensor data is logged during this. ``` ### Periodic logging Add a cron entry executing this e.g. every 3 Minutes: ```shell de-p1st-monitor ``` ## Example log files ```shell ssh nas 'tail -n 1 /var/log/de-p1st-monitor/*' ``` ``` ==> /var/log/de-p1st-monitor/cpu_15min.csv <== 20230712T101202,0.1351318359375 ==> /var/log/de-p1st-monitor/cpu_1min.csv <== 20230712T101201,0.2215576171875 ==> /var/log/de-p1st-monitor/cpu_5min.csv <== 20230712T101201,0.155517578125 ==> /var/log/de-p1st-monitor/drive_20d86155-30d4-404c-95e8-c701cfb16ca5.csv <== 20230712T101202,27 ==> /var/log/de-p1st-monitor/drive_4651c3f1-e4b8-45aa-a823-df762530a307.csv <== 20230712T101202,27 ==> /var/log/de-p1st-monitor/drive_68c349e8-5118-4773-9fd5-5dbad9acee4e.csv <== 20230712T101202,30 ==> /var/log/de-p1st-monitor/drive_b8ef1da9-d76d-44b4-86d4-71c82c888b6f.csv <== 20230712T101202,42 ==> /var/log/de-p1st-monitor/filesystem_3CBA-B4EA.csv <== 20230712T101201,0.22699999999999998 ==> /var/log/de-p1st-monitor/filesystem_a454430b-dee3-4b6b-8325-f7bdb9435ed1.csv <== 20230712T101201,nan ==> /var/log/de-p1st-monitor/filesystem_b8ef1da9-d76d-44b4-86d4-71c82c888b6f.csv <== 20230712T101201,0.28300000000000003 ==> /var/log/de-p1st-monitor/filesystem_c385a436-0288-486f-a2b9-c64c2db667e7.csv <== 20230712T101201,0.397 ==> /var/log/de-p1st-monitor/memory.csv <== 20230712T101201,3331,7434,7966 ==> /var/log/de-p1st-monitor/net_enp0s31f6.csv <== 20230712T101202,34945986870,32771833466,20230706T100247 ==> /var/log/de-p1st-monitor/net_enp0s31f6.csv.exported.csv <== 20230619T203731,68129.75690607735,67623.71270718232 ==> /var/log/de-p1st-monitor/sensor_script_room-temp.csv <== 20230712T101202,26.19 ==> /var/log/de-p1st-monitor/swap.csv <== 20230712T101201,2375,32767 ==> /var/log/de-p1st-monitor/temp_coretemp_Core 0.csv <== 20230712T101202,33.0 ==> /var/log/de-p1st-monitor/temp_coretemp_Core 1.csv <== 20230712T101202,39.0 ==> /var/log/de-p1st-monitor/temp_coretemp_Package id 0.csv <== 20230712T101202,39.0 ``` ## Plots ### Creating plots with graph-cli 1) Export and fetch data ```shell ssh_target=rootYodaNas dst=~/de-p1st-monitor-"${ssh_target}" files="${dst}".files # Export .csv files on SSH target and save list of exported files to $files. ssh "${ssh_target}" 'de-p1st-monitor --export' > "${files}" rm -rf "${dst}" mkdir -p "${dst}" rsync --checksum --archive --progress --human-readable --delete \ --files-from="${files}" "${ssh_target}":/ "${dst}" mv "${dst}"/var/log/de-p1st-monitor/* "${dst}" rm -r "${dst}"/var "${files}" cd "${dst}" ``` 2) Install (Python) `graph-cli` ```shell # With a Python venv: #python -m venv ~/de-p1st-monitor.venv #source ~/de-p1st-monitor.venv/bin/activate #pip install graph-cli # With nix: nix-shell -p graph-cli ``` 3) Create plots Create one plot for each .csv file with different resampling methods (https://pandas.pydata.org/pandas-docs/stable/reference/resampling.html#computations-descriptive-stats): ```shell function plot(){ for file in "${@}"; do graph "${file}" -x 1 --resample "${sample_duration}" --resample-action "${action}" --figsize 1600x1000 -o "${file}".resample-"${sample_duration}-${action}".png || { echo "Error while processing ${file}" } done } # MEAN sample_duration=24H action=mean plot {swap,memory}.csv {temp_,cpu_,sensor_script_}*.csv # MAX sample_duration=24H action=max plot {swap,memory}.csv {temp_,drive_,drive-temp_,net_,cpu_,filesystem_,sensor_script_}*.csv # SUM sample_duration=24H action=sum plot net_*.csv ``` 4) Create more plots as you like Some self-explaining examples: ```shell # x and y axis by column name graph cpu_1min.csv -x 'datetime#Date' -y 'float#LoadAverage1min' --resample 1H -o cpu_1min_resample-1H.png # x and y axis by column number graph cpu_1min.csv -x 1 -y 2 --resample 1H -o cpu_1min_resample-1H.png # specify x axis; use all other axes for y graph cpu_1min.csv -x 1 --resample 1H -o cpu_1min_resample-1H.png # increased plot size graph cpu_1min.csv -x 1 --resample 1H --figsize 1600x1000 -o cpu_1min_resample-1H.png ``` ### Example plots ![img](images/cpu_1min.csv.resample-1H.png) ![img](images/drive_68c349e8-5118-4773-9fd5-5dbad9acee4e.csv.resample-1H.png) ![img](images/filesystem_c385a436-0288-486f-a2b9-c64c2db667e7.csv.resample-1H.png) ![img](images/memory.csv.resample-1H.png) ![img](images/net_enp0s31f6.csv.exported.csv.resample-1H.png) ![img](images/swap.csv.resample-1H.png) ![img](images/temp_coretemp_Package%20id%200.csv.resample-1H.png)