pyDash – A Web Based Linux Performance Monitoring Tool
pydash is a lightweight web-based monitoring tool for Linux written in Python and Django plus Chart.js. It has been tested and can run on the following mainstream Linux distributions: CentOS, Fedora, Ubuntu, Debian, Arch Linux, Raspbian as well as Pidora.
You can use it to keep an eye on your Linux PC/server resources such as CPUs, RAM, network stats, processes including online users and more. The dashboard is developed entirely using Python libraries provided in the main Python distribution, therefore it has a few dependencies; you don’t need to install many packages or libraries to run it.
In this article, we will show you how to install pydash to monitor Linux server performance.
How to Install pyDash in Linux System
1. First install required packages: git and Python pip as follows:
-------------- On Debian/Ubuntu -------------- $ sudo apt-get install git python-pip -------------- On CentOS/RHEL -------------- # yum install epel-release # yum install git python-pip -------------- On Fedora 22+ -------------- # dnf install git python-pip
2. If you have git and Python pip installed, next, install virtualenv which helps to deal with dependency issues for Python projects, as below:
# pip install virtualenv OR $ sudo pip install virtualenv
3. Now using git command, clone the pydash directory into your home directory like so:
# git clone https://github.com/k3oni/pydash.git # cd pydash
4. Next, create a virtual environment for your project called pydashtest using the virtualenv command below.
$ virtualenv pydashtest #give a name for your virtual environment like pydashtest
Important: Take note the virtual environment’s bin directory path highlighted in the screenshot above, yours could be different depending on where you cloned the pydash folder.
5. Once you have created the virtual environment (pydashtest), you must activate it before using it as follows.
$ source /home/aaronkilik/pydash/pydashtest/bin/activate
From the screenshot above, you’ll note that the PS1 prompt changes indicating that your virtual environment has been activated and is ready for use.
6. Now install the pydash project requirements; if you are curious enough, view the contents of requirements.txt using the cat command and the install them using as shown below.
$ cat requirements.txt $ pip install -r requirements.txt
7. Now move into the pydash directory containing settings.py or simple run the command below to open this file to change the SECRET_KEY to a custom value.
$ vi pydash/settings.py
Save the file and exit.
8. Afterward, run the django command below to create the project database and install Django’s auth system and create a project super user.
$ python manage.py syncdb
Answer the questions below according to your scenario:
Would you like to create one now? (yes/no): yes Username (leave blank to use 'root'): admin Email address: [email protected].com Password: ########### Password (again): ############
9. At this point, all should be set, now run the following command to start the Django development server.
$ python manage.py runserver
10. Next, open your web browser and type the URL: http://127.0.0.1:8000/ to get the web dashboard login interface. Enter the super user name and password you created while creating the database and installing Django’s auth system in step 8 and click Sign In.
11. Once you login into pydash main interface, you will get a section for monitoring general system info, CPU, memory and disk usage together with system load average.
Simply scroll down to view more sections.
12. Next, screenshot of the pydash showing a section for keeping track of interfaces, IP addresses, Internet traffic, disk read/writes, online users and netstats.
13. Next is a screenshot of the pydash main interface showing a section to keep an eye on active processes on the system.
For more information, check out pydash on Github: https://github.com/k3oni/pydash.
That’s it for now! In this article, we showed you how to setup and test the main features of pydash in Linux. Share any thoughts with us via the feedback section below and in case you know of any useful and similar tools out there, let us know as well in the comments.