As per the assingment repo consists of the following files:
- Python Code for collection System stats, for which i used psutil python library.
- ElasticSearch Model file to signifying the model.
- Kibana Dashboard json exported file.
- Images of Kibana Dashboard.
- Python Code consists of two modules, elasticSearch.py and process_info.py.
- with process_info.py being entry-point for the application.
- Added Python code to get information related to processes present in the system.
- Added the list in elasticsearch DB using elasticsearch python client.
- Visualized elaticsearch data, based on cpu and memory percentage usage, grouped by PID's in Kibana Dashboard.
- Also Performed filtering to get only those PID's having CPU usage or memory consumption more than or equal 40%.
Kibana Dashboard Image for denoting CPU and memory usage in percentage for all the PID.
Kibana Dashboard Image, for showing Count of Processes, with CPU or memory usage more than 40%
Kibana Dashboard Time-Chart Image, for showing PID, with CPU or memory usage more than 40% for an time interval of 30 mins.
