Open AccessEnhancement of observability using Kubernetes operator
Author(s) -
Prerana Shenoy S. P.,
Sai Vishnu Soudri,
Ramakanth Kumar P.,
Sahana Bailuguttu
Publication year - 2022
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v25.i1.pp496-503
Subject(s) - computer science , observability , visualization , software deployment , real time computing , distributed computing , reliability (semiconductor) , embedded system , operator (biology) , reliability engineering , memory footprint , operating system , data mining , engineering , power (physics) , biochemistry , physics , chemistry , mathematics , repressor , quantum mechanics , transcription factor , gene
Observability is the ability for us to monitor the state of the system, which involves monitoring standard metrics like central processing unit (CPU) utilization, memory usage, and network bandwidth. The more we can understand the state of the system, the better we can improve the performance by recognizing unwanted behavior, improving the stability and reliability of the system. To achieve this, it is essential to build an automated monitoring system that is easy to use and efficient in its working. To do so, we have built a Kubernetes operator that automates the deployment and monitoring of applications and notifies unwanted behavior in real time. It also enables the visualization of the metrics generated by the application and allows standardizing these visualization dashboards for each type of application. Thus, it improves the system's productivity and vastly saves time and resources in deploying monitored applications, upgrading Kubernetes resources for each application deployed, and migration of applications.