Monitoring Kubernetes Cluster MenggunakanPrometheus dan Grafana
Keywords:
Cloud Computing, Cluster, Container, Kubernetes, Prometheus, Grafana, CPU, Memory, Traffic.Abstract
The large number of client requests can cause excessive workload on the server so that it can
make the server down. Because it uses cloud computing services that can increase the number of client
requests. With the cluster technology in cloud computing, the server workload will be divided evenly or
balanced to each server. Clustering can be combined with containers where each process or application
running on each container has the same kernel. Therefore, we need an application capable of managing
containers, one of which is Kubernetes. Kubernetes has several components, namely clusters, pods, services
and nodes that need to be monitored. To be able to carry out monitoring, an application that can help is
used, namely Prometheus and Grafana. Prometheus will retrieve the data in Kubernetes, then the data that
has been obtained by Prometheus can be visualized with Grafana. Grafana can convert metric data into
graphs that are easy to understand and interactive. Based on the results of functionality testing that has
been carried out, Prometheus has succeeded in reading data from the target server and Grafana has
succeeded in displaying it in graphical form. In the test, from 5 trials of 20-100 user access, the monitoring
system can show the amount of CPU usage, memory, and traffic load that can continue to increase
according to the user's access load.
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