So you said your Java or React app is running on Kubernetes and it is using Prometheus and Grafana for dashboard purpose and monitoring. So to understand the architecture I would suggest to start from uh monitoring graphana dashboards like you know the board matrix or uh CPU or memory and uh like you know service maps using the dashboard ids like 1860 or 858 1 these are all graphana dashboard id can go and google and then we can also search it. Now coming to the errors you have asked like 4.
1, 43 and then 500 that those are business level errors like errors like 4. 1 and 43 usually mean for uh authentication or authorization issues. So check token configurations or ingress rules.
500 mms are mostly backend issues. So there is only one way to check from the logs or uh like you know login tool like ELP stack or some other tools. And um coming to uh the Prometheus in real time uh we use um node exporter and also we use uh cube set metrics.
There is something called jmx exporter also that is for java application and there is something called blackbox blackbox exporter that is for uh endpoints and the very famous one is advisor by Google. This is to monitor the container metrics. So in graphl the popular dashboard sir I will tell you the numbers uh it's 1860 as I said before for node exporter and uh 315 is for cubetis cluster and 1206 is for arus these IDs were also explained in my docker video as well you can watch the link now coming about the arcill yes we use image updator to automatically deploy new version to the cluster with real time other useful extensions are like notification for alerts and app set controller to manage multiple apps efficiently.
As far as I believe with my experience maybe I might be wrong, I might be correct. This setup is honestly used in almost all the environments in the realtime use case like to production to monitor and also to debug and to deploy faster.
