kubernetes-mixin VS prometheus

I'd suggest looking at the queries used by the kubernetes mixin dashboards for inspiration.

Came across this lib, but realized the last update was 4 years ago.

Take a look at the kubernetes mixins to get an idea and/or starting point

The last step is to use the Mixin dashboard to visualize the usage of PV, you can get it from here

It's working good so far, except for the annoying CPUThrottlingHigh alert that is firing for many pods (including the own Prometheus' config-reloaders containers). This alert is currently under discussion, and I want to silence its notifications for now.

I think it might still have issues figuring out that it needs to apply CRDs first: https://github.com/grafana/tanka/issues/246 Besides that, I found it super-handy for deploying https://github.com/prometheus-operator/prometheus-operator and https://github.com/kubernetes-monitoring/kubernetes-mixin

These all standard dashboards are basically generated from the kubernetes-mixin project.

I would suggest looking at the Kubernetes Mixin: https://github.com/kubernetes-monitoring/kubernetes-mixin, it has both alerts and Grafana dashboards.

WriteRequest::timeseries is a vector (https://github.com/prometheus/prometheus/blob/main/prompb/re...) and

Developers widely use Prometheus as a system for operational monitoring and alerting for their projects. Here is a list of tools for monitoring frontend services with Prometheus.

Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.

Distributed system administrators need mechanisms and tools for monitoring individual nodes in order to analyze the system and promptly detect anomalies. Developers also need effective mechanisms for analyzing, diagnosing issues, and identifying bugs in protocol implementations. Logging, tracing, and collecting metrics are common observability techniques to allow monitoring and obtaining diagnostic information from the system; most of the explored code bases use these techniques. OpenTelemetry and Prometheus are popular open-source monitoring solutions, which are used in many of the explored code bases.

Setting up monitoring for a system, especially one involving GRPC communication, provides crucial visibility into its operations. In this guide, we walked through the steps to instrument both a GRPC server and client with Prometheus metrics, exposed those metrics via an HTTP endpoint, and visualized them using Grafana. The Docker-Compose setup simplified the deployment of both Prometheus and Grafana, ensuring a streamlined process.

Alerting and Notification: Select a tool with flexible alerting mechanisms to proactively detect anomalies or deviations from defined thresholds. Consider asking questions like "Does this tool offer customizable alerting options and support notification channels that suit our team's communication preferences?" A tool like Prometheus provides robust alerting capabilities.

Prometheus

Prometheus is an open-source monitoring and alerting toolkit. It is designed to monitor highly dynamic containerized systems, making it an excellent choice for monitoring Docker containers and Kubernetes clusters.

wget https://github.com/prometheus/prometheus/releases/download/v2.46.0/prometheus-2.46.0.linux-amd64.tar.gz

Prometheus: Open-source monitoring system. Often used together with Grafana.