KlusterView VS net-test

KlusterView, is a flexible and streamlined tool for visualizing Kubernetes metrics. 🚀With KlusterView, you can easily monitor your Kubernetes cluster, whether you're an individual developer or part of a small team. It simplifies the monitoring process, empowering you to focus on building and deploying software without worrying about infrastructure differences. Our open source product is designed to simplify monitoring in Kubernetes clusters. KlusterView v1.0 offers an embedded dashboard with resource usage metrics, pod and node health status, and trends over time. You also get a visual representation of cluster nodes and pods, making it easy to identify container-specific issues. Installation is a breeze with Helm Chart or manual installation methods. Plus, KlusterView integrates smoothly with existing monitoring tools, providing customization options to fit your needs. We have an exciting roadmap ahead! Currently, we're working on full support for Grafana Live features, in-window dashboard customization, and integration with Grafana's RBAC system. We're also planning pod-level error monitoring and integration with Grafana Alerts Management. Want to contribute? KlusterView is an open-source project, and we welcome contributions. Check out our GitHub repository and join the community.Say goodbye to complex Kubernetes monitoring. Try KlusterView today and gain valuable insights into your cluster without the hassle. Simplify your monitoring journey with KlusterView!

[KlusterView](https://www.klusterview.io), is a flexible and streamlined tool for visualizing Kubernetes metrics. With KlusterView, you can easily monitor your Kubernetes cluster, whether you're an individual developer or part of a small team. It simplifies the monitoring process, empowering you to focus on building and deploying software without worrying about infrastructure differences. Our open source product is designed to simplify monitoring in Kubernetes clusters. [KlusterView](https://github.com/oslabs-beta/KlusterView) v1.0 offers an embedded dashboard with resource usage metrics, pod and node health status, and trends over time. You also get a visual representation of cluster nodes and pods, making it easy to identify container-specific issues. Installation is a breeze with Helm Chart or manual installation methods. Plus, KlusterView integrates smoothly with existing monitoring tools, providing customization options to fit your needs. We have an exciting roadmap ahead! Currently, we're working on full support for Grafana Live features, in-window dashboard customization, and integration with Grafana's RBAC system. We're also planning pod-level error monitoring and integration with Grafana Alerts Management. Want to contribute? KlusterView is an open-source project, and we welcome contributions. Check out our GitHub repository and join the community.Say goodbye to complex Kubernetes monitoring. Try KlusterView today and gain valuable insights into your cluster without the hassle. Simplify your monitoring journey with KlusterView! TL;DR: KlusterView simplifies Kubernetes metrics visualization with a user-friendly interface. Monitor your cluster effortlessly and focus on software development. Containers and Kubernetes provide portability and orchestration, respectively. KlusterView v1.0 offers an embedded dashboard and visual representation of cluster nodes and pods. Join our open-source community and enjoy hassle-free monitoring! We invite you to explore our [LinkedIn profile](https://www.linkedin.com/company/klusterview/about/), [Github repository](https://github.com/oslabs-beta/KlusterView), and [website](https://www.klusterview.io) for more information about us! /#Kubernetes #Monitoring #DevOps #OpenSource

Cool! It's so funny I just recently took an old bash script of mine which did something similar and have been upgrading it into a proper application which exports metrics to Prometheus and Grafana: https://github.com/Noah-Huppert/net-test

I saw a comment below where some was rolling their eyes that you "complicated" stuff with Prometheus, Grafana, and Docker and how you could just use Bash scripts and crons. As I just upgraded my codebase from this more bare metal approach to this "more complex setup" I'd like to mention: there's no way you could do time series statistical analysis easily with "just a cron job and a bash script". Prometheus and Grafana are for more than just buzz words. Prometheus offers an advanced time series database which allows you to, at minimum, do more robust analysis using data techniques like Histograms. As for Grafana, it makes exploring data dead easy. Providing users with a Docker Compose setup is also something I did with my tool and the benefits are huge. It lets me distribute a setup which relies on multiple moving parts working smoothly together. Sure I could write a whole wiki on how you should setup Prometheus Grafana and my tool, or I could distribute the setup with a configuration as code tool. Ensuring that even if someone doesn't want to use Docker Compose they can at least read my configuration as code and see exactly what I did to setup my tool.