Magalix Dashboards Overview

Get the most out of Magalix, by knowing how to navigate our dashboards.

Once you get your cluster connected to Magalix, we start analyzing your cluster's data and generate recommendations to improve the cluster at different dimensions, such as performance, reliability, security, cost, etc. 

After your first recommendations are ready, you will be directed to Magalix Home Dashboard when you can start navigating our product and get valuable insights and recommendations about your cluster. 

Note: You will still see the cluster connection page till we generate your first recommendations, which usually takes 8 - 15 mins, after that, you will be redirected to the Home Dashboard.

Magalix recommendations fall into one of two categories: 

  1. Issues, which are generated by KubeAdvisor to help you identify if your workloads are violating any policies whether Magalix predefined policies or your own defined policies. (To learn more about Kube Advisor, Click here)
  2. Optimizations, which are generated by KubeOptimizer to help you optimize your clusters to make it performant and cost-efficient. (To learn more about KubeOptimizer, Click here)

For the first 24 hours, you won't be able to see any optimizations, because we will need to collect 24 hours worth of data at least in order for KubeOptimizer algorithms to start generating any optimizations recommendations. 


Magalix Dashboards gives you an easy way to organize and access your recommendations and provide you with more valuable insights about your cluster. Below are the dashboards you will be seeing in our web console.

Home Dashboard

The home dashboard provides a bird-eye and hierarchal view of generated analysis and recommended actions. It starts with the overall picture across all your clusters


Cluster Dashboard

Cluster dashboard gives you more in-depth details of the overall resources utilization and cluster issues. 


Issues View

Issues View provides the list of reported issues categorized by an advisor.


Single Issue Analysis

This view is breaking down entities and workloads inside your Kubernetes cluster that are violating an advisor policy. You can drill from that screen into the detailed recommendation view.


Recommendation View

This view is a detailed analysis of the workload level. It is broken down into how you can fix an issue, the collected evidence, and the history of the reported issue.