originally developed by Google, Kubernetes has grown into the go-to management system for platforms and applications. Anything that needs multiple different containers usually turns to Kubernetes, with the tool being ideal for developing, monitoring, and scaling an application.

Part of what makes Kubernetes so effective is the range of different metrics within the software. By moving through the various different metrics available, you’re able to build up a holistic understanding of the app, containers, and the performance of individual nodes. With this, you’re able to address problems when they arise, allocate resources effectively, and understand exactly how your system works.

In this article, we’ll be exploring Kubernetes metrics, pointing towards the most essential metrics to follow and why you ought to take a note of them.

Which Kubernetes Metrics ought to I Monitor?

If you’re wanting to create healthy clusters, then monitoring them by following certain metrics is a important practice. considering the popularity of Kubernetes, it’s no wonder that there are a range of different metrics that you can trace within the system. Typically, these fall into two broad categories:

Cluster Metrics – Whether it be able to general health and efficiency of the cluster itself, its workload and progress, or even information about the individual nodes that are used by the cluster, Kubernetes has metrics that you can access.

Deployments and Pods – any pods or deployments that come from the Kubernetes system itself will have a range of different metrics for you to monitor.

Kubernetes cluster Metrics

To give yourself a holistic understanding of how a cluster within Kubernetes is working, you’ll need to know the number of resources that the cluster is using, how interconnected it is in terms of which applications are on each node, and information about the capacity of each individual node in your system.

Due to the sheer scope of Kubernetes, supporting up to 5,000 nodes per cluster, it’s essential to understand how the system is working. considering the potential size of your ecosystem, this would be nearly impossible without the cluster metrics.

These metrics come in a few different forms:

Nodes – Within this section, anything that relates to nodes within a cluster will be located. This relates to information like CPU, memory or disk utilization, network bandwidth usage, and much more will all be here. With these metrics, you’re able to deduce the strain on individual nodes, allowing you to run your system much more efficiently by reallocating resources to different pods. Equally, if a pod is restarting or crashing, you’ll be able to find out why by checking the strain on the related nodes.

Pods Per Node – Within Kubernetes, you will have to pay your cloud company for the use of certain clusters. This considered, metrics related to this section will tell you exactly what a cluster is doing, how numerous nodes are available to it, and information about the cost of that particular cluster to your business.

Memory and CPU – Kubernetes allows a node’s kubelet to be allocated to different containers. Within this section, you’ll be able to set minimum and maximum limits on the number of resources that are allocated. Equally, metrics within this section will detail the memory requirements of all of the different pods connected to your system, giving you a holistic summary of your entire ecosystem’s memory usage.

Node resources – in some cases within Kubernetes, nodes will fail. Without these node resource metrics, it would be challenging to discuss why. This section allows you to track the workload of individual pods, double-checking the size of different nodes available and if this will be enough to sustain the system as a whole. Additionally, you can use the information about the number of pods per node

While the cluster metrics are much much more complex than pod and deployment metrics, they also give much much more information about the system as a whole, allowing you to understand where resources are being allocated and how efficiently your ecosystem is running.

Pod and Deployment Metrics

These metrics are extremely vast, covering 10s of different individual elements and allocations. However, they can be summarized into three distinct groups, each of which has a range of different metrics within them.

The three pod and deployment metric groups that you’ll encounter within Kubernetes are:

General Metrics – Anything that is related to the health of the pods within your Kubernetes ecosystem falls into this category. From information about the quantity of instances that a pod is supporting to details about any pods that have failed or have restarted, this section will help you find information about resource allocation, the strain on your pods, and their general health.

Container Metrics – relating to the general resource limits of each of younull