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Kubernetes Monitoring Explained: 10+ Tools To Get You Started

These Kubernetes monitoring tools will increase your visibility and help you monitor metrics such as health, performance, usage, and cost.

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Kubernetes is the platform of choice for orchestrating containerized applications. It’s ideal for large applications running on distributed instances. But you likely already knew that because if you are weighing Kubernetes monitoring tools, you know what Kubernetes (K8s) is and why it is useful. 

That means you also have an inkling of how challenging Kubernetes can be to manage. This is where Kubernetes monitoring tools come in handy. 

This guide will cover Kubernetes monitoring in detail, so you can improve your Kubernetes visibility, including knowing which Kubernetes metrics to track. We’ll also cover the best Kubernetes monitoring tools, so you can get started monitoring the metrics that matter most to you and your business.

Table Of Contents

What Is Kubernetes Monitoring?

Kubernetes monitoring is the set of activities engineers use to monitor the performance, efficiency, health, and cost characteristics of a Kubernetes system on an ongoing basis. Teams do this by looking at metrics that the Kubernetes infrastructure outputs.

It consists of analyzing various metrics of your organization's infrastructure to obtain helpful information. Monitoring is an integral part of observability in software engineering.  

Aside from informing your decisions, why is monitoring Kubernetes important? 

The Importance Of Monitoring Kubernetes

In highly distributed and dynamic environments, Kubernetes can be a complex work of confusion without the right tools to simplify observability and see how all components work together. 

If you use multiple tools together, such as Amazon Elastic Kubernetes Service (EKS) with Fargate, you also know the setup can tend to limit visibility into your Kubernetes infrastructure.  The Kubernetes benefits you expect may be hard to discern while observing limited observability. 

You may not be able to tell whether everything is running smoothly under the surface due to low visibility. You also may not know when it’s time to take action to prevent security, performance, network, health, and cost risks.

You can track critical insights, such as your Kubernetes infrastructure's availability, resource utilization, health, and related costs, with a good monitoring tool.    

What types of Kubernetes monitoring metrics will you need to monitor to get the right insights? 

Kubernetes Monitoring Metrics: What Metrics Should You Monitor?

Engineers use monitoring metrics to determine how applications behave once deployed. There are several types of monitoring metrics to track in Kubernetes. Here are some of the most important ones to pay close attention to:

  • Kubernetes cluster metrics such as its state, running containers, network input/output, and resource consumption
  • Latency of API requests
  • The running and deployment of Kubernetes pods 
  • Resource metrics such as CPU utilization, memory utilization, and disk utilization at both the node and pod levels   
  • Control plane metrics such as etcd data stores, API servers, controller life cycles, and scheduler status
  • Metrics related to cost, such as Kubernetes costs per product, team, or cluster 
  • Container-native and application metrics    

How do you get metrics from Kubernetes?

Engineering teams accomplish this by evaluating different abstraction levels, including containers, pods, nodes, and entire Kubernetes clusters.

Most engineers prefer collecting as many metrics as possible before selecting Key Performance Indicators (KPIs). Each team will have a unique way of collecting Kubernetes monitoring metrics since there are various tools to help with that. 

In general, Kubernetes metrics are collected in one of two ways:

1. Using DaemonSets

DaemonSets are features in Kubernetes that run copies of required pods on all nodes. It runs a monitoring agent on all desired pods to collect health and performance metrics. A wide range of tools use this approach since DaemonSets are easy to provision.

2. Using Metrics Server

Engineers install a Metrics Server as a regular pod inside Kubernetes to collect data and events from pods and containers inside a cluster. Metrics Server used to be Heapster before deprecation. 

Metrics Servers are an excellent choice if you work with large workloads since they can monitor clusters with up to 5,000 nodes.   

Speaking of tools, here are several that help engineers and team leaders like you simplify Kubernetes monitoring. 

Kubernetes Monitoring Tools: What Tools Exist For Monitoring Kubernetes?

Kubernetes monitoring tools are available both as closed-source and open-source solutions. The benefits of open-source monitoring tools include being free to use and can be good options if you are on a tight budget. 

Closed-source solutions provide ready-to-use tools, ongoing technical support, and ready infrastructure, so you don't have to worry about constructing your own. 

Also, while some organizations told The New Stack they monitor Kubernetes clusters with a specific tool:

Kubernetes Tools

Credit: The New Stack

Several respondents said they use more than one tool for tracking Kubernetes KPIs:

Kubernetes Tools

Credit: The New Stack

That said, what are the most effective tools for monitoring Kubernetes clusters?

1. Kubernetes Dashboard

Kubernetes Dashboard

With Kubernetes Dashboard, users can monitor, manage, and troubleshoot a Kubernetes environment using an UI add-on that runs in their web browsers. It displays fundamental metrics like CPU and memory utilization across all nodes, as well as workload health statistics.  

Since it is part of the Kubernetes ecosystem (such as Kube-state-metrics and Fluentd/Fluent Bit for logging), some people do not consider it a tool. But it does the job, so we'll include it here, especially since it's an excellent place to start before deploying more advanced Kubernetes monitoring services, tools, or platforms.  

2. CloudZero

Many "all-in-one" Kubernetes monitoring solutions do not provide a way for engineering teams to monitor their Kurbenetes costs and accurately allocate spend to the cost metrics their business cares about. This is where CloudZero comes in. 

CloudZero is a cloud cost intelligence platform that helps engineering teams measure and monitor their Kubernetes costs. Helpful dashboards display costs per cluster, pod, or namespace down to an hour.

CloudZero Kubernetes Filter

Engineers can see the cost impact of their work — and teams can provide context to finance around unit cost, cost per customer, feature, and more.

By understanding how changes to their Kubernetes projects affect their cloud spend, engineers can take steps to optimize costs based on best practices. As opposed to tools like AWS CloudWatch, CloudZero combines billing data with Kubernetes usage statistics to provide crucial insights into your business operations. Learn more about CloudZero Kubernetes cost monitoring here.

3. Prometheus 

Prometheus

Prometheus is the most popular open-source monitoring solution for Kubernetes for several reasons. Chief among those is it combines a powerful querying language (PromQL) with a multi-dimensional data model, unlike alternative time-series databases like InfluxDB, Cassandra, and Graphite. 

In addition, it uses a pull method rather than a push one, has a large developer community that helps improve the platform, and provides real-time alerting tools. You can also run the platform on top of your Kubernetes with the Prometheus Operator

However, it does not come with a built-in visualization tool. For that, you will need to use another tool, such as Grafana.

4. cAdvisor

cadvisor

Credit: GeekFlair

Container Advisor is also a native Kubernetes monitoring tool for gathering, analyzing, and reporting resource utilization as well as historical data and performance statistics both at the container and cluster levels. 

cAdvisor automatically discovers active containers so you can monitor their metrics, such as CPU, network, and memory usage (at the node level, not per pod). However, as with the Kubernetes Dashboard, it primarily focuses on collecting metrics — not event logs, traces, and events — and does not store long-term data.      

5. Grafana

grafana

Grafana is a robust and open-source solution for querying, visualizing, monitoring, alerting on, and analyzing Kubernetes metrics. 

You will typically find engineers using it in combination with Prometheus, Grafite, or InfluxDB. This is typical because Grafana offers excellent visualization and monitoring dashboards to use with the databases. 

Many people use it because it offers alerting mechanisms, can query multiple entities at once, supports Elastisearch, and is compatible with many data sources. Grafana also allows for some log browsing. 

6. Jaeger

jaeger

Jaeger is a distributed tracing and monitoring solution in complex distributed systems such as a Kubernetes environment. It also acts as a troubleshooting tool, allowing your team to perform distributed transaction monitoring and context propagations, root cause and service dependency analyses, as well as latency and performance optimizations.

It supports several data sources, including Cassandra, memory, Kafka, and Elasticsearch, and has been open-source since 2016.

Like Grafana and cAdvisor, you can use a DaemonSet configuration to deploy it. Or you can use the Jaeger Operator.    

7. The ELK Stack

The ELK Stack

Credit: Sematext

The ELK Stack is an open-source monitoring tool for logging Kubernetes. The acronym stands for Elasticsearch, Logstash, and Kibana, which form the basis of a small logging pipeline. But the stack usually includes Beats for data collection and Kafka for buffering when dealing with massive amounts of data.

The stack combines Elastisearch’s scalability, Logstash’s log aggregation and analysis capabilities, and Kibana’s rich analysis tool for making sense of collected data. 

Despite being challenging to maintain at scale, the ELK Stack deploys easily and has a robust developer community to support it.      

8. Sematext

sematext

Sematext is a full-stack visibility tool for container orchestrators and containers if you want a comprehensive logging and monitoring solution. Yet, it is also compatible with traditional systems. 

You can collect all events, logs, and metrics running in a Kubernetes cluster, structure them, and visualize them in custom monitoring dashboards. This all happens in real-time.

With Sematext, you can also detect anomalies in real-time and receive alerts regarding pod-level issues. Besides monitoring resource usage, it also captures network throughput. It is also easy to install as a Sematext Operator, DaemonSet, Helm chart, or Kubernetes Operator.    

9. Weave Scope

weavescope

Weave Scope is a robust improvement over Kubernetes-native Kube-state-metrics because it allows engineers to run diagnostic commands on and manage containers within the interface. 

Engineers have access to a drill-down view of their app, the infrastructure it is deployed on, and the connections between components through the user interface. It also displays contextual logs, metrics, and metadata for Docker and Kubernetes containers.     

10. Datadog

datadog

If you do not want to monitor infrastructure or run any storage yourself, Datadog can help. Datadog allows your team to aggregate service states, metrics, and events within your Kubernetes environment in real-time. With it, you can monitor entire clusters down to a single host.

Datadog lets you see inside apps or stacks, from anywhere, at any scale. It offers comprehensive DevOps services, including network, security, and real-time monitoring. It also provides log management, including filters, search functions, and a logs analysis tool for troubleshooting needs.

The tool offers full API access across all apps and infrastructure to increase visibility. In addition, it can be run on every cluster node by using a DaemonSet. 

11. Dynatrace

dynatrace

Dynatrace is also a full-stack monitoring solution for Kubernetes environments. With this tool, you can monitor availability and health for applications and processes, dependencies, and connections among hosts, containers, and cloud instances. 

Dynatrace lets you unify and harness insights from over 500 different tools you probably already use, including AWS, Azure, OpenShift, Google Cloud, and Kubernetes, among others. Even better, it uses events, traces, metrics, and behavioral information to reveal the inner workings of Kubernetes applications. 

Like DataDog, Dynatrace is best suited to complex, distributed systems, provides superior APM integration, and requires substantial investment.    

Monitor Kubernetes Costs With CloudZero

Overall, monitoring your Kubernetes setup and environment provides you the insight you need to ensure proper performance and address concerns around security, network, health, and cost. By choosing the right monitoring tools, you can make sure you have the relevant data you need to make informed product and engineering decisions.

Tools like Dynatrace, Sematext, and Datadog can help when it comes to monitoring performance or security. When it comes to monitoring your Kubernetes cost, though, this is where a cloud cost intelligence platform, like CloudZero, can help.

With CloudZero Kubernetes cost monitoring, engineers can see how much they spend on Kubernetes per feature, product, customer, team, and more — and even drill down into costs per cluster, pod, or namespace down to an hour. 

Moreover, CloudZero tracks, detects, and alerts on cost anomalies, sending timely notifications to the right people in your organization to ensure you don't overspend on Kubernetes. Request a demo today and find out how CloudZero can help you monitor your Kubernetes costs.

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