Kubernetes Monitoring Tools

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6 Open Source Kubernetes Monitoring Tools You Should Know

What Are Kubernetes Monitoring Tools? 

A Kubernetes monitoring tool is a software application that helps monitor the health, performance, and resource utilization of a Kubernetes cluster and its components. The goal of a Kubernetes monitoring tool is to provide visibility into the cluster and its components, to help identify potential issues, and to facilitate the troubleshooting process. 

Some of the key features of a Kubernetes monitoring tool include:

  • Metric collection and analysis: The ability to collect and analyze various metrics related to the cluster, such as resource utilization, network traffic, and application performance.
  • Alerting: The ability to set up alerts that notify administrators when certain thresholds are exceeded, such as when a pod is unresponsive or when resource utilization exceeds a certain level.
  • Dashboarding: The ability to display metrics and other data in a user-friendly format, using graphical representations such as charts, graphs, and tables.
  • Log collection and analysis: The ability to collect and analyze logs from the various components of the cluster, such as pods, nodes, and controllers, to help diagnose issues and troubleshoot problems.

In this article, we briefly review some tools for monitoring Kubernetes:

Kubernetes Dashboard

License: Apache-2.0 license

GitHub Repo: https://github.com/kubernetes/dashboard

The Kubernetes dashboard is a web-based graphical user interface (GUI) that provides a centralized view of a Kubernetes cluster. It allows users to easily monitor, troubleshoot, and manage various resources in the cluster, such as nodes, pods, services, and deployments.

The Kubernetes dashboard is a built-in component of Kubernetes and is deployed as a Kubernetes application. It can be accessed through a web browser and provides an intuitive interface for interacting with Kubernetes resources, which can be especially helpful for users who are not familiar with the command-line interface (CLI) or for quick visual inspection.

Some of the features provided by the Kubernetes dashboard include:

  • A summary of the cluster’s overall health, including the number of nodes and pods, as well as their status.
  • The ability to view and modify Kubernetes resources, such as deployments, services, and replication controllers.
  • Access to the logs and events of pods running in the cluster.
  • The ability to create and manage custom resource definitions (CRDs).
  • The ability to deploy and manage Helm charts.

The Kubernetes dashboard is extensible, and it can be customized to meet the specific needs of different users and organizations. However, it should be properly secured and access should be restricted to authorized users only, as the dashboard provides access to sensitive information and control over the cluster.


License: Apache-2.0 license

GitHub Repo: https://github.com/prometheus/prometheus

Prometheus is an open-source monitoring and alerting toolkit that is widely used for monitoring and troubleshooting distributed systems. It was originally developed at SoundCloud and is now a graduated project of the Cloud Native Computing Foundation (CNCF).

Prometheus is designed to be highly scalable, reliable, and adaptable to different environments. It uses a pull-based model to scrape metrics from various sources, such as applications, databases, and operating systems. These metrics are then stored in a time-series database, which can be queried and analyzed using PromQL, a powerful query language.

Some of the key features of Prometheus include:

  • Highly flexible and configurable data collection, including support for custom metrics and labels.
  • Powerful graphing and visualization capabilities, with support for various types of charts and dashboards.
  • Seamless integration with Kubernetes and other container orchestration platforms.
  • A rich ecosystem of third-party exporters and integrations, including support for various programming languages and frameworks.


License: AGPL-3.0 license

GitHub Repo: https://github.com/grafana/grafana

Grafana is an open-source platform for data visualization and monitoring that allows users to create and share interactive, customizable dashboards. It is often used in conjunction with other monitoring and observability tools, such as Prometheus, to provide a complete end-to-end monitoring solution.

Grafana provides a rich set of features, including:

  • A flexible and intuitive query editor that supports a variety of data sources, including Prometheus, Graphite, InfluxDB, and more.
  • A wide range of built-in visualization types, including graphs, gauges, tables, and heatmaps.
  • Support for custom plugins, allowing users to extend and customize the platform with their own visualizations and integrations.
  • The ability to create and share dashboards with other users, allowing for collaboration and knowledge-sharing.


License: Apache-2.0 license

GitHub Repo: https://github.com/jaegertracing/jaeger-kubernetes

Jaeger is an open-source, distributed tracing system that is used to monitor and troubleshoot microservices-based distributed systems. It was developed by Uber Technologies and is now part of the CNCF. Jaeger consists of several components, including:

  • A tracing client library that can be integrated into applications to capture and instrument trace data.
  • A collector that receives trace data from the clients and forwards it to a storage backend.
  • A query service that allows users to search and retrieve trace data from the storage backend.
  • A web-based UI that allows users to visualize and analyze trace data.

Jaeger supports multiple data storage backends, including Cassandra, Elasticsearch, and in-memory storage, and it can be used in various deployment scenarios, including Kubernetes, Docker, and bare metal environments.

ELK Stack

License: MIT license

GitHub Repo: https://github.com/deviantony/docker-elk

The ELK Stack is a popular open-source solution for centralized logging and log analysis. ELK stands for Elasticsearch, Logstash, and Kibana, which are the three main components of the stack. Here are the main features of each tool:

  • Elasticsearch: A distributed search and analytics engine that stores and indexes logs and other data. It provides fast and flexible search capabilities and can scale horizontally to handle large amounts of data.
  • Logstash: A data processing pipeline that ingests, filters, and transforms logs from various sources and sends them to Elasticsearch for storage and indexing. It supports a wide range of input and output plugins, including file, Syslog, and Kafka, as well as filters for parsing, transforming, and enriching log data.
  • Kibana: A web-based user interface for visualizing and exploring data stored in Elasticsearch. It provides a variety of tools for creating and customizing dashboards, charts, and tables, as well as for searching and filtering log data.

The ELK stack is highly customizable and can be extended with additional plugins and integrations.

Container Advisor (cAdvisor)

License: Apache-2.0 license

GitHub Repo: https://github.com/google/cadvisor

Container Advisor (cAdvisor) is an open-source tool that provides real-time monitoring and analysis of container resource usage and performance. It was originally developed by Google and is now part of CNCF.

cAdvisor is designed to be container-aware and provides detailed metrics on resource usage and performance for each container running on a host, such as CPU usage, memory usage, and network I/O. It can also collect and analyze container-specific data, such as the container’s image, labels, and environment variables.

cAdvisor is designed to be lightweight and low-overhead, and it can be deployed as a standalone binary or as a container itself. It supports various container runtimes, including Docker, Kubernetes, and rkt, and it provides a REST API for programmatic access to the collected metrics.


License: Apache-2.0 license

GitHub Repo: https://github.com/kubernetes/kube-state-metrics

kube-state-metrics provides metrics on the state of Kubernetes objects, such as nodes, pods, deployments, and services. It collects data directly from the Kubernetes API server and exposes the data as Prometheus metrics, enabling users to monitor and analyze the state of Kubernetes objects in real-time and create custom dashboards and alerts based on the collected metrics.

Some of the key features of kube-state-metrics include:

  • Detailed metrics on the state of Kubernetes objects, such as ReplicaSets, deployments, and services.
  • Customizable metrics, with support for filtering and labeling.
  • Integration with Prometheus and other monitoring tools.
  • Low overhead and high performance, with minimal impact on the Kubernetes API server.
  • Extensibility, with support for custom collectors and plugins


Lumigo is a troubleshooting platform, purpose-built for microservice-based applications. Developers using Kubernetes to orchestrate their containerized applications can use Lumigo to monitor, trace and troubleshoot issues fast. Deployed with zero-code changes and automated in one-click, Lumigo stitches together every interaction between micro and managed service into end-to-end stack traces. These traces, served alongside request payload data, give developers complete visibility into their container environments. Using Lumigo, developers get:End-to-end virtual stack traces across every micro and managed service that makes up a serverless application, in context

  • API visibility that makes all the data passed between services available and accessible, making it possible to perform root cause analysis without digging through logs 
  • Distributed tracing that is deployed with no code and automated in one click 
  • Unified platform to explore and query across microservices, see a real-time view of applications, and optimize performance

To try out Lumigo for Kubernetes, check out our Kubernetes operator on GitHub.

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