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:
In this article, we briefly review some tools for monitoring Kubernetes:
In this article
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:
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:
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:
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:
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.
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:
The ELK stack is highly customizable and can be extended with additional plugins and integrations.
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:
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
To try out Lumigo for Kubernetes, check out our Kubernetes operator on GitHub.