Kubernetes monitoring for containerized applications is crucial but challenging. That's why we have curated this list of the top 13 Kubernetes monitoring tools to help you monitor your Kubernetes deployments like a pro. These tools will help you oversee your Kubernetes cluster, from tackling resource utilization to optimizing performance.
There's no doubt that Kubernetes is the most popular container orchestration platform that has revolutionized the application deployment and management world.
But with the increase in the complexity of growing the Kubernetes environment, the need for effective monitoring also grows.
This is where the Kubernetes monitoring tools come into the picture.
Kubernetes monitoring tools are solutions designed to efficiently manage the Kubernetes environment.
These tools collect and analyze various metrics, logs, and events from the Kubernetes infrastructure, giving users important insights for cost & performance optimization.
In this blog, we'll explore the top 13 Kubernetes monitoring tools designed to simplify keeping a close eye on your containerized applications.
Without further ado, let's look at the top 13 open-source Kubernetes monitoring tools.
- cAdvisor by Google
- Weave Scope
- Fluentd and Fluent Bit
- Kubernetes Dashboard
- Components of Kubernetes Monitoring
Prometheus is an open-source Kubernetes monitoring tool with a dimensional data model and flexible query language.
Prometheus specializes in collecting metrics, essentially data points that reflect the performance and health of your applications and infrastructure.
Pros of Prometheus
Scalability: Prometheus can handle the monitoring needs of large-scale Kubernetes environments thanks to its scalable architecture and efficient data storage mechanisms.
Powerful Alerting: It has a robust alerting system that can notify you of any unusual behavior or performance issues, enabling proactive intervention.
Rich Ecosystem: Prometheus boasts a rich ecosystem with various exporters and integrations, making it compatible with various systems and applications.
Flexible Querying: The PromQL (Prometheus Query Language) allows you to query and analyze metrics to gain deep insights into your Kubernetes environment.
Cons of Prometheus
Additional Components: To collect metrics from various sources, you may need to deploy additional components called exporters. While these exporters expand Prometheus' capabilities, setting them up can add complexity to the configuration.
Learning Curve: As with any powerful tool, starting with Prometheus may require learning and familiarity with its query language and configuration setup.
Grafana is another open-source Kubernetes monitoring platform. It helps users query, visualize, alert, and understand users' metrics.
With Grafana, users can customize their monitoring experience, making it visually appealing and tailored to their needs.
Pros of Grafana
Great Visualization: It offers many visualization options like graphs, charts, heatmaps, etc. This helps users present their Kubernetes data in a visually appealing way.
Flexible Dashboards: Grafana lets users create a custom dashboard that offers a holistic view of your Kubernetes environment. Users get all the information in a single place by combining these metrics.
Alerting Capabilities: Users can set up alerts based on specific thresholds or conditions. This helps them get notified when important metrics exceed predefined limits.
Thriving Community: Grafana has been the game for a long, and hence they have a supportive and resourceful community. This makes it easy to leverage the collective knowledge and resources.
Cons of Grafana
Plugin Limitations: While Grafana itself is open-source, some plugins or data sources may have commercial licenses, which might limit their availability in the free version.
Initial Learning Curve: Getting started with Grafana may require some initial learning to configure data sources, create dashboards, and utilize advanced features effectively.
Also Read: Differences between Grafana and Datadog
OpenTelemetry is one of the great additions to the observability landscape, focusing on observability and distributed tracing.
This helps users gain insight into the performance and behavior of your microservices and applications running in Kubernetes clusters.
Pros of OpenTelemetry
Comprehensive Observability: It offers a holistic approach to observability. They do this by collecting metrics, logs, and distributed traces. It gives users a complete picture of their Kubernetes environment. This further helps them understand the interactions and dependencies between different components.
Distributed Tracing: They help users trace requests as they flow through various microservices. This further allows us to avoid bottlenecks, performance and latency issues, and more.
Standardized API: OpenTelemetry follows a standardized API and instrumentation model, making adopting and integrating into your Kubernetes applications and services easier.
Vendor-Neutral and Extensible: OpenTelemetry is designed to be vendor-neutral and supports multiple programming languages and frameworks. It also offers extensibility options, allowing you to customize data collection and export based on your needs.
Jaeger is software that can help users monitor and troubleshoot complex microservices architectures. Initially, it was developed by Uber Technologies, and now they are part of CNCF.
Jaeger excels at being a Kubernetes monitoring tool by providing end-to-end visibility by capturing timing data across different distributed system components and presenting it in a user-friendly format.
This enables developers to identify bottlenecks, latency issues, and potential optimizations.
Pros of Jaeger
Distributed Tracing: It specializes in distributed tracing, allowing users to visualize and analyze flow requests across multiple microservices. This helps especially in the kubernetes environment with complex architectures.
Rich Visualization: Jaeger has a rich and very interactive UI that reflects data in a graphical format. It offers detailed visualization, such as trace timelines, service dependencies, and individual span details.
Integration Ecosystem: The good thing about Jaeger is that it supports multiple programming languages and frameworks. It also integrates with tools such as Prometheus, and Grafana.
Cons of Jaeger
Learning Curve: Understanding and implementing distributed tracing effectively with Jaeger may require learning and familiarity with distributed systems concepts. Setting up and configuring Jaeger to capture the necessary tracing data can be challenging, especially for beginners.
Resource Consumption: Jaeger generates significant tracing data, which can consume storage and network resources. Careful consideration should be given to the storage and retention policies to avoid overwhelming the system with excessive trace data.
Also Read: New Relic vs Grafana - Which One to Choose?
cAdvisor by Google
Container Advisor, also known as cAdvisor, is an open-source monitoring tool. It is designed especially for containerized environments like Kubernetes.
It collects and analyzes resources used and offers performance metrics based on that. It collects metrics mostly related to CPU, memory, disk usage, etc.
Pros of cAdvisor
Lightweight and Easy Setup: It is lightweight and straightforward to set up. It automatically discovers containers running on a node and starts collecting metrics without requiring any complex configuration.
Comprehensive Container Metrics: It offers users a good range of metrics that includes CPU usage, memory, consumption, network activity, and more. These metrics give users a proper insight into resource utilization.
Real-time Monitoring: With cAdvisor, users can get real-time monitoring capabilities. This allows them to observe the container's metrics as they are being updated.
Cons of cAdvisor
Limited Scalability: Since it is designed specifically for monitoring containers on individual nodes, cAdvisor can be difficult to monitor many containers. For extensive monitoring, some additional tools might be required.
Lack of Advanced Alerting and Visualization: It offers basic monitoring capabilities and lacks advanced alerting and visualization features. cAdvisor does not offer advanced features such as built-in mechanisms for setting up alerts or creating visual dashboards.
Limited Historical Data: The issue with cAdvisor is it only stores a limited amount of historical data, so if a user requires long-term data retention, they might need to implement additional mechanisms.
Also Read: Which one to Choose - Grafana or Kibana?
Kubewatch (officially archived by VMware) is one the exceptional open-source monitoring tools designed especially for Kubernetes.
It is well known for offering real-time notification for events within a Kubernetes cluster.
Pros of Kubewatch
Real-time Event Notifications: Users can get real-time alerts and notifications for events via multiple channels such as webhooks, Slack, email, and more. This helps them stay informed about any critical challenges.
Customizable Event Filtering: Users can customize event filtering based on their needs. They can define their rules to filter out events based on the relevancy of the projects.
Simple Configuration and Setup: The configuration and setup process for Kubewatch is simple and easy. That makes it a perfect choice for quick event monitoring in Kubernetes. Users can start receiving notifications for various cluster events even with minimal configuration.
Cons of Kubewatch
Limited Monitoring Scope: The primary focus of Kubewatch is event notifications and alerts, and they lack comprehensive monitoring capabilities of other Kubernetes environment aspects.
Lack of Historical Data: Kubewatch's primary function is to provide real-time event notifications. It does not store historical event data for analysis or long-term retention. Users who require historical event tracking or auditing capabilities may need to integrate Kubewatch with additional tools or solutions.
Dependency on External Notification Channels: Even though Kubewatch supports various notification channels like Slack and email, it relies on external services or platforms for delivering notifications.
Also Read: ELK Stack vs SPLUNK
Users can get a comprehensive dashboard view to monitor their kubernetes in real time.
Pros of kube-ops-view
Intuitive Cluster Visualization: It offers an intuitive visual representation of the kubernetes cluster and its element. The dashboard displays the status health of resources using color-coordinated indicators.
Real-time Monitoring: The kube-ops-view dashboard lets users get real-time data on their Kubernetes cluster's state. Users can also monitor metrics like CPU and memory usage, pod status, and more in one place.
Customizable Views: Users can customize the views and filters based on their specific monitoring requirements. They can easily focus on specific namespaces, labels, or resources per their needs.
Cons of kube-ops-view
Limited Historical Data: Since kube-ops-view primarily offers real-time visibility into the cluster, it doesn't store historical data. Users needing long-term trend analysis might need additional integration with other tools.
Lack of Advanced Monitoring Features: It does not offer advanced features such as log analysis, in-depth metrics, or alerting. It focuses more on offering a high-level overview rather than giving detailed reports.
Weave Scope is another open-source Kubernetes monitoring tool best suited for Kubernetes and containerized environments.
They offer users a real-time status of the cluster in graphical mode. This helps them achieve great insight into the various components.
Pros of Weave Scope
Real-time Cluster Visualization: It offers real-time visualizations of clusters and a tropical view of the resources such as nodes, pods, and containers. These visual representations help users understand the architecture and relationship between different components.
Deep Monitoring Capabilities: Along with the visual insights, they also offer rich monitoring capabilities. They capture all the real-time metrics related to CPU usage, memory consumption, network traffic, and more.
Interactive and Dynamic UI: Weave Scope has a very interactive user interface allowing users to explore their cluster more in detail. Users can zoom in and out and filter resources based on their needs.
Cons of Weave Scope
Initial Learning Curve: Weave Scope may have a slight learning curve. It is especially for users new to the tool or those who are not familiar with Kubernetes concepts.
Resource Intensive: While Weave Scope provides comprehensive monitoring and visualization, it can consume significant resources, especially in large-scale deployments.
Limited Historical Data: Weave Scope focuses primarily on real-time monitoring and visualization, providing insights into the current state of the cluster. However, it does not store historical data for in-depth trend analysis or long-term monitoring.
Fluentd and Fluent Bit
Fluentd and Fluent Bit are open-source log collection and forwarding tools. It is designed for handling large volumes of log data in Kubernetes environments.
Fluentd is a full-featured log collector. And Fluent Bit is a lightweight log forwarder. They are both developed by the same team at Treasure Data.
Pros of Fluentd
Log Collection and Aggregation: Fluentd and Fluent Bit excel at collecting logs from various sources within your Kubernetes cluster. They can efficiently gather logs from containers, applications, system components, and other log-producing entities.
Scalability and Performance: The tool is designed to efficiently handle high volumes of log data. They offer mechanisms for buffering and batching logs. That ensures smooth operation even in scenarios with many log-producing entities or high log volumes.
Flexibility and Extensibility: They have extensive plugin ecosystems, allowing easy integration with various data sources, log formats, and storage systems. They support numerous output destinations, including popular log management platforms like Elasticsearch and Kafka.
Cons of Fluentd
Learning Curve and Configuration Complexity: It can have a steep learning curve due to its rich feature set and configuration options. Users might need time and effort to understand and set up Fluentd correctly.
Resource Consumption: Fluentd and Fluent Bit, especially when dealing with large log volumes, can consume significant CPU and memory resources. Careful resource allocation and monitoring are necessary to ensure they don't impact the Kubernetes cluster's overall performance and stability.
Limited Real-time Log Analysis: Fluentd and Fluent Bit focus primarily on log collection and forwarding, providing centralized log aggregation and storage. However, they are not designed for real-time log analysis or complex log parsing.
OpenSearch is an open-source distributed search and analytics engine. It is a community-driven Elasticsearch fork.
It offers powerful indexing and querying capabilities for large volumes of data. OpenSearch provides scalability, fault-tolerance and supports various data ingestion methods.
Pros of OpenSearch
Scalability: OpenSearch is designed to handle large-scale data. It can easily scale horizontally to accommodate growing data volumes and user demands.
Fault-tolerance: It provides built-in fault-tolerance mechanisms. That further ensures high availability and resilience to node failures within a cluster.
Rich Querying Capabilities: OpenSearch supports advanced querying, including full-text search, filtering, and aggregations. That allows users to extract valuable insights from their Kubernetes data.
Active Community: As an open-source project, OpenSearch benefits from an active community. The community ensures ongoing development, bug fixes, and support from a vibrant user base.
Cons of OpenSearch
Learning Curve: OpenSearch's advanced features and query DSL can have a learning curve. It can be difficult to learn, especially for users new to search engines or complex data querying.
Configuration Complexity: Setting up and configuring OpenSearch may require expertise and understanding of distributed systems. That makes the whole process a bit more complex.
Migration from Elasticsearch: While OpenSearch is derived from Elasticsearch, migrating from Elasticsearch to OpenSearch may involve effort and consideration of potential compatibility differences.
Checkmk is an open-source solution that can be a great Kubernetes monitoring tool option. It offers comprehensive monitoring and alerting capabilities for IT infrastructure components.
It provides a unified platform for monitoring servers, networks, applications, and cloud environments.
Pros of Checkmk
Comprehensive Monitoring: Checkmk covers various aspects of your IT infrastructure, including servers, networks, applications, and more. It collects metrics, logs, and events from different sources, giving you a holistic view of your environment.
User-Friendly Interface: Checkmk provides a user-friendly web-based interface that simplifies configuration and monitoring. It offers intuitive wizards and templates for easy setup and management, making it accessible for beginners and experienced users.
Extensibility through Plugins: It has an extensive plugin ecosystem. That enables integration with various technologies and platforms. This further allows users to expand and customize their monitoring capabilities as per their needs.
Powerful Alerting and Notification: Checkmk offers flexible alerting features. This allows you to define custom alert rules based on your requirements. It supports various notification methods, ensuring timely alerts via email, SMS, or other channels and informing you about critical issues.
Cons of Checkmk
Learning Curve: Checkmk's extensive feature set and configuration options may have a learning curve. This can be an issue, especially for users new to monitoring tools.
Resource Consumption: Depending on the scale of your environment, Checkmk can consume significant resources, such as CPU and memory. Proper resource allocation and monitoring are essential to ensure it doesn't impact the performance of your monitored systems.
Complexity for Large Environments: While Checkmk is suitable for small to medium-sized environments, managing and configuring it for large-scale deployments can be complex.
Zabbix is an open-source enterprise-grade monitoring solution that provides comprehensive monitoring and alerting capabilities for IT infrastructure.
It offers many features, including real-time monitoring, data visualization, event management, and reporting.
Pros of Zabbix
Comprehensive Monitoring: Zabbix supports monitoring various components of your IT infrastructure, including servers, networks, virtual machines, applications, and more. It offers extensive monitoring options, allowing you to collect and analyze metrics from different sources.
Flexible Configuration: It provides a flexible and powerful configuration system. It allows you to define monitoring checks, configure thresholds, and set up custom actions based on specific criteria.
Scalability and Performance: It is designed to handle large-scale monitoring deployments. It provides scalability options, allowing you to monitor many devices, metrics, and hosts.
Alerting and Notification: Zabbix offers robust alerting capabilities, allowing you to define custom triggers and notifications based on specific conditions. It supports various notification methods, such as email, SMS, and integrations with popular messaging platforms.
Cons of Zabbix
Learning Curve: Zabbix has a learning curve, especially for users new to monitoring tools. Understanding its architecture, configuration options, and advanced features may require time and effort. However, extensive documentation and community support are available to assist in the learning process.
Initial Setup Complexity: The initial setup and configuration of Zabbix can be complex, especially for larger deployments. It involves installing and configuring server components and agents and defining monitoring templates. Proper planning and understanding of your monitoring requirements are essential for a successful setup.
User Interface: While Zabbix provides a web-based user interface, some users may find it less intuitive than other modern monitoring tools. However, recent versions of Zabbix have significantly improved the user interface, enhancing user experience and usability.
Also Read: How to Install & Setup Kubernetes Dashboard?
Kubernetes Dashboard is a web-based user interface that provides a visual representation of Kubernetes clusters.
It offers users a graphical view of their cluster's resources. This further allows them to monitor, troubleshoot, and manage applications and infrastructure within the cluster.
Pros of Kubernetes Dashboard
User-Friendly Interface: Kubernetes Dashboard offers an intuitive and user-friendly interface that simplifies cluster management tasks. It visually represents the cluster's resources, including services, deployments, nodes, and pods. This makes it easier for users to interact with and understand the cluster's infrastructure.
Cluster Resource Monitoring: They provide real-time resource utilization monitoring within the cluster. It displays CPU, memory, and network usage metrics. That allows users to identify performance bottlenecks, optimize resource allocation, and make informed scaling and capacity planning decisions.
Application Management: With Kubernetes Dashboard, users can manage and interact with applications deployed in the cluster. It allows for monitoring the status and health of pods, scaling deployments, accessing logs, and performing basic troubleshooting tasks.
Role-Based Access Control (RBAC) Integration: Kubernetes Dashboard integrates with Kubernetes' RBAC systems. Administrators can define roles and permissions. That ensures only authorized users can access specific resources and functionalities within the cluster.
Cons of Kubernetes Dashboard
Limited Customizability: It may have limitations when customizing the interface and visualizations. Users looking for highly tailored or specialized monitoring and management dashboards may require additional tools or customizations.
Advanced Features and Configuration: Kubernetes Dashboard focuses on providing a high-level view and basic management capabilities. It may lack advanced features and configuration options available through other specialized Kubernetes management platforms.
Security Considerations: Kubernetes Dashboard exposes a web-based interface that must be properly secured to prevent unauthorized access. Proper authentication, encryption, and access controls should be implemented to ensure the security of the dashboard and the cluster.
Also Read: Top Kubernetes Dashboard Alternatives
Components of Kubernetes Monitoring
Now that we looked at the top Kubernetes monitoring tools, let's look at some components.
One of the important components of K8s monitoring is cluster monitoring. Through this, users can keep an eye on the overall health and resource utilization of their Kubernetes cluster.
Under this, they monitor various metrics such as CPU and memory usage, node capacity, and network traffic.
Tracking the cluster-level metrics helps users identify the bottlenecks and let them plan for scalability efficiently.
Also Read: How to Use Kubeadm for K8s Clusters?
The other component on the list is container monitoring. Since containers are considered the fundamental building block of the application, it is crucial to monitor them thoroughly.
Container monitoring helps users monitor each container's CPU usage, memory consumption, and network activity.
With the help of this, users can spot any resource-intensive containers, rearrange the resource allocation, and tackle performance-related challenges.
Like containers and clusters, pods are also crucial to the Kubernetes environment. Pods are groups of containers that run the application.
With this, users can monitor multiple metrics like pod health, restarts, and resource utilization. This helps identify potential issues that may impact the availability and performance of your applications.
What is the best tool to monitor EKS?
Prometheus with Grafana is considered one of the best tool combinations for monitoring Amazon Elastic Kubernetes Service (EKS).
What is the APM tool for Kubernetes?
Prometheus and Datadog are popular Application Performance Monitoring tools for Kubernetes.