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Monitoring your clusters is crucial if you’re running Kubernetes in production as it helps maintain smooth operations and improve system stability.
This post will discuss exactly what Kubernetes monitoring is. It’s a lot more than just natively watching a few metrics on the Kubernetes dashboard. We’ll show you some of the best tools you can use to monitor Kubernetes clusters and highlight their advantages and disadvantages.
#What Is Kubernetes?
Kubernetes is an open-source container orchestration tool that allows you to deploy, scale, and manage containerized applications on a shared cluster of nodes. Kubernetes packages the application, the base operating system, the application’s dependencies, and the configuration into one neat pod unit. You can then deploy this pod onto a single node or across many nodes in the cluster to maximize availability and performance.
Kubernetes runs on top of a cluster of nodes and handles the scheduling and distribution of workloads among them. Its primary function is to avoid impedance between application components (e.g., containers) running on different nodes. As a result, it’s suitable for resource-intensive applications such as Hadoop clusters.
#What Is Kubernetes Monitoring?
Kubernetes monitoring is the tracking of the performance and health of a Kubernetes cluster, its components, and the applications running on it. Monitoring Kubernetes clusters is crucial for ensuring that the cluster runs smoothly and that applications perform optimally.
It typically involves tracking various metrics related to the cluster and its components, such as CPU usage, memory utilization, disk I/O, network traffic, and more. You can collect this data using the metrics server and monitoring tools like Prometheus, which can provide real-time insights into the cluster’s health and help you identify issues before they impact the performance of the applications running on it.
Besides monitoring the cluster, Kubernetes monitoring involves monitoring the applications running on it by leveraging its logs. This includes tracking metrics such as request latency, error rates, and resource utilization for individual pods and containers. This data can help operators identify performance issues, troubleshoot problems, and optimize resource usage.
#What Are the Advantages of Kubernetes Monitoring?
Some advantages of Kubernetes monitoring include the following:
Improved cluster performance: Kubernetes monitoring enables you to identify and resolve issues that could impact the performance of your cluster. By monitoring metrics such as CPU usage, memory utilization, and network traffic, you can ensure that your cluster is running efficiently and using resources effectively.
Better resource management: Kubernetes monitoring enables you to track resource utilization across your cluster and individual applications. This data can help you optimize resource allocation, avoid over-provisioning, and reduce costs by ensuring your cluster uses resources effectively.
Increased reliability and availability: Kubernetes monitoring helps you identify potential issues and failures before they impact your applications. By monitoring metrics such as pod health, container uptime, and network connectivity, you can quickly identify and resolve issues and maintain high levels of availability and reliability.
Simplified troubleshooting: Kubernetes monitoring provides visibility into the performance and health of your cluster and applications. By tracking metrics such as request latency and error rates, you can quickly identify the potential root cause of issues and take corrective action.
Stronger security: Kubernetes monitoring can help you detect and respond to security threats by monitoring for unusual network activity, unauthorized access attempts, and other anomalies. This enables you to respond quickly to security incidents and protect your cluster and applications from potential attacks.
#What Are the Disadvantages of Kubernetes Monitoring?
There are, however, a few potential disadvantages of Kubernetes monitoring that you should know about:
Increased complexity: Kubernetes monitoring requires specialized tools and expertise, which can add complexity to your operations. Setting up and configuring monitoring tools can be time-consuming and require additional resources.
Higher resource usage: Monitoring Kubernetes clusters and applications can generate significant amounts of data, consuming additional resources and impacting performance. This can be especially problematic for organizations with large or complex environments.
Cost: Kubernetes monitoring solutions can be expensive, especially for organizations with large or complex environments. Besides the monitoring tools' cost, organizations may need to invest in additional infrastructure to support monitoring.
False positives: Monitoring tools may generate false positives, leading to wasted time and resources investigating nonexistent issues. Tuning monitoring tools to reduce false positives can be challenging and require ongoing effort.
Compliance challenges: Monitoring Kubernetes clusters and applications can raise compliance challenges, particularly for organizations operating in regulated industries. Organizations may need to ensure that their monitoring tools comply with industry-specific regulations and standards.
#What Are the Best Tools for Kubernetes Monitoring?
Several monitoring tools are available for Kubernetes, each with their own strengths and weaknesses. Here are some of the best:
#Prometheus
Prometheus is an open-source monitoring system that’s popular in the Kubernetes community. It’s highly customizable, and you can integrate it with many Kubernetes components. Prometheus can monitor CPU usage, memory utilization, network traffic, and other metrics.
#Grafana
Grafana is a popular visualization tool that can display metrics collected by Prometheus and other monitoring tools. It provides real-time dashboards and alerts, making monitoring Kubernetes clusters and applications easy.
#Datadog
Datadog is a cloud-based monitoring platform that provides real-time visibility into Kubernetes clusters, applications, and infrastructure. It can monitor performance, resource utilization, and security metrics and provide detailed insights and recommendations for optimization.
#New Relic
New Relic is a software-based monitoring and analysis platform that helps organizations monitor and improve their infrastructure and applications. It provides a variety of reports and tools that allow them to analyze and fix issues in real time.
New Relic also offers a variety of analytics tools that can analyze and monitor your applications. These tools can help you understand how your users behave and improve performance.
#Sysdig
Sysdig is a cloud-based platform that provides real-time monitoring and security for Kubernetes clusters and applications. It can monitor performance, resource utilization, and security metrics and provide detailed insights and recommendations.
#Kubernetes Dashboard
Kubernetes Dashboard is an open-source, web-based user interface for managing and monitoring Kubernetes clusters. It provides an overview of the cluster status, detailed metrics about resource use, and data about the nodes and pods in the cluster. It also allows users to create and edit resources from the cluster.
Kubernetes Dashboard provides an easy way to manage and monitor Kubernetes clusters. It helps users keep track of the resources in the cluster, the nodes' condition, and the pods' health.
#Dynatrace
The Dynatrace platform is a comprehensive solution that enables organizations to monitor and optimize the performance of their digital experiences and applications. You can use it to identify and address various issues related to the availability and performance of their applications.
You can also use Dynatrace to monitor hybrid and cloud environments. It can provide insight into the performance of specific applications running on different platforms.
#How Do I Monitor Performance in Kubernetes?
Here’s a step-by-step tutorial on how to conduct monitoring with Kubernetes:
First, you’ll need to install a monitoring solution. We’ll use Prometheus and install Prometheus-operator using helm. That way, you won’t need a lot of extra configurations because the operator’s helm charts take care of it beforehand.
helm install stable/prometheus-operator
To confirm that you have the required resources, you can run kubectl get all, where you’ll notice that apart from Prometheus-operator, you have Grafana and Kube state metrics deployments. You’ll use Grafana for visualization and Kube state metrics to scrape Kubernetes components metrics.
Ensure that you have a node exporter daemonset running. This will convert cluster metrics to Prometheus metrics format.
To access Grafana, you’ll use port forward. That way, you can access it outside your cluster.
kubectl --namespace monitoring port-forward svc/grafana 3000
You can then access it from your local host at port 3000. The login credentials are admin for the username and admin for the password (according to the documentation).
You’ll follow the same steps to access Prometheus by using kubectl port-forward.
kubectl --namespace monitoring port-forward svc/prometheus-k8s 9090
From the user interfaces, you can see the metrics scraped and the alerts set, including target endpoints.
You’ll need a metric exporter unique to your language or utility and a service monitor to monitor different applications in your cluster and expose their metrics for Prometheus to scrape. You can find Prometheus exporters on the Prometheus website.
#Conclusion
It’s important for anyone working with Kubernetes to monitor the system’s behavior periodically, including through logging and metrics. Logging can help you identify problems and troubleshoot them. If a metric dips below a certain point, Kubernetes will initiate an action or take corrective measures to restore things to normal levels. You could also try using Loft to simplify your Kubernetes deployment and easily manage your application.
This post was written by Mercy Kibet. Mercy is a full-stack developer with a knack for learning and writing about new and intriguing tech stacks.
