Kubernetes monitoring involves tracking application performance and resource utilization across cluster components, such as pods, containers, and services. The goal is to gain visibility into the health and security of your clusters. Kubernetes provides built-in features for monitoring, including the resource metrics pipeline that tracks several metrics like node CPU and memory usage and a full metrics pipeline.
Kubernetes monitoring enables you to gain visibility into your cluster behavior. This information is critical to ensure you can proactively manage clusters effectively and efficiently. Since each Kubernetes scenario is unique, you may need to track different metrics and configure alerts to notify specific stakeholders of certain events. However, all scenarios typically require visibility into resource utilization, misconfigurations, failures, and security.
Containers are immutable. While traditional software development models let you update a program as needed, you cannot take the same approach with containers. You can only update the code by retiring a container and replacing it with a new container. It means you need to handle and monitor numerous deployments to keep your applications up-to-date. Doing this manually is inefficient, verging on impossible.
Kubernetes monitoring features and tools enable you to gain visibility into your cluster performance, but visibility is only one advantage of monitoring. Here are additional benefits of Kubernetes monitoring:
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Each Kubernetes scenario has different characteristics requiring a unique set of metrics. When choosing metrics, you should start by assessing your project and then choose the most appropriate metrics. Here are key performance metrics you can start with:
Set Up On-Call Notifications
Kubernetes monitoring is not useful if you do not have an effective way to push notifications to cluster administrators. Adopt tooling that allows you to define staff responsible for a Kubernetes cluster, and push high-priority alerts to them using channels like email, SMS, Slack, or dedicated notification apps (i.e., message redundancies). It is also valuable to define escalation paths, so that if an individual is not available or cannot resolve the issue, the notification is immediately passed to their superior.
Automated alerting tools integrate seamlessly with Kubernetes, and they streamline the incident detection-to-resolution process for response teams through:
Alerting systems ensure that critical incidents rise above the noise, and they orchestrate incident alerts to notify the right people at the right time, every time. That way, critical incidents are resolved promptly without implicated consequences.
Monitoring Kubernetes in a Cloud Environment
Cloud environments present unique challenges. Here are important metrics to monitor when deploying Kubernetes in a cloud environment:
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Track the API Gateway for Microservices
API metrics can help you gain visibility into the performance of your microservices. For example, latency, request rate, and call error metrics can indicate degraded performance in a specific component within a specific service.
You can identify service-level metrics by automatically detecting anomalies on API requests on the service’s load balancer. You can use an ingress controller like Istio or Nginx. It can help you gain visibility into agnostic metrics you can use to measure all Kubernetes services.
Always Alert on High Disk Usage
High disk usage (HDU) is a common issue in Kubernetes workloads. HDU alerts typically indicate there’s an issue that can affect an application’s end-users. You should monitor all of your disk volumes, including the root file system. Ideally, you should set HDU alerts to 75%-80% utilization.
In this article, we explained the basics of Kubernetes monitoring, covered several critical Kubernetes metrics including failed pods, pod restart, and CrashLoopBackOff, and provided four best practices that can help you more effectively monitor your Kubernetes clusters:
We hope this will be useful as you improve the observability of your Kubernetes environment.
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