Kubernetes observability tutorial: Metrics collection and analysis

In the second part of a Kubernetes observability tutorial series, the article focuses on using Elastic Observability to monitor applications running in Kubernetes by collecting and analyzing various metrics. It highlights the challenges involved in monitoring Kubernetes due to its distributed nature and the variety of technologies involved. The tutorial introduces Metricbeat, a tool used to collect metrics from Kubernetes pods and clusters, and explains how it integrates with Elastic's Kibana for data visualization. Metricbeat can be deployed in two ways: as a single pod for cluster metrics using kube-state-metrics and as a DaemonSet for host-specific metrics via the kubelet API. The tutorial also covers using Metricbeat's autodiscovery feature to apply technology-specific modules for collecting metrics, with examples using NGINX and MySQL. Furthermore, it describes how Metricbeat can augment or replace Prometheus for application metrics collection, facilitating the correlation of metrics with logs and application performance monitoring data. The article concludes by encouraging readers to explore Kibana's pre-built dashboards and to utilize Elastic's services for a comprehensive observability solution.

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