Kubernetes is a container orchestration product that’s surging in popularity because of the way it simplifies container deployment. The benefits of Kubernetes include auto-scaling abilities, load balancing, remote storage, and its known and stable API.
Kubernetes is an open source container orchestrator, which was started initially by Google but is now hosted by the Cloud Native Computing Foundation (CNCF). Kubernetes delivers container orchestration across several physical and virtual environments, such as computers or the cloud. Kubernetes deploys abstraction at the pod and service levels.
The simplification of container deployment through Kubernetes, however, increases the complexity of performance management. Performance management delivers insight into computing performance and any roadblocks interrupting that performance for end users. It’s a crucial toolset for enterprises to have in place. Enterprises typically use more than ten performance management tools to keep a pulse on their services. The most common of performance management tools include application performance management (APM), network performance management (NPM), and unified performance management (UPM), which is a converged solution of APM and NPM.
The Intricacy of Kubernetes Monitoring
It’s common to monitor both the host and its applications. When it comes to Kubernetes monitoring, there are two additional items that need visibility: the pods and the container cluster itself. A pod is a minuscule unit consisting of one or a group of containers that share the same storage and rule set for running the containers. The contents of the pod are co-located, co-scheduled, and operate in a shared context. The overall intent of a pod is to “simplify application deployment and management by providing a higher-level abstraction than the set of their constituent applications.”
Kubernetes monitoring can become complex because Kubernetes automatically schedules containers’ runtime. Labels are the solution. IT administrators attach labels to pods to distinguish pod attributes that are pertinent to users. Kubernetes said that labels “are absolutely crucial for monitoring since all metrics and events will be sliced and diced using labels across the different layers of your infrastructure.” Attaching performance metrics to labels provides the insight needed to monitor performance within the pod. Another monitoring tool for pods is service discovery, which detects a change in pod and container configuration. Overall, it’s imperative to check the health of both pod deployment and currently running pods.
The collection of metrics required to maintain a robust Kubernetes performance also needs to focus on resource utilization. Optimal resource utilization covers a variety of checks, including CPU and memory, container health, disk usage, NPM, and APM.
Third-Party Kubernetes Monitoring
Kubernetes offers performance management products for its product, including Heapster, which is a cluster-wide aggregator, and cAdvisor, an open source container resource and performance analysis agent. With its rising fame, multiple third-party vendors created other Kubernetes monitoring solutions. We rounded up a few of them here, but more solutions exist in the marketplace.