real time scenarios working with docker and kubernetes

Although pods may still be running on node 1, we omitted them from this diagram for clarity. This diagram differs slightly from the last one. The kube-proxy component routes requests for these service IPs from anywhere in the cluster. These services maintain a list of backend pods and load balances across them. Services fixes this by providing a stable virtual IP frontend to these pods.

This presents a problem for any service or DNS record relying on these pod IPs. However, these virtual IPs are randomly assigned. Having pods on a virtualized network solves significant issues with providing dynamically scheduled networked workloads. Network traffic, shown by the arrow connecting pods B and C, is facilitated by the network overlay and pods do not have knowledge about the host’s networking stack. The overlay assigned each of these pods an IP and can listen on the same port despite conflicts they (is the “they” referring to the pods or the overlay? If it’s the pods please replace “they” with “pods” and if it’s the overlay, “they” should be changed to “it” would have listening at the host level.

Here we have two nodes, each running two pods, all connected to each other via a network overlay. This diagram shows the relationship between pods and network overlays. In this model, pods get their own virtual IP addresses to allow different pods to listen to the same port on the same machine. To solve this problem, Kubernetes uses a network overlay. However, because pods may share the same host on the same ports, workloads must be scheduled in a way that ensures ports do not conflict with each other on a single machine. Each pod is composed of multiple containers that can optionally expose ports. Pods are the scheduling primitives in Kubernetes. To be successful in debugging Kubernetes clusters, we need to understand all of the parts. Networking in Kubernetes has several components and can be complex for beginners. We’ll use it’s trace latency on requests to our Kubernetes pods to identify problems in the network stack. AppOptics is a next-generation application performance monitoring (APM) and infrastructure monitoring solution. In this article, we will use AppOptics ™ tracing to diagnose some latency issues with applications running on Kubernetes. When cloud providers have availability zone outages, or are in constrained environments such as bare metal, being able to debug and successfully resolve problems in our nodes is still an important skill to have. Fortunately, Kubernetes insulates us against most of these issues with its ability to reschedule workloads, and just replacing nodes when issues occur. While you can expect a typical Kubernetes cluster to be stable most of the time, like all software, issues can occur in production. Maintaining a Kubernetes cluster requires proactive maintenance and monitoring to help prevent and diagnose issues that occur in clusters. Kubernetes is a container orchestrator that provides a robust, dynamic environment for reliable applications.

Real time scenarios working with docker and kubernetes