This page describes the lifecycle of a Pod. Pods follow a defined lifecycle, starting in the Pending phase, moving through Running if at least one of its primary containers starts OK, and then through either the Succeeded or Failed phases depending on whether any container in the Pod terminated in failure. Like individual application containers, Pods are considered to be relatively ephemeral (rather than durable) entities. Pods are created, assigned a unique ID (UID), and scheduled to run on nodes where they remain until termination (according to restart policy) or deletion.

Make your HTTP (or HTTPS) network service available using a protocol-aware configuration mechanism, that understands web concepts like URIs, hostnames, paths, and more. The Ingress concept lets you map traffic to different backends based on rules you define via the Kubernetes API.

In the scheduling-plugin NodeResourcesFit of kube-scheduler, there are two scoring strategies that support the bin packing of resources: MostAllocated and RequestedToCapacityRatio. Enabling bin packing using MostAllocated strategy The MostAllocated strategy scores the nodes based on the utilization of resources, favoring the ones with higher allocation. For each resource type, you can set a weight to modify its influence in the node score. To set the MostAllocated strategy for the NodeResourcesFit plugin, use a scheduler configuration similar to the following:

Application logs can help you understand what is happening inside your application. The logs are particularly useful for debugging problems and monitoring cluster activity. Most modern applications have some kind of logging mechanism. Likewise, container engines are designed to support logging. The easiest and most adopted logging method for containerized applications is writing to standard output and standard error streams. However, the native functionality provided by a container engine or runtime is usually not enough for a complete logging solution.

kube-state-metrics, an add-on agent to generate and expose cluster-level metrics.

Production-Grade Container Orchestration

This page shows how to use an Init Container to initialize a Pod before an application Container runs. Before you begin You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:

Debugging common cluster issues.

Configure load balancing, port forwarding, or setup firewall or DNS configurations to access applications in a cluster.

Node Problem Detector is a daemon for monitoring and reporting about a node's health. You can run Node Problem Detector as a DaemonSet or as a standalone daemon. Node Problem Detector collects information about node problems from various daemons and reports these conditions to the API server as Node Conditions or as Events. To learn how to install and use Node Problem Detector, see Node Problem Detector project documentation.