FastAPI framework, high performance, easy to learn, fast to code, ready for production

FastAPI framework, high performance, easy to learn, fast to code, ready for production

This page shows how to perform a rollback on a DaemonSet. 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:

FastAPI framework, high performance, easy to learn, fast to code, ready for production

FastAPI framework, high performance, easy to learn, fast to code, ready for production

FEATURE STATE: Kubernetes v1.21 [stable] This page shows how to limit the number of concurrent disruptions that your application experiences, allowing for higher availability while permitting the cluster administrator to manage the clusters nodes. Before you begin Your Kubernetes server must be at or later than version v1.21. To check the version, enter kubectl version. You are the owner of an application running on a Kubernetes cluster that requires high availability.

In this example, you will run a Job in Indexed completion mode configured such that the pods created by the Job can communicate with each other using pod hostnames rather than pod IP addresses. Pods within a Job might need to communicate among themselves. The user workload running in each pod could query the Kubernetes API server to learn the IPs of the other Pods, but it's much simpler to rely on Kubernetes' built-in DNS resolution.

FastAPI framework, high performance, easy to learn, fast to code, ready for production

FastAPI framework, high performance, easy to learn, fast to code, ready for production

To scale an application and provide a reliable service, you need to understand how the application behaves when it is deployed. You can examine application performance in a Kubernetes cluster by examining the containers, pods, services, and the characteristics of the overall cluster. Kubernetes provides detailed information about an application's resource usage at each of these levels. This information allows you to evaluate your application's performance and where bottlenecks can be removed to improve overall performance.