Extending Kubectl.pptx

Cloud Workstations provides preconfigured, customizable, and secure managed development environments on Google Cloud. Cloud Workstations is accessible through a browser-based IDE, from multiple local code editors (such as IntelliJ IDEA Ultimate or VS Code), or through SSH. Instead of manually setting up development environments, you can create a workstation configuration specifying your environment in a reproducible way

This document describes how to create a 3 node Kubernetes cluster using kubeadm. It provides instructions for initializing the master node, joining the worker nodes to the cluster, and deploying the flannel pod network. Key steps include disabling SELinux and swap, installing Docker, kubeadm and kubelet, initializing the master with kubeadm init, joining the workers with kubeadm join, and applying the flannel YAML.

Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. This training helps you understand key concepts within 3 hours.

This document contains the agenda for the SQLDay 2018 conference. It lists the gold, silver, and bronze sponsors of the event, as well as the strategic partner. It then includes slides on various topics that will be presented, including Kubernetes for data scientists, containers, Docker, GPU and Docker, Kubernetes architecture, deploying to Kubernetes, autoscaling in Kubernetes, Kubeflow, JupyterHub, Tensorflow Training Controller, and Tensorflow Serving. It concludes with a thank you slide.

Out of the box Kubernetes is an Operations platform which is great for flexibility but creates friction for deploying simple applications. Along comes Spinnaker which allows you to easily create custom workflows for testing, building, and deploying your application on Kubernetes. Salvatore Incandela and Fabio Marinelli will give an introduction to Containers and Kubernetes and the default development/deployment workflows that it enables. They will then show you how you can use Spinnaker to simplify and streamline your workflow and help provide a full #gitops style CI/CD.

Containers are everywhere these days. Many of us are containerizing our applications to take advantage of the ease of a single artifact, but what can we do to make deploying these containers to a fleet of servers easier? Kubernetes is arguably the most popular container orchestration system to date. Kubernetes was born out of a decade of research at Google and has seen success; by itself as a fantastic way to orchestrate containers across multiple machines and as a component in other platforms. This talk will begin with the anatomy and setup of a Kubernetes cluster. We'll demonstrate (live) taking a container containing a simple web service and launch our application into a small Kubernetes cluster. Next we'll perform a rolling update to deploy a new container version with zero downtime. Also, we'll check out some cool debugging features Kubernetes provides over the course of our demo.

Continuous delivery/deployment with Kubernetes, Docker and Jenkins running on Google Cloud (Google Container Engine)

This document provides an overview of how to deploy a SQL Server 2019 Big Data Cluster on Kubernetes. It discusses setting up infrastructure with Ubuntu templates, installing Kubespray to manage the Kubernetes cluster lifecycle, and using azdata to deploy the Big Data Cluster. Key steps include creating an Ansible inventory, configuring storage with labels and profiles, and deploying the cluster. The document also offers tips on sizing, upgrades, and next steps like load balancing and monitoring.

The document discusses new features of the Azure Cloud Provider in OpenShift 3.10. Key changes include installer improvements that allow for creating an azure.conf file and internal hostname in Azure NICs. There are also upgrades to Azure disk/file mount options and performance improvements for mounting and unmounting Azure disks. Experimental features mentioned include more advanced options for LoadBalancers, using Azure REST API authentication via Managed Service Identity, and monitoring via Prometheus.

This document provides an agenda and instructions for learning Kubernetes in 90 minutes. The agenda includes exercises on running a first web service in Kubernetes, revisiting pods, deployments and services, deploying with YAML files, and installing a microservices application called Guestbook. Key Kubernetes concepts covered include pods, deployments, services, YAML descriptors, and using deployments to scale applications. The document also provides background on containers, Docker, and the Kubernetes architecture.

The document provides instructions for setting up Kubernetes on two VMs (master and worker nodes) using VirtualBox. It describes the minimum requirements for the VMs and outlines the steps to configure networking and install Kubernetes, container runtime (containerd), and CNI (Flannel). The steps covered include setting up NAT and host-only networking in VirtualBox, configuring the hosts file, installing Kubernetes packages (kubeadm, kubelet, kubectl), initializing the master node with kubeadm, joining the worker node to the cluster, and deploying a sample pod.

Docker containers provide significantly lower resource usage and higher density than traditional virtual machines when running multiple workloads concurrently on a server. When booting 15 Ubuntu VMs with MySQL sequentially, Docker containers boot on average 3.5 seconds compared to 5.8 seconds for KVMs. During steady state operation of 15 active VMs, Docker uses on average 0.2% CPU and 49MB RAM per container, while KVMs use 1.9% CPU and 292MB RAM each. Docker maintains low 1-minute load averages of 0.15, while KVMs average 35.9% under load.

In this slide, I introduce the kubernetes and show an example what is CaaS and what it can provides. Besides, I also introduce how to setup a continuous integration and continuous deployment for the CaaS platform.

The document provides instructions for setting up a Kubernetes cluster with one master node and one worker node on VirtualBox. It outlines the system requirements for the nodes, describes how to configure the networking and hostnames, install Docker and Kubernetes, initialize the master node with kubeadm init, join the worker node with kubeadm join, and deploy a test pod. It also includes commands to check the cluster status and remove existing Docker installations.

Effective Kubernetes is a continuous deployment process that the team understands. Keep it Simple. Think twice before going for more complex solutions. Source: https://github.com/wojciech12/talk_effective_kubernetes Presented at Cloud Native Talks #2 (Online Meetup) - https://www.meetup.com/Cloud-Native-Kubernetes-Warsaw/events/257125529/